JP7820465B2 - system - Google Patents

Description

The technology disclosed herein relates to a system.

Patent document 1 discloses a persona chatbot control method executed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot's character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Japanese Patent Application Laid-Open No. 2022-180282

Conventional cat toys have difficulty responding to individual cat preferences and behavioral patterns, and it has also been difficult to adapt to changes in cat behavioral patterns. Furthermore, there have been no toys that can understand how cats play and provide appropriate stimulation based on that.

The present invention provides a spherical, freely mobile device, a means for operating the device from a smartphone, a sensor installed in the device that detects the cat's movements and behavioral patterns, generative AI that analyzes data from the sensor and understands the cat's preferences and play styles, and a means for providing appropriate reactions and stimuli to the cat based on the AI. This makes it possible to respond to each cat's individual preferences and behavioral patterns and to respond to changes in these. It is also possible to understand the cat's play style and provide appropriate stimuli based on that.

1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. FIG. 10 is a conceptual diagram illustrating an example of the configuration of a data processing system according to a second embodiment. FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. FIG. 10 is a conceptual diagram illustrating an example of the configuration of a data processing system according to a third embodiment. FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. FIG. 10 is a conceptual diagram illustrating an example of the configuration of a data processing system according to a fourth embodiment. FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. 1 shows an emotion map onto which multiple emotions are mapped. 1 shows an emotion map onto which multiple emotions are mapped. FIG. 10 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. FIG. 10 is a sequence diagram showing a processing flow of the data processing system in Application Example 1 of Form Example 1. FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2. FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a third embodiment of the third form example. FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3. FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined.

Below, an example of an embodiment of a system relating to the technology disclosed herein is described with reference to the accompanying drawings.

First, let me explain the terminology used in the following explanation.

In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, a processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose Computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

In the following embodiments, coded random access memory (RAM) is memory in which information is temporarily stored and is used by the processor as work memory.

In the following embodiments, the coded storage refers to one or more non-volatile storage devices that store various programs, parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

In the following embodiments, a communication I/F (Interface) with a symbol is an interface that includes a communication processor, an antenna, etc. The communication I/F controls communication between multiple computers. Examples of communication standards that can be applied to the communication I/F include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

In the following embodiments, "A and/or B" is synonymous with "at least one of A and B." In other words, "A and/or B" means that it may be just A, just B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and/or B" also applies when three or more things are expressed connected by "and/or."

[First embodiment]

Figure 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

As shown in FIG. 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

The data processing device 12 includes a computer 22, a database 24, and a communication I/F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and communication I/F 26 are also connected to the bus 34. The communication I/F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and/or a LAN (Local Area Network).

The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I/F 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

The reception device 38 is equipped with a touch panel 38A, a microphone 38B, etc., and receives user input. The touch panel 38A detects contact with an indicator (e.g., a pen or finger) to receive user input via the indicator. The microphone 38B detects the user's voice to receive user input via voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

The output device 40 is equipped with a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible by the user 20 (e.g., audio and/or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

The communication I/F 44 is connected to the network 54. The communication I/Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54.

Figure 2 shows an example of the main functions of the data processing device 12 and smart device 14.

As shown in FIG. 2, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

Storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

Next, we will explain the identification process performed by the identification processing unit 290 of the data processing device 12.

"Example 1"

One aspect of the present invention provides a spherical device. This device has an internal driving source such as a motor or battery, and is able to move around freely. A sensor is placed on the outside of the device to detect the cat's movements and behavioral patterns. This sensor detects the cat's movements and behavioral patterns and sends the data to a generative AI. The generative AI analyzes the received data and understands the cat's preferences and play styles. Based on this understanding, it then sends instructions to the device to provide the cat with appropriate reactions and stimuli. The device operates in accordance with the instructions and provides the cat with appropriate reactions and stimuli.

"Example 2"

As a specific example, if a cat exhibits aggressive behavior toward the device, a sensor will detect that behavior and send that information to the generative AI. The generative AI will analyze the information and understand that the cat prefers aggressive play. Based on that understanding, it will instruct the device to perform actions that will stimulate the cat. The device will then act in accordance with those instructions and provide the cat with appropriate stimulation.

"Example 3"

In addition, the generative AI accumulates data on the cat's behavior over time and learns changes in the cat's behavior patterns based on that accumulated data. For example, if a cat initially prefers aggressive play but develops a preference for gentler play over time, the generative AI will learn this change and issue appropriate instructions to the device based on that learning. This makes it possible to provide appropriate reactions and stimuli in response to changes in the cat's behavior patterns.

The processing flow for each example is explained below.

"Example 1"

Step 1: The spherical device starts operating, and the sensors that detect the cat's movements and behavior patterns begin to function.

Step 2: The sensor detects the cat's movements and behavior patterns and sends that data to the generative AI.

Step 3: The generative AI analyzes the received data and understands the cat's preferences and play styles.

Step 4: Based on its understanding, the generative AI sends instructions to the device to provide the cat with appropriate reactions and stimuli.

Step 5: The device acts according to the instructions and provides the cat with the appropriate reaction or stimulus.

"Example 2"

Step 1: The cat exhibits aggressive behavior toward the device.

Step 2: The sensor detects the behavior and sends that information to the generative AI.

Step 3: The generative AI analyzes the information and understands that cats prefer aggressive play.

Step 4: Based on that understanding, the generative AI instructs the device to perform actions that stimulate the cat.

Step 5: The device follows the instructions and provides the appropriate stimulation to the cat.

"Example 3"

Step 1: The generative AI accumulates cat behavior data over time.

Step 2: The generative AI learns changes in the cat's behavioral patterns based on the accumulated data.

Step 3: The generative AI issues appropriate instructions to the device based on its learning.

Step 4: The device operates according to the instructions, providing appropriate reactions and stimuli in response to changes in the cat's behavioral patterns.

(Example 1)

Next, we will explain Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Conventional animal play equipment struggled to provide the appropriate reactions and stimulation needed to keep animals interested, resulting in animals quickly becoming bored. Furthermore, the lack of a system capable of analyzing animals' behavioral patterns in real time and controlling their movements accordingly made it difficult to provide play styles tailored to each animal's individual preferences.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavioral patterns, generative artificial intelligence that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the artificial intelligence, means for generating instructions for controlling the operation of the device and sending the instructions to the device, and means for the device to operate in accordance with the instructions and provide appropriate reactions and stimuli to the animal. This makes it possible to analyze the behavioral patterns of animals in real time and provide appropriate reactions and stimuli according to the preferences of each individual animal.

The "device" is a spherical, freely movable device equipped with sensors that detect the movements and behavior patterns of animals.

An "information terminal" is an electronic device that provides a means for operating a device, including smartphones and tablets.

A "sensor" is a device that detects animal movements and behavior patterns and is installed in the device.

"Generative AI" is an artificial intelligence system that analyzes data from sensors and understands animals' preferences and play styles.

"Means for providing reactions and stimuli" refers to mechanisms and methods for providing appropriate reactions and stimuli to animals based on generative artificial intelligence.

"Means for generating instructions" refers to the mechanism or method for generating instructions to control the operation of a device based on data analyzed by generative artificial intelligence.

"Means for sending instructions" refers to communication means for sending the generated instructions to the device.

"Means for controlling behavior" refers to the mechanism or method by which the device operates according to the instructions it receives and provides the animal with an appropriate reaction or stimulus.

This invention is a system that analyzes animal behavior patterns in real time and provides appropriate reactions and stimuli based on the preferences of each individual animal. Specific embodiments of this system are described below.

System Configuration

The system consists of the following main components:

1. Device: A spherical, freely movable device equipped with sensors that detect animal movements and behavior patterns.

2. Information terminal: An electronic device that provides a means for operating a device, including smartphones and tablets.

3. Sensor: A device that detects animal movements and behavior patterns and is installed in the device.

4. Generative AI: An artificial intelligence system that analyzes data from sensors to understand animals' preferences and play styles.

5. Means for providing reactions and stimuli: Mechanisms and methods for providing appropriate reactions and stimuli to animals based on generative artificial intelligence.

6. Means for generating instructions: A mechanism or method for generating instructions to control the operation of a device based on data analyzed by generative artificial intelligence.

7. Means for sending instructions: A communication means for sending the generated instructions to the device.

8. Means for controlling behavior: The mechanism or method by which the device operates according to the instructions it receives and provides the animal with the appropriate reaction or stimulus.

System Operation

1. Initialize the device

The user turns on the device.

The device checks the internal motor and battery to ensure they are working properly.

The device will calibrate the sensors to ensure accurate data collection.

2. Data Collection

The device uses sensors to detect animal movements and behavior patterns in real time.

The device temporarily stores detected data.

3. Data Transmission

The device sends the collected data to the server.

The server receives the data and prepares it for analysis.

4. Data Analysis

The server passes the received data to the generative artificial intelligence.

Generative AI analyzes data to understand animals' preferences and behavioral patterns.

5. Instruction Generation

Based on the analysis results, generative AI generates instructions to provide the animal with appropriate reactions and stimuli.

The server receives the generated instructions.

6. Sending instructions

The server sends the generated instructions to the device.

The terminal receives the instructions and transmits them to the device.

7. Device Operation

The device operates according to the instructions received by the terminal.

The device provides the animal with appropriate reactions and stimuli.

Specific examples

For example, if a cat approaches a device, the device's sensor will detect the movement. The server will determine that the cat is interested in the device and send the data to the generative AI. The generative AI will then generate an instruction to "move the device slightly to attract the cat." The server will then send the instruction to the device, which will then move the device.

Example prompt

"Generate an appropriate reaction when a cat approaches the device."

"If my cat likes to chase the device, what movements should I give it?"

In this way, the system can analyze the animal's behavior in real time and provide appropriate reactions, keeping the animal engaged.

The flow of the identification process in Example 1 will be explained using Figure 11.

Step 1: Initialize your device

Input: The user turns on the device.

Processing: The device checks the internal motors and batteries to ensure they are working properly. It also calibrates the sensors to ensure accurate data collection.

Output: The device is ready to operate normally.

Specific operation: The user presses the device's power button, and the device checks the device's LED indicator to confirm normal operation.

Step 2: Collect data

Input: The device detects animal movements and behavior patterns.

Processing: The device uses its sensors to detect animal movements and behavior patterns in real time and temporarily store the data.

Output: Data on animal movements and behavior patterns is collected.

Specific operation: The device uses a sensor to detect the cat's movement as it approaches the device and stores the data in memory.

Step 3: Send data

Input: Collected animal movement and behavior pattern data.

Processing: The device sends the collected data to the server. The server receives the data and prepares it for analysis.

Output: Data is sent to the server and ready for analysis.

Specific operation: The device sends data to the server via Wi-Fi, and the server receives the data and stores it in a database.

Step 4: Data Analysis

Input: Animal movement and behavior pattern data received by the server.

Processing: The server passes the received data to the generative AI, which analyzes the data to understand the animal's preferences and behavioral patterns.

Output: Analysis results on animal preferences and behavior patterns.

Specific operation: The server inputs data into the generative AI, which then concludes that "cats like to chase balls."

Step 5: Generate instructions

Input: Analysis results from generative artificial intelligence.

Processing: Based on the analysis results, the generative AI generates instructions to provide the animal with appropriate reactions and stimuli. The server receives the generated instructions.

Output: Instructions for providing the appropriate reaction or stimulus to the animal.

Specific operation: The generative artificial intelligence generates the instruction "rotate the device to the right," and the server receives that instruction.

Step 6: Send instructions

Input: Generated instructions.

Processing: The server sends the generated instructions to the terminal, which receives the instructions and transmits them to the device.

Output: Instructions sent to the device.

Specific operation: The server sends instructions to the terminal via Wi-Fi, and the terminal receives the instructions and passes them on to the device.

Step 7: Device Operation

Input: Instructions received by the terminal.

Processing: The terminal operates the device according to the instructions received, providing the animal with the appropriate reaction or stimulus.

Output: The appropriate reaction or stimulus provided to the animal.

Specific behavior: The terminal controls the device's motor and rotates it to the right. The device rotates in front of the cat, and the cat chases it.

(Application Example 1)

Next, we will explain Application Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Existing pet devices struggled to fully understand animals' movements and behavior patterns and provide appropriate reactions and stimuli. Furthermore, physical stores lacked the means to provide a fun environment for animals. This meant that efforts to reduce animal stress and improve customer satisfaction were not fully achieved.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

In this invention, the server includes a spherical device that can move around freely, means for operating the device from a smartphone, a sensor installed in the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and ways of playing, means for providing the animal with appropriate reactions and stimuli based on the AI, and means for the device to detect the animal's movements within the physical store and provide appropriate reactions and play using the generative AI. This allows the animal to have fun within the physical store, improving customer satisfaction.

A "spherical device that can move freely" is a spherical device that has an internal power source such as a motor or battery and can move in any direction.

"Means for operating from a smartphone" refers to interfaces and applications for remotely controlling the operation of a device using a smartphone.

A "sensor that detects animal movements and behavior patterns" is a device that senses the position, speed, direction, and other movements of animals and collects that data.

"Generative AI" is an artificial intelligence model that analyzes collected animal movement and behavior data to understand animals' preferences and play styles.

"Means for providing appropriate reactions and stimuli to animals" refers to a mechanism that allows animals to take appropriate actions or react based on instructions generated by the generative AI.

"Means for detecting animal movements within a physical store and using generative AI to provide appropriate reactions and play" refers to a system that detects animal movements within a physical store in real time, sends that data to generative AI, and provides appropriate reactions and play for the animals.

This invention is a system for providing an environment in a physical store where animals, particularly cats, can have fun. The system includes a spherical, freely moving device, a means for operating it from a smartphone, sensors that detect the animal's movements and behavior patterns, generative AI, and a means for providing the animal with appropriate reactions and stimuli.

System Configuration

1. Spherical device:

It is equipped with a motor and battery inside, allowing it to move in any direction.

Sensors are placed on the exterior to detect animal movement.

2. How to operate from your smartphone:

An application is provided for remotely controlling the device's operation using a smartphone.

3. Sensors that detect animal movements and behavior patterns:

It detects the animal's location, speed, direction, and other movements and collects that data.

4. Generative AI:

Analyze collected animal movement and behavior data to understand animals' preferences and play styles.

Generative AI models are used to generate appropriate reactions and stimuli for animals.

5. How to provide appropriate reactions and stimuli to animals:

The robot will then perform appropriate actions and reactions towards the animal based on the instructions generated by the generative AI.

Program processing explanation

The server sends the animal's movement data collected from the sensors to the generative AI. The generative AI analyzes this data to understand the animal's preferences and play styles. Based on what it understands, it generates instructions to provide the animal with appropriate reactions and stimuli. These instructions are sent to the device, which then performs the appropriate action on the animal.

The hardware used includes sensors to detect animal movement, motors to power the device, and batteries to power the device. The software used includes a generative AI model, a sensor control module, and a motor control module.

Specific examples

For example, when a cat approaches a device in a pet shop, a sensor detects its movement and sends the data to the generative AI. The generative AI then generates movements that will interest the cat and sends those instructions to the device. The device then starts moving as if the cat is chasing it, attracting the cat's interest.

Also, when a cat touches the device in a cafe, a sensor detects the movement and sends the data to the generative AI. The generative AI generates a rotating motion that the cat will enjoy and sends that instruction to the device. The device then rotates in a way that the cat will enjoy, attracting its interest.

Example prompt

"Enter your cat's movement data. This data includes the cat's position, speed, direction, etc. Use this data to generate reactions that will interest your cat."

The above is an embodiment of the invention. This system allows animals to have fun in physical stores, improving customer satisfaction.

The flow of the specific processing in Application Example 1 will be explained using Figure 12.

Step 1:

The sensor detects the animal's movement. The sensor collects data such as the animal's position, speed, and direction, and sends that data to the server. The input is the animal's movement data, and the output is the movement data sent to the server.

Step 2:

The server sends the animal's movement data received from the sensors to the generative AI. The generative AI analyzes this data and understands the animal's preferences and play styles. The input is movement data from the sensors, and the output is the analysis results by the generative AI.

Step 3:

The generative AI generates appropriate reactions and stimuli for the animal based on the analysis results. The generative AI generates actions and responses that will interest the animal and sends these instructions to the server. The input is the analysis results of the animal's movement data, and the output is the generated reactions and stimulus instructions.

Step 4:

The server sends the instructions received from the generative AI to the device. The device begins to operate based on the received instructions. The input is the instructions from the generative AI, and the output is the device's operation.

Step 5:

The device provides appropriate reactions and stimuli to the animal. The device responds to the animal's movements and performs actions that the animal enjoys. The input is instructions from the server, and the output is reactions and stimuli to the animal.

Step 6:

The device detects physical stimuli from the animal and feeds that data back to the server. The server then sends this data to the generative AI, where it is stored as animal behavior data. The input is physical stimulus data from the animal, and the output is feedback data for the generative AI.

These are the specific processing steps of this system. The specific actions performed at each step allow animals to have fun in physical stores.

(Example 2)

Next, we will explain Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Previous cat devices simply detected a cat's behavior and were unable to provide appropriate stimuli based on the cat's individual behavioral patterns and preferences. They also lacked the functionality to accumulate cat behavior data and learn over time, making it difficult to respond to changes in a cat's behavioral patterns. Furthermore, they lacked the functionality to automatically respond to physical stimuli from the cat and provide feedback on that response. This made it difficult to maintain a cat's interest, and made effective play and training impossible.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

In this invention, the server includes sensor means for detecting the cat's behavior, terminal means for transmitting data from the sensor means to the server, means for analyzing the data using a generative AI model in the server means, device means for providing stimuli to the cat based on instructions from the server means, and terminal means for controlling the device means. This makes it possible to analyze cat behavior data in real time and provide appropriate stimuli based on the individual cat's behavioral patterns and preferences. In addition, by accumulating cat behavior data over time and learning changes in behavioral patterns based on that data, the cat's interest can be sustained. Furthermore, the function of automatically responding to physical stimuli from the cat and providing feedback on that response allows for effective play and training.

"Sensor means" refers to a device for detecting cat behavior, including motion sensors and cameras.

"Terminal means" refers to a device for transmitting data from sensor means to a server, and includes a data transmission module and a communication device.

The "server means" is a device that analyzes the received data using a generative AI model and generates instructions to provide appropriate stimulation to the cat.

A "generative AI model" is an artificial intelligence model that analyzes cat behavior data and generates instructions to provide appropriate stimuli based on the cat's behavioral patterns and preferences.

"Device means" refers to a device for providing stimuli to the cat based on instructions from the server means, and includes a robotic arm, a laser pointer, etc.

"Real-time" means that data is processed immediately the moment it is generated, providing an immediate response without delay.

"Behavioral patterns" refer to the tendencies and habits of a series of behaviors that a cat displays in response to specific situations or stimuli.

"Feedback" refers to the device's means' response to physical stimuli from the cat being sent back to the generative AI model, allowing the generative AI model to learn and generate more appropriate instructions.

This invention is a system that detects cat behavior, analyzes the data, and provides appropriate stimuli to the cat. This system includes sensor means, terminal means, server means, a generative AI model, and device means.

First, the device detects the cat's behavior using a sensor. Sensors include motion sensors and cameras. For example, if the cat scratches the device with its claws, this behavior is detected in real time.

The device then transmits the detected behavioral data to a server via a data transmission module. This data includes the cat's movement patterns and location information. For example, it includes the time and location information when the cat scratches the device.

The server inputs the received data into a generative AI model to analyze the cat's behavior. Examples of generative AI models used include OpenAI's (registered trademark) GPT-4 (registered trademark). The generative AI model determines whether the cat enjoys aggressive play. For example, if the cat frequently exhibits aggressive behavior toward the device, it learns that behavioral pattern.

Then, based on the analysis results, the server instructs the device to perform appropriate actions to stimulate the cat, for example, moving the robotic arm to attract the cat's interest.

Finally, the terminal receives instructions from the server and controls the device to provide appropriate stimuli to the cat, for example, moving a laser pointer to stimulate the cat.

As a concrete example, consider the following scenario: When a cat scratches its claws at the device, the motion sensor detects this movement. The sensor sends this information to the server via the data transmission module. The generative AI model analyzes the data and understands that cats prefer aggressive play. The generative AI model then instructs the robotic arm to perform actions that will attract the cat's interest. The robotic arm operates according to these instructions, providing the cat with appropriate stimuli.

Examples of prompts to input into a generative AI model include:

"Your cat has clawed at the device. Analyze this behavior and determine whether your cat prefers aggressive play. Then instruct the device on the appropriate action to stimulate your cat."

The above is a form for implementing this invention.

The flow of the identification process in Example 2 will be explained using Figure 13.

Step 1:

The device uses sensor means to detect the cat's behavior. Specifically, motion sensors and cameras monitor the cat's movements in real time and detect aggressive behavior. For example, if the cat digs its claws into the device, this behavior will be detected.

Input: Cat movement

Output: Detected cat behavior data (e.g., time and location of cat claw movements)

Step 2:

The device sends the detected behavioral data to the server via the data transmission module. Specifically, the data obtained from the sensor is packetized and sent to the server via the network.

Input: Detected cat behavior data

Output: Behavioral data sent to the server

Step 3:

The server inputs the received data into a generative AI model to analyze the cat's behavior. Specifically, it inputs behavioral data into a generative AI model (e.g., GPT-4) to determine whether the cat prefers aggressive play.

Input: Behavioral data sent to the server

Output: Analysis of cat behavior patterns (e.g., cats prefer aggressive play)

Step 4:

Based on the analysis results, the server instructs the device on the appropriate actions to stimulate the cat. Specifically, it generates movement instructions for the robot arm and laser pointer based on the analysis results of the generative AI model.

Input: Analysis results of cat behavior patterns

Output: Commands to the device (e.g., moving the robotic arm to attract the cat's attention)

Step 5:

The terminal receives instructions from the server and controls the device to provide appropriate stimuli to the cat. Specifically, it moves the robotic arm and laser pointer to entertain the cat.

Input: Operation instructions from the server

Output: Appropriate stimuli provided to the cat (e.g., robotic arm movement, laser pointer movement)

The above is the specific flow of processing for this system's program.

(Application Example 2)

Next, we will explain Application Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Conventional safety monitoring systems in factories have the drawback of being unable to detect abnormal worker or machine behavior in real time and quickly respond appropriately. Furthermore, systems that understand animal behavior and provide appropriate stimuli are limited, and they are unable to learn changes in animal behavior patterns. To solve these issues, a system is needed that can monitor animal and worker behavior in real time, detect abnormal behavior, and respond appropriately.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

In this invention, the server includes a spherical device that can move around freely, means for operating the device from an information terminal, a sensor installed in the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, a sensor that detects abnormal behavior of workers and machines within the factory, means for transmitting data from the sensor to the generative AI and analyzing the abnormal behavior, and means for instructing an appropriate response based on the analysis results. This makes it possible to learn changes in the animal's behavior patterns and provide appropriate stimuli, as well as detect abnormal behavior of workers and machines within the factory in real time and respond quickly.

A "spherical, freely movable device" is a device that has a spherical shape and the ability to physically move freely.

An "information terminal" is an electronic device used to remotely control devices such as smartphones and tablets.

A "sensor that detects animal movements and behavior patterns" is a device that detects animal movements and behavior in real time and acquires that data.

"Generative AI" is an artificial intelligence system that analyzes acquired data, understands the behavioral patterns of animals and workers, and generates appropriate responses.

"Means for providing appropriate reactions and stimuli to animals" refers to devices and methods for providing appropriate reactions and stimuli to animals based on the analysis results of generative AI.

"Sensors that detect abnormal behavior of workers and machines in factories" are devices that monitor the behavior of workers and machines in factories and detect abnormal behavior in real time.

"Means for analyzing abnormal behavior" refers to a method or device for sending data on detected abnormal behavior to the generative AI and analyzing that data.

"Means for instructing appropriate responses" refers to a method or device for instructing appropriate responses to abnormal behavior based on the analysis results of generative AI.

As an embodiment of this invention, the following system is constructed.

First, a spherical, freely movable device is prepared. This device is equipped with sensors that detect the animal's movements and behavioral patterns. The device can be controlled from an information terminal (e.g., a smartphone or tablet).

Next, we prepare the generative AI. This generative AI analyzes the data obtained from the sensors to understand the animal's preferences and play styles. The generative AI generates instructions to provide the animal with appropriate reactions and stimuli.

In addition, sensors will be installed within the factory to detect abnormal behavior by workers or machines. These sensors will also send data to the generative AI, which will analyze the abnormal behavior. The generative AI will then instruct the appropriate response to the abnormal behavior.

A specific example would be the following system.

1. Animal behavior monitoring system

If an animal exhibits aggressive behavior toward the device, a sensor detects the behavior and sends that information to the generative AI. The generative AI analyzes the information and understands that the animal prefers aggressive play. Based on this understanding, it then instructs the device to perform actions that will stimulate the animal. The device then acts according to those instructions and provides the animal with appropriate stimulation.

2. Factory Safety Monitoring System

If a worker or machine in a factory behaves abnormally, a sensor detects the behavior and sends the data to the generative AI. The generative AI analyzes the data and detects abnormal behavior. If an abnormality is detected, the generative AI will instruct the appropriate response, such as sounding an alarm or halting work.

The hardware used includes sensors to detect animal movement, sensors to detect abnormal behavior in factories, information terminals, and spherical devices. The software used is a generative AI model.

As a concrete example, the following prompt sentence could be input into a generative AI model:

Example prompt:

"Analyze the data when a worker falls, and if an abnormality is detected, issue an instruction to sound an alarm."

In this way, it is possible to learn changes in animal behavior patterns and provide appropriate stimuli, as well as detect abnormal behavior of workers or machinery within the factory in real time and respond quickly.

The flow of the specific processing in Application Example 2 will be explained using Figure 14.

Step 1:

Sensors detect the movement of animals and workers.

Input: Animal and worker movement data

Data processing: Sensors collect operational data in real time and convert it into digital signals.

Output: Digitized motion data

Step 2:

Data obtained from the sensors is sent to the generative AI.

Input: Digitized motion data

Data processing: The data acquired by the sensor is packetized in order to be sent to the generative AI.

Output: Packetized motion data

Step 3:

Generative AI analyzes movement data.

Input: Packetized motion data

Data calculation: Generative AI analyzes movement data to identify abnormal movements and animal behavior patterns.

Output: Analysis results (detection of abnormal behavior and animal behavior patterns)

Step 4:

Generative AI will instruct appropriate responses based on the analysis results.

Input: Analysis results

Data calculation: Based on the analysis results, generative AI determines the appropriate response (e.g., sound an alarm, activate the device, etc.).

Output: Action instructions

Step 5:

Devices and information terminals operate according to the instructions of generative AI.

Input: Response instructions

Specific actions: The device provides appropriate stimuli to the animal, the information terminal sounds an alarm, etc.

Output: Action taken (stimulates animal, sounds alarm, etc.)

Step 6:

The generative AI receives feedback from the results of its actions.

Input: Result of the action performed

Data processing: Generative AI evaluates the execution results and accumulates data to reflect in the next response.

Output: Updated behavioral database

These steps will enable the system to learn changes in animal behavior patterns and provide appropriate stimuli, as well as detect abnormal behavior of workers or machinery within the factory in real time and respond quickly.

(Example 3)

Next, we will explain Example 3 of Form Example 3. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Previous animal devices struggled to learn an animal's behavioral patterns in real time and provide appropriate reactions and stimuli based on those patterns. Furthermore, there were no systems that could accumulate animal behavioral data over long periods of time and learn from those changes. This made it difficult to provide appropriate reactions and stimuli in response to changes in an animal's behavioral patterns.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

In this invention, the server includes means for storing data from sensors that detect animal movements and behavioral patterns in a database, means for cleansing the stored data and extracting behavioral patterns, means for the generative artificial intelligence to learn changes in behavioral patterns, and means for generating appropriate instructions based on the learning results. This makes it possible to provide appropriate reactions and stimuli in response to changes in the animal's behavioral patterns.

The "device" is a spherical device that can move freely and detects the movements and behavior patterns of animals.

A "personal digital assistant" is a portable electronic device, such as a smartphone or tablet, used to operate the device.

A "sensor" is a sensing device installed in a device to detect animal movements and behavior patterns.

"Generative AI" is AI that analyzes data from sensors, understands animals' preferences and play styles, and provides appropriate reactions and stimuli.

The "database" is an information management system for storing animal behavior data collected from sensors.

"Cleansing" is the process of removing noise from raw data stored in a database and filling in missing data.

A "behavioral pattern" is a tendency for an animal to exhibit a series of behaviors at a particular time or in a particular situation.

"Learning" is the process by which generative artificial intelligence understands changes in animal behavior patterns based on accumulated data.

"Instructions" are specific operational commands that generative AI issues to a device based on its learning results.

"Reactions" are specific actions or stimuli that the device performs on the animal in accordance with instructions from the generative artificial intelligence.

This invention is a system that learns animal behavior patterns in real time and provides appropriate reactions and stimuli based on those patterns. Specific embodiments of this system are described below.

Hardware and software used

Hardware: Sensors (cameras, microphones, etc.) that detect animal movements and behavior patterns, a spherical device that can move freely, and a mobile information terminal (smartphone or tablet)

Software: Generative AI (e.g., OpenAI's GPT-4), databases (MySQL (registered trademark) and MongoDB)

System Configuration

1. Device:

It is equipped with sensors to detect animal movements and behavior patterns.

Data from sensors is collected in real time and sent to a server.

2. Mobile Information Devices:

Used as a means to operate the device.

Users can control the device's operation through their mobile information terminal.

3. Server:

Receives data sent from sensors and stores it in a database.

Clean the accumulated data and extract behavioral patterns.

Uses generative artificial intelligence to learn changes in behavioral patterns.

Based on the learning results, appropriate instructions are generated for the device.

Specific examples

For example, consider a situation where a cat initially prefers aggressive play, but over time begins to prefer gentle play.

1. Data Collection:

The device (camera) captures the cat poking at the toy as it moves vigorously.

The server receives the video data and stores it in a database.

2. Data preprocessing:

The server removes unnecessary parts from the video data and extracts only the cat's movements.

The server organizes the extracted data by time and analyzes the cat's behavioral patterns.

3. Learning behavioral patterns:

The server uses generative artificial intelligence to learn when the cat has changed from aggressive to calm play.

The server saves the learning results and proceeds to the next step.

4. Generating appropriate instructions:

The server inputs a prompt to the generative AI: "Since the cat has started to prefer gentle play, please generate instructions to move a toy with gentle movements."

The server sends the generated instructions to the device.

5. Providing Reactions:

The device (toy) makes gentle movements according to instructions received from the server.

The device provides gentle play for your cat and responds to your cat's behavioral patterns.

Example prompt

By inputting the following prompt sentence into the generative artificial intelligence, instructions based on changes in the cat's behavioral patterns can be generated.

Behavioral data for a cat is shown below. At first, the cat preferred aggressive play, but over time, it began to prefer gentle play. Based on this change, generate instructions to provide the cat with appropriate reactions and stimuli.

In this way, the system is able to provide appropriate reactions and stimuli in response to changes in the animal's behavioral patterns. The flow of the identification process in Example 3 will be explained using Figure 15.

Step 1: Data Collection

The device (sensor) monitors the animal's movements in real time and collects behavioral data. For example, a camera captures a cat's movements and a microphone records the cat's meows.

Input: Real-time animal movements and sounds

Output: Animal behavior data (video and audio data)

Specific operation: The camera captures the cat's movements, and the microphone records the cat's meows. The device collects this data and sends it to the server.

Step 2: Data preprocessing

The server cleanses the raw data stored in the database. Specifically, it removes noise and fills in missing data.

Input: Raw data (video data, audio data)

Output: Cleansed data

Specific operation: The server removes unnecessary parts from the video data and filters noise from the audio data. Any missing data is filled in.

Step 3: Extracting behavioral patterns

The server organizes the cleansed data by time and extracts behavioral patterns.

Input: Cleansed data

Output: Behavioral pattern data

Specific operation: The server analyzes the cleansed data and extracts information about the animal's behavior at specific times of the day.

Step 4: Learning behavioral patterns

The server uses a generative AI model to learn animal behavior patterns based on accumulated data.

Input: Behavioral pattern data

Output: Learning results (changes in behavioral patterns)

Specific operation: The server inputs behavioral pattern data into the generative AI model, which then learns changes in the animal's behavior. For example, it learns that a cat has changed from aggressive play to calm play.

Step 5: Generate appropriate instructions

The server generates appropriate instructions for the device based on the learning results.

Input: Learning results

Output: Instruction data

Specific behavior: The server inputs a prompt to the generative AI model: "Since the cat has started to prefer gentle play, please generate instructions to move a toy with gentle movements," and sends the generated instructions to the device.

Step 6: Provide a reaction

The terminal (device) operates according to the instructions received from the server.

Input: Instruction data

Output: Reaction to animals

Specific action: The device activates a toy with gentle movements, providing gentle play for the cat.

(Application Example 3)

Next, we will explain Application Example 3 of Form Example 3. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Conventional animal devices and generative AI were limited to learning animal behavior patterns and providing appropriate reactions. However, there were no systems that could learn the behavior patterns of workers in factories and provide appropriate support. As a result, improvements in work efficiency and reductions in worker burden were not fully achieved. Therefore, there is a need for a system that can learn the behavior patterns of workers in factories and provide appropriate support.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

In this invention, the server includes a spherical device that can move around freely, means for operating the device from a smartphone, a sensor installed in the device that detects the animal's movements and behavioral patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and behavioral patterns, means for providing appropriate reactions and stimuli to the animal based on the AI, and means for accumulating worker behavioral data over time, learning changes in behavioral patterns based on the accumulated data, and providing appropriate support. This makes it possible to learn the behavioral patterns of workers within the factory and provide appropriate support.

A "spherical, freely movable device" is a device that has a spherical shape and the ability to physically move freely.

"Means for operating from a smartphone" refers to the interface or software for remotely operating a device using a smartphone.

A "sensor that detects animal movements and behavior patterns" is a device that detects animal movements and behavior in real time and collects that data.

"Generative AI" is an artificial intelligence technology that learns the behavioral patterns of animals and workers based on collected data and provides appropriate reactions and support.

"Means for providing appropriate reactions and stimuli" refers to devices or functions that provide appropriate reactions and stimuli to animals and workers based on the results of learning by the generative AI.

"Means for accumulating worker behavioral data over time" refers to a system that continuously records worker behavior and stores that data for long periods of time.

"Means of learning changes in behavioral patterns and providing appropriate support" is a function that analyzes accumulated behavioral data, recognizes changes in behavioral patterns, and provides optimal support to workers.

The following hardware and software are required to implement this invention. Hardware requires a spherical, freely movable device, a smartphone, a factory robot, and sensors. Software requires Python, scikit-learn, and a generative AI model.

First, the spherical, freely movable device is equipped with sensors that detect the behavior of animals and workers in real time. These sensors detect the movements and behavioral patterns of animals and workers and collect that data. The collected data is sent to a generative AI model for analysis.

The generative AI model learns the behavioral patterns of animals and workers based on collected data. This learning process uses Python and scikit-learn. Specifically, it uses the KMeans clustering algorithm to classify behavioral patterns and learns how behavioral patterns change over time.

Once learning is complete, the generative AI model will provide instructions for providing appropriate reactions and stimuli to animals and workers. For example, if an animal prefers aggressive play, the device will provide appropriate stimuli. Also, if a worker transitions from manual to automated tasks, the robot will provide appropriate support.

For example, if a worker is manually assembling parts in a factory, a robot will help carry the parts. Also, if a worker is operating automated machinery, a robot will help with machine maintenance.

Examples of prompt statements include:

"Develop AI that collects data on worker behavior in factories and learns changes in behavioral patterns based on that data. For example, when workers transition from manual to automated tasks, create a robot that learns this change and provides appropriate support."

In this way, this invention can improve work efficiency within factories and reduce the burden on workers.

The flow of the specific processing in Application Example 3 will be explained using Figure 16.

Step 1:

The server uses sensors to collect behavioral data of animals and workers. The input is real-time behavioral data obtained from the sensors, and the output is a list of collected behavioral data. Specifically, the sensors detect the movements of animals and workers and send that data to the server.

Step 2:

The server accumulates the collected behavioral data. The input is the behavioral data collected in step 1, and the output is a database of accumulated behavioral data. Specifically, the server saves the data it receives in the database.

Step 3:

The server uses the accumulated behavioral data to train a generative AI model. The input is the accumulated behavioral data, and the output is the trained generative AI model. Specifically, the server uses Python and scikit-learn to run the KMeans clustering algorithm and classify behavioral patterns.

Step 4:

When new behavioral data is input, the server uses a generative AI model to predict behavioral patterns. The input is the new behavioral data, and the output is the predicted behavioral pattern. Specifically, the server inputs the new data into the generative AI model and obtains the predicted results.

Step 5:

The server issues instructions to provide appropriate reactions and support based on the prediction results. The input is the predicted behavior pattern, and the output is instructions for reactions and support. In terms of specific operations, the server instructs the device or robot to perform the appropriate action.

Step 6:

The terminal (smartphone) receives instructions from the server and operates the device or robot. The input is the instruction from the server, and the output is the operation of the device or robot. Specifically, the smartphone sends operation commands to the device or robot.

Step 7:

The user monitors the operation of the device or robot and operates it manually as necessary. The input is the operating status of the device or robot, and the output is the user's operation commands. Specifically, the user manually operates the device or robot using a smartphone.

Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

"Example 1"

One embodiment of the present invention provides a system that incorporates an emotion engine. This system recognizes the user's emotions and adjusts the reactions and stimuli given to the cat according to those emotions. Specifically, when the user is happy, the system encourages the cat to play actively. Conversely, when the user is depressed, the system encourages the cat to play quietly. This enables optimal interaction with the cat according to the user's emotional state.

"Example 2"

The emotion engine also recognizes emotions from the user's tone of voice, facial expressions, or physical reactions. For example, if the user is smiling, the system will recognize that the user is happy and encourage the cat to play actively. Conversely, if the user is crying, the system will recognize that the user is sad and encourage the cat to play quietly. This allows for a more accurate understanding of the user's emotional state and optimal interaction with the cat accordingly.

"Example 3"

Furthermore, the emotion engine adjusts the device's movements and reactions according to the user's emotions, improving the interaction between the user and the cat. For example, when the user is angry, the system suppresses the device's movements to prevent the cat from bothering the user. Conversely, when the user is happy, the system activates the device's movements to allow the cat to play happily with the user. This enables optimal interaction with the cat according to the user's emotional state.

The processing flow for each example form is explained below.

"Example 1"

Step 1: The user's emotion engine recognizes the user's emotion.

Step 2: Based on the recognized emotion, the system adjusts its reactions and stimuli to the cat.

Step 3: When the user is happy, the system encourages active play with the cat.

Step 4: When the user is feeling down, the system encourages quiet play with the cat.

"Example 2"

Step 1: The emotion engine recognizes emotions from the user's tone of voice, facial expressions, or physical reactions.

Step 2: If the user is smiling, the system recognizes that the user is happy and encourages active play with the cat.

Step 3: If the user is crying, the system recognizes that the user is sad and prompts the cat to play quietly.

"Example 3"

Step 1: The emotion engine recognizes the user's emotions.

Step 2: Adjust the device's movements and responses based on the user's emotions.

Step 3: When the user is angry, the system inhibits the device's movement to prevent the cat from bothering the user.

Step 4: When the user is happy, the system activates the device's activity, allowing the cat to play happily with the user.

(Example 1)

Next, we will explain Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Previous animal devices simply detected animal movements and behavioral patterns, but were unable to understand the animal's preferences and play styles and provide appropriate reactions or stimulation. Furthermore, they lacked the ability to adjust interactions with the animal based on the user's emotional state, making it difficult to deepen the relationship between the user and the animal.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, and an emotion engine that recognizes the user's emotions and adjusts the reactions and stimuli to the animal according to those emotions. This makes it possible to understand the animal's behavior patterns and provide optimal reactions and stimuli according to the user's emotional state.

A "device" is a spherical piece of equipment that can move freely.

An "information terminal" is an electronic device that provides a means for operating a device.

A "sensor" is a device used to detect animal movements and behavior patterns.

"Generative AI" is artificial intelligence that analyzes data from sensors and understands animals' preferences and play styles.

"Means for providing reactions and stimuli" refers to a mechanism for providing appropriate reactions and stimuli to animals based on the analysis results of the generative AI.

The "emotion engine" is a system that recognizes the user's emotions and adjusts the reactions and stimuli given to animals based on those emotions.

"Animal behavior data" is information about animal movements and behavior patterns.

"Feedback" is the process of returning the device's response to physical stimuli from the animal to the generative AI.

This invention is a system that understands animal behavior patterns and provides optimal reactions and stimuli according to the user's emotional state. Specific embodiments of this system are described below.

Hardware and software used

Device: A spherical device that can move freely. It is equipped with motors, batteries, and sensors.

Information terminal: An electronic device that provides a means for operating a device. Examples include smartphones and tablets.

Sensor: A device used to detect animal movements and behavior patterns. Accelerometers and infrared sensors are used.

Generative AI: Artificial intelligence that analyzes data from sensors to understand animals' preferences and play styles. It uses AI models that run on the cloud.

Emotion engine: A system that recognizes the user's emotions and adjusts the animal's reactions and stimuli accordingly. Emotion recognition software is used.

Program processing

The server receives the animal's behavioral data sent from the device and inputs it into the generative AI. The generative AI analyzes the received data to understand the animal's preferences and play styles. Based on the analysis results, the generative AI then generates instructions to provide the animal with appropriate reactions and stimuli, and sends these to the device.

The device collects data to recognize the user's emotions. For example, it uses the smartphone's camera and microphone to analyze the user's facial expressions and tone of voice. The emotion engine receives the user's emotional data and adjusts the animal's reactions and stimuli according to those emotions.

Specific examples

Example 1: When a cat approaches the device, the sensor detects its movement and sends the data to the server. The server uses a generative AI model to determine that the cat is interested and sends the device an instruction to "rotate to attract the cat's attention." The device then begins to rotate in place.

Example 2: When a user is using a smartphone, the device captures the user's facial expression with its camera, and the emotion engine recognizes that the user is happy. The server then sends instructions to the generative AI model to encourage active play, causing the device to act as if it were running around with a cat.

Example prompt

"Please explain what happens when a cat approaches the device."

"Please explain how users react to cats when they are happy."

The above is a specific embodiment for implementing this invention. This system makes it possible to understand animal behavior patterns and provide optimal reactions and stimuli according to the user's emotional state.

The flow of the identification process in Example 1 will be explained using Figure 17.

Step 1:

Initializing the device

Server: Initializes the device. Checks the status of the motor and battery, and ensures that sensors are working properly.

Input: The signal that powers on the device.

Output: Signals that initialization is complete.

Specific operation: When the device is turned on, the server checks the status of each component of the device and, if everything is normal, sends a signal indicating initialization is complete.

Step 2:

Cat movement detection

Device: Uses internal sensors to detect your cat's movements and behavior patterns in real time.

Input: Cat movements and behavior.

Output: Detection data.

Specific behavior: When a cat approaches or touches the device, the sensor detects the movement and collects data.

Step 3:

Data transmission

Device: Sends detected data to the server.

Input: Detection data.

Output: Send data to the server.

Specific operation: The data collected by the sensor is sent to the server via wireless communication.

Step 4:

Data analysis

Server: Inputs the received data into a generative AI model to analyze the cat's behavioral patterns and preferences.

Input: Detection data.

Output: Behavioral pattern analysis results.

Specific operation: The server inputs the data "a cat touched the device" into the generated AI model, and the AI determines that "the cat is showing interest."

Step 5:

Generating instructions

Server: Based on the analysis results, generates instructions to provide the cat with appropriate reactions and stimuli.

Input: Behavioral pattern analysis results.

Output: Instructions to the device.

Specific operation: The server generates an instruction to "rotate the device to attract the cat's attention" and sends it to the device.

Step 6:

Device Operation

Device: Operates according to instructions from the server and provides appropriate reactions and stimuli to the cat.

Input: Instructions from the server.

Output: Device operation.

Specific action: The device will start to rotate and act in a way that will attract the cat's interest.

Step 7:

User emotion recognition

Device: Collect data to recognize the user's emotions. For example, use the smartphone's camera and microphone.

Input: User's facial expression and tone of voice.

Output: Emotion data.

Specific operation: The device analyzes the user's facial expressions and tone of voice to recognize their emotional state.

Step 8:

Adjusting instructions based on emotions

Server: Receives the user's emotional data and adjusts the cat's reactions and stimuli.

Input: Emotion data.

Output: Adjusted instructions.

Specific behavior: If the server recognizes that the user is happy, it sends instructions to the generative AI model to encourage active play. The device then behaves as if it is running around with a cat.

(Application Example 1)

Next, we will explain Application Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Previous pet devices simply detected animal behavior patterns and were unable to deeply understand the animal's preferences or play styles. Furthermore, they lacked the ability to adjust interactions with the animal based on the user's emotional state, making it difficult to provide interactions with the pet that best fit the user's emotional state. Furthermore, they lacked a way to control the device or display animal behavior data in real time, making it difficult for users to understand the device's operating status and the animal's behavior.

The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavioral patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, means for recognizing the user's emotional state using an emotion engine and adjusting the reactions and stimuli provided to the animal in accordance with the emotional state, and means for displaying the device's operation and the animal's behavioral data on the information terminal. This makes it possible to deeply understand the animal's behavioral patterns and provide optimal interactions with the pet in accordance with the user's emotional state.

A "spherical device capable of moving freely" is a spherical device that has an internal motor and battery and can move autonomously based on external instructions.

An "information terminal" is an electronic device, such as a smartphone or tablet, that is operated by the user to control the device.

A "sensor that detects animal movements and behavior patterns" is a device that detects an animal's location, speed, movements, etc. in real time and collects that data.

"Generative AI" is an artificial intelligence system that analyzes collected data and understands animals' preferences and play styles.

The "emotion engine" is a system that recognizes the user's emotional state and adjusts interactions with animals based on that information.

"Means for providing appropriate reactions and stimuli to animals" refers to a mechanism that allows appropriate actions and reactions to be taken by animals based on the analysis results of the generative AI.

"Means for displaying the device's operation and animal behavior data on an information terminal" refers to a function for displaying the device's operating status and animal behavior data on an information terminal in real time.

A system for implementing this invention includes a spherical, freely movable device, an information terminal, a sensor that detects animal movements and behavior patterns, a generative AI, an emotion engine, and a means for displaying on the information terminal.

System Configuration

1. Spherical device:

It is equipped with a motor and battery inside and moves autonomously based on external instructions.

Equipped with sensors to detect animal movements and behavior patterns.

2. Information terminal:

Electronic devices operated by users, such as smartphones and tablets.

Displays device operation and animal behavior data in real time.

3. Sensor:

It detects animals' location, speed, movements, etc. in real time and collects that data.

4. Generative AI:

Analyze the collected data to understand the animals' preferences and play styles.

Generative AI models are used to generate instructions to provide appropriate reactions and stimuli to animals.

5. Emotion Engine:

Recognizes the user's emotional state and adjusts interactions with animals based on that information.

6. Display means:

Device operation status and animal behavior data are displayed on the information terminal.

Program processing explanation

The server first collects animal behavior data from sensors. This data is sent to the generative AI, which analyzes the animal's preferences and play styles. Based on the analysis results, the generative AI generates instructions to provide the animal with appropriate reactions and stimuli. Furthermore, an emotion engine recognizes the user's emotional state and adjusts interactions with the animal based on that information. Finally, device operations and animal behavior data are displayed in real time on the information terminal.

Specific examples

For example, if this system were used in a pet shop, when a customer was playing with a cat, the smartphone app would analyze the cat's behavior in real time and adjust how the customer interacted with the cat depending on the customer's emotional state. An example of a prompt sentence to be input into the generative AI model is as follows:

Example prompt:

Cat behavior data: Movement: Active, Play style: Chasing a ball

User's emotional state: State: Happy

Based on this data, generate instructions to provide appropriate reactions and stimuli for your cat.

By inputting this prompt into a generative AI model, we can obtain appropriate reactions and stimulation instructions for the cat.

The flow of the specific processing in Application Example 1 is explained using Figure 18.

Step 1:

The server obtains animal behavior data from sensors. The sensors detect the animal's position, speed, movement, etc. in real time and send the data to the server. The input is raw data from the sensors, and the output is the animal's behavior data sent to the server.

Step 2:

The server sends the acquired animal behavior data to the generative AI. The generative AI analyzes the received data and understands the animal's preferences and play styles. The input is the animal's behavior data, and the output is the analysis results regarding the animal's preferences and play styles.

Step 3:

The server generates instructions to provide appropriate reactions and stimuli to the animal based on the analysis results from the generative AI. It uses the generative AI model to create prompts and generate specific instructions for the animal. The input is the analysis results of the generative AI, and the output is instructions for the animal.

Step 4:

The server uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes data such as the user's facial expressions and voice to identify the user's emotional state. The input is the user's emotional data, and the output is the user's emotional state.

Step 5:

The server adjusts the reactions and stimuli given to the animal based on the user's emotional state. Based on the output of the emotion engine, it modifies the instructions of the generative AI to provide optimal interaction. The input is the user's emotional state and the instructions of the generative AI, and the output is the adjusted instructions given to the animal.

Step 6:

The server sends the adjusted instructions to the spherical device. The device acts based on the received instructions and provides the animal with an appropriate reaction or stimulus. The input is the adjusted instructions, and the output is the device's behavior.

Step 7:

The terminal displays device operation and animal behavior data in real time. Users can check the device's operating status and the animal's behavior through the information terminal. The input is device operation data and animal behavior data, and the output is the information displayed on the information terminal.

(Example 2)

Next, we will explain Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Previous animal devices struggled to provide appropriate responses to animal behavior and were unable to realize interactions that took the user's emotional state into account. This made it difficult to provide an optimal experience for both the animal and the user. Furthermore, there was a lack of systems that could learn changes in the animal's behavioral patterns and adapt over the long term.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

In this invention, the server includes means for operating a spherical, freely mobile device, means for using sensors to detect the animal's movements and behavioral patterns, means for using generative AI to analyze data from the sensors and understand the animal's preferences and play styles, means for using an emotion engine to recognize the user's emotional state, and means for optimizing interactions with the animal based on the generative AI and emotion engine. This makes it possible to provide appropriate responses to the animal's behavior and enable interactions that take the user's emotional state into consideration. It also makes it possible to learn changes in the animal's behavioral patterns and adapt over the long term.

A "device" is a spherical piece of equipment that can move freely.

An "information terminal" is an electronic device that provides a means for operating a device.

A "sensor" is a device that detects animal movements and behavior patterns.

"Generative AI" is artificial intelligence that analyzes data from sensors and understands animals' preferences and how they play.

An "emotion engine" is software or hardware that recognizes the user's emotional state.

"Reactions" are appropriate responses or stimuli provided to animals based on generative AI.

"Interaction optimization" refers to optimizing the interaction between animals and users based on generative AI and an emotion engine.

"Behavioral data" is information about animal movements and behavior patterns.

"Feedback" means that the device automatically responds to physical stimuli from the animal and transmits that response to the generative AI.

This invention is a system that provides optimal interaction based on the animal's behavior and the user's emotional state. Specific embodiments of this system are described below.

Hardware and software used

Device: A spherical, freely movable device that provides physical responses to the animal's behavior.

Information terminal: An electronic device that provides a means for operating a device. Examples include smartphones and tablets.

Sensor: A device that detects animal movements and behavior patterns. It is installed in the device and collects data in real time.

Generative AI: Artificial intelligence that analyzes data from sensors to understand animals' preferences and play styles. An example of this is OpenAI's GPT-4.

Emotion engine: Software or hardware that recognizes the user's emotional state. It analyzes the user's tone of voice, facial expressions, or physical reactions.

System Operation

The server receives the animal's behavior data sent from the sensor and analyzes it using generative AI. The generative AI understands the animal's behavioral patterns and sends instructions to the device to provide appropriate reactions and stimuli.

Furthermore, the server uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes the user's tone of voice and facial expressions to determine whether the user is happy or sad. The server optimizes interactions with the animal based on this emotional state.

Specific examples

For example, if a cat scratches the device, the sensor detects the action. The sensor sends the data to a server, which analyzes the data using generative AI. The generative AI understands that the cat prefers aggressive play and instructs the device to move a cat toy. The device follows this instruction to move the cat toy and provide the cat with the appropriate stimulation.

At the same time, the server uses its emotion engine to recognize the user's smile and determine that the user is happy. The server then encourages the cat to play actively depending on the user's emotional state.

Example prompt

"What should I do if my cat is acting aggressively towards my device?"

"Please tell me what kind of play I should encourage the cat to do when the user is smiling."

This system enables optimal interaction based on the emotional state of the animal and the user.

The flow of the identification process in Example 2 will be explained using Figure 19.

Step 1:

Data collection using sensors

The server monitors the animal's behavior in real time using sensors installed on the device. The sensors detect any aggressive behavior from the animal toward the device. For example, if a cat digs its claws into the device, the sensor detects this behavior. The input is the animal's behavior data, and the output is the detected behavior data.

Step 2:

Data transmission

The sensor sends the detected behavioral data to the server. The server receives this data and passes it on to the generative AI. The input is the behavioral data sent from the sensor, and the output is the behavioral data sent to the server.

Step 3:

Analysis using generative AI

The server uses generative AI to analyze the behavioral data it receives. The generative AI uses, for example, OpenAI's GPT-4, to understand that animals prefer aggressive play. Specifically, it analyzes the behavioral data and determines that the behavior constitutes aggressive play. The input is the behavioral data sent to the server, and the output is the analysis results.

Step 4:

Device instructions

The server issues instructions to the device based on the analysis results of the generative AI. For example, it instructs the device to move a cat toy. The device follows this instruction to move the cat toy and provide the cat with appropriate stimulation. The input is the analysis results of the generative AI, and the output is the instruction to the device.

Step 5:

Recognize user emotions using an emotion engine

The server uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's tone of voice, facial expressions, or physical reactions. For example, if the user is smiling, the emotion engine recognizes that the user is happy. The input is the user's emotion data, and the output is the emotion recognition result.

Step 6:

Cat interaction optimization

The server optimizes interactions with animals according to the user's emotional state. For example, if the user is smiling, it encourages the animal to play actively. Conversely, if the user is crying, it encourages the animal to play quietly. This allows for optimal interaction with animals according to the user's emotional state. The input is the emotion recognition result, and the output is instructions for optimized interactions.

(Application Example 2)

Next, we will explain Application Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Previous pet devices struggled to provide interactions that fully took into account the animal's behavior and the user's emotional state. Furthermore, they lacked a means to provide appropriate stimuli based on the animal's behavioral patterns and the user's emotions, making it difficult to increase satisfaction for both the pet and the user.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing the animal with appropriate reactions and stimuli based on the AI, an emotion engine that recognizes the user's emotional state, and means for adjusting interactions with the animal based on the emotion engine. This enables appropriate interactions that take into account the animal's behavior and the user's emotional state in real time.

A "spherical, freely movable device" is a device that has a spherical shape and can physically move freely.

An "information terminal" is an electronic device operated by a user, such as a smartphone or tablet.

A "sensor that detects animal movements and behavior patterns" is a device that detects animal movements and behavior in real time.

"Generative AI" is an artificial intelligence system that analyzes collected data and understands animals' preferences and behavioral patterns.

"Means for providing appropriate reactions and stimuli" refers to devices and methods for providing appropriate reactions and stimuli to animals based on the analysis results of the generative AI.

The "emotion engine" is a system that recognizes emotions from the user's tone of voice, facial expressions, and physical reactions.

"Means for adjusting interactions with animals" refers to devices and methods for optimizing interactions with animals based on the recognition results of the emotion engine.

This invention is a system that takes into account the animal's behavior and the user's emotional state in real time to provide appropriate interaction. Below, we will show a specific embodiment for realizing this system.

System Configuration

The system consists of the following main components:

1. A spherical, freely movable device:

This device is a spherical device that can be moved freely to induce animal behavior. It is equipped with a motor and battery inside and operates according to instructions from an information terminal.

2. Information terminal:

Electronic devices such as smartphones and tablets that provide an interface for users to operate the device. Dedicated applications are installed on them to control the device's operation.

3. Sensors that detect animal movements and behavior patterns:

The device is equipped with a camera and accelerometer to detect animal movements and behavior in real time.

4. Generation AI:

It is an artificial intelligence system that analyzes collected data to understand animals' preferences and behavioral patterns. Generative AI accumulates animal behavioral data over time and learns changes in behavioral patterns based on that data.

5. How to provide appropriate reactions and stimuli:

This is a device or method for providing appropriate responses or stimuli to animals based on the analysis results of generative AI. For example, the device may stimulate the animal by making specific movements.

6. Emotion Engine:

This is a system that recognizes emotions from the user's tone of voice, facial expressions, and physical reactions. The emotion engine detects the user's emotional state in real time through the camera and microphone.

7. Ways to regulate interactions with animals:

An apparatus and method for optimizing interactions with animals based on the recognition results of an emotion engine. For example, if the user is recognized as sad, the device will behave calmly.

Program processing explanation

The server detects the user's emotional state through a camera and microphone and sends it to the generative AI. The generative AI analyzes the animal's behavioral data and the user's emotional data to determine an appropriate reaction. The information terminal receives instructions from the generative AI and instructs the device on how to act.

The hardware used includes a camera (to detect animal behavior and the user's facial expressions), a microphone (to detect the user's tone of voice), and a motor (to control the device's movement). The software includes OpenCV (image processing), Keras (emotion recognition model), and requests (communication with AI services).

Specific examples

For example, if a user comes into the store with a smiling face and a pet, the emotion engine will recognize that the user is happy. The generative AI will analyze the animal's behavioral data and the user's emotional data and instruct the device to behave in a way that encourages active play. Conversely, if the user looks sad, the device will be instructed to behave calmly.

Example prompt

"If the user's emotion is 'happy' and the animal's behavior is 'aggressive,' we will provide a toy that encourages active play with the animal."

The flow of the specific processing in Application Example 2 is explained using Figure 20.

Step 1:

The server captures the user's facial expressions and tone of voice in real time through a camera and microphone. It receives camera footage and audio data as input. It preprocesses this data using OpenCV and audio processing libraries to extract the user's facial features and tone of voice. It generates data indicating the user's emotional state as output.

Step 2:

The server uses an emotion engine to analyze the user's emotional state data obtained in step 1. It uses facial feature points and voice tone data as input. The emotion engine inputs this data into an emotion recognition model (using Keras) and classifies the user's emotions into categories such as "happy" or "sad." As an output, it generates a label indicating the user's emotional state.

Step 3:

The terminal acquires animal behavior data in real time through sensors installed on the device. As input, it receives data from the sensors (acceleration, location information, etc.). It preprocesses this data to extract the animal's movements and behavioral patterns. As output, it generates data indicating the animal's behavioral state.

Step 4:

The server uses generative AI to integrate and analyze the user's emotional state data obtained in step 2 and the animal's behavior data obtained in step 3. The user's emotional state data and the animal's behavior data are used as input. The generative AI determines appropriate reactions and stimuli for the animal based on this data. As output, it generates operational instructions for the device.

Step 5:

The terminal sends the operation instructions generated in step 4 to the device. As input, it receives operation instruction data from the generative AI. The terminal transmits these instructions to the device's motor control system, controlling the device to perform the appropriate operation. As output, the device's physical operation is executed.

Step 6:

The device automatically responds to physical stimuli from the animal and feeds that response back to the generative AI as animal behavior data. As input, it receives physical stimulus data from the animal. The device detects this data with sensors and sends it to the generative AI. As output, the animal's behavior data is updated.

Step 7:

The server re-analyzes the animal's behavior data updated in step 6 and learns changes in the animal's behavior patterns. It uses the updated animal's behavior data as input. The generative AI accumulates this data and learns changes in the animal's behavior patterns. As output, it generates new movement instructions based on the animal's behavior patterns.

(Example 3)

Next, we will explain Example 3 of Form Example 3. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Previous animal devices struggled to provide appropriate reactions and stimuli based on the animal's behavioral patterns and the user's emotional state. Furthermore, they lacked the ability to accumulate animal behavioral data over time and learn from changes in that data, making it impossible to respond appropriately to the animal's interests and preferences. Furthermore, the device's movements and responses were not adjusted to take the user's emotional state into account, resulting in suboptimal interactions between the user and the animal.

The specific processing by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means. In this invention, the server includes a spherical device that can move freely around, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, an emotion engine for analyzing the user's emotional state, and means for adjusting the device's movements and reactions based on the analysis results of the emotion engine. This makes it possible to provide appropriate reactions and stimuli in response to changes in the animal's behavior patterns, enabling optimal interaction according to the user's emotional state.

A "device" is a spherical piece of equipment that can move freely.

An "information terminal" is an electronic device that provides a means for operating a device.

A "sensor" is a device used to detect animal movements and behavior patterns.

"Generative AI" is artificial intelligence that analyzes data from sensors and understands animals' preferences and how they play.

An "emotion engine" is software or hardware for analyzing a user's emotional state.

A "reaction" is an appropriate response or stimulus provided to an animal.

"Animal behavior data" is information about animal movements and behavior patterns.

"User's emotional state" refers to the emotional state the user is feeling.

This invention is a system that analyzes animal behavior data and the user's emotional state to provide optimal interaction. A specific embodiment of this system is described below.

System Configuration

The system consists of the following main components:

1. Device: A spherical, freely movable device. The device is equipped with sensors to detect animal movements and behavior patterns.

2. Information terminal: An electronic device that provides a means for operating a device. Examples include smartphones and tablets.

3. Server: The central component that receives and analyzes data from devices and information terminals.

4. Generative AI: Artificial intelligence that analyzes data from sensors and understands animals' preferences and play styles.

5. Emotion engine: Software or hardware for analyzing the user's emotional state.

Data collection and analysis

The server collects animal behavior data from sensors installed on the device. For example, a camera tracks a cat's movements and a sensor detects which objects the cat touches. The collected data is stored in a database.

Generative AI analyzes accumulated behavioral data and learns the behavioral patterns of animals. For example, it learns that cats become active at 8am every morning and that they prefer certain toys. Based on this learning, it issues appropriate instructions to the device.

User sentiment analysis and device adjustment

The device uses a camera and microphone to analyze the user's emotional state. For example, it analyzes the user's facial expressions and tone of voice to determine whether the user is angry or happy.

The server adjusts the device's movements and reactions based on the analysis results of the emotion engine. For example, when the user is angry, the device's movements will be suppressed so that the animal can remain quiet. Conversely, when the user is happy, the device's movements will be more active so that the user can play with the animal.

Specific examples

For example, if a cat initially likes chasing laser pointers, but after a few weeks starts to prefer rolling a ball, the generative AI will learn this change and instruct it to move the ball-rolling device more frequently.

Also, when the user comes home from work and is tired, the emotion engine detects the user's fatigue and reduces the device's activity so that the cat can stay quiet. Conversely, when the user is relaxing on a day off, the device's activity will be more active so that the user can play with the cat.

Example prompt

"Please explain the generative AI program that accumulates cat behavior data and learns changes in behavior patterns."

"Please explain how the emotion engine works, adjusting the device's behavior and responses based on the user's emotions."

In this way, the system utilizes animal behavior data and user emotion data to provide optimal interaction. The flow of the identification process in Example 3 will be explained using Figure 21.

Step 1:

The server collects animal behavior data from sensors installed on the device. As input, it receives real-time data from the sensors and, as output, generates data on the animal's movements and behavior patterns. Specifically, the camera tracks the cat's movements and the sensor detects which objects the cat touches.

Step 2:

The server stores the collected behavioral data in a database. As input, it receives the animal behavioral data generated in step 1, and as output, it stores the time-stamped behavioral data in the database. Specifically, it records the data "October 1, 2023, 08:00:00 - Cat chases laser pointer."

Step 3:

Generative AI analyzes accumulated behavioral data and learns animal behavior patterns. It receives behavioral data stored in a database as input and generates learning results about the animal's behavior patterns as output. Specifically, it learns the pattern of "chasing a laser pointer every morning at 8 o'clock."

Step 4:

The server issues instructions to the device based on the learning results of the generative AI. It receives the learning results of the generative AI as input and generates specific instructions for the device as output. Specifically, it issues the instruction "move the laser pointer at 8 o'clock every morning."

Step 5:

The device uses a camera and microphone to analyze the user's emotional state. As input, it receives data related to the user's facial expressions and tone of voice, and as output, it generates an analysis result related to the user's emotional state. Specifically, if the user is smiling while speaking, it is determined that they are happy.

Step 6:

The server adjusts the device's movements and reactions based on the analysis results of the emotion engine. It receives the user's emotion analysis results as input and generates specific instructions regarding the device's movements and reactions as output. Specifically, when the user is angry, the device's movements are suppressed so that the animal can remain quiet. Conversely, when the user is happy, the device's movements are made more active so that the user can play with the animal.

(Application Example 3)

Next, we will explain Application Example 3 of Form Example 3. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart device 14 will be referred to as the "terminal."

Previous pet interaction systems struggled to provide appropriate reactions and stimuli based on changes in animal behavior patterns and the user's emotional state. Furthermore, they lacked the ability to provide real-time advice on how users should interact with animals, making it difficult to achieve optimal interactions with animals.

The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, an emotion engine that senses the user's emotional state and adjusts the device's movements and reactions, and means for advising the user on optimal interactions with the animal. This makes it possible to provide appropriate reactions and stimuli in response to changes in the animal's behavior patterns, and to achieve optimal interactions according to the user's emotional state.

A "spherical, freely movable device" is a device that has a spherical shape and the ability to physically move freely.

An "information terminal" is an electronic device operated by a user, such as a smartphone or tablet.

A "sensor that detects animal movements and behavior patterns" is a device that detects animal movements and behavior in real time and collects that data.

"Generative AI" is artificial intelligence that learns animal behavior patterns based on collected data and generates appropriate reactions and stimuli.

"Means for providing appropriate reactions and stimuli" is a function that provides appropriate reactions and stimuli to animals based on the results of learning by the generative AI.

An "emotion engine" is a system that senses the user's emotional state and adjusts the device's behavior and responses accordingly.

"Means for advising optimal interactions" is a function that provides real-time instructions to users on how best to interact with and play with animals.

A system for implementing this invention has the following configuration:

First, a spherical, freely movable device is required. This device is equipped with sensors that detect the animal's movements and behavior patterns. The sensors detect the animal's movements and behavior in real time and collect that data.

Next, you need an information terminal. An information terminal is an electronic device that users can operate, such as a smartphone or tablet. You can operate the device through this information terminal.

The collected data is analyzed by generative AI, which accumulates data on the animal's behavior over time and learns changes in the animal's behavior patterns based on that accumulated data. This makes it possible to understand the animal's preferences and play styles, and provide appropriate reactions and stimulation.

Furthermore, the emotion engine senses the user's emotional state. The emotion engine adjusts the device's movements and responses according to the user's emotional state. For example, it increases the device's movements when the user is happy, and reduces the device's movements when the user is angry.

Finally, it includes a way to advise users on optimal interactions with animals, allowing them to know in real time how to interact with animals.

For example, if the user types "happy," the system will advise, "Play with your cat more!". Also, if the user types "angry," the system will advise, "Let's give your cat a break."

Examples of prompts are as follows:

Enter the user's emotion (happy, angry, neutral): happy

In this way, it is possible to provide appropriate reactions and stimuli in response to changes in the animal's behavioral patterns, achieving optimal interaction according to the user's emotional state.

The flow of the specific processing in Application Example 3 will be explained using Figure 22.

Step 1:

The user operates the information terminal and starts the device. As input, the user starts the information terminal's application and turns on the device. As output, the device starts operating and the sensor begins to detect animal movement.

Step 2:

Sensors detect animal movements and behavior patterns in real time and collect the data. The animal's movements and behavior are detected by the sensors as input. The collected data is sent to the generative AI as output.

Step 3:

Generative AI analyzes the collected data and learns the animal's behavioral patterns. The input is the animal's behavioral data transmitted from the sensors. The output is the generation of appropriate reactions and stimulus instructions based on changes in the animal's behavioral patterns.

Step 4:

The emotion engine senses the user's emotional state. As input, the user enters their emotional state into the information terminal. As output, the emotion engine analyzes the user's emotional state and sends the results to the generative AI.

Step 5:

The generative AI adjusts the device's movements and responses based on the user's emotional state. The input is data on the user's emotional state sent from the emotion engine. The output is the device's movements and responses adjusted according to the user's emotional state.

Step 6:

Advises the user on optimal interactions with animals. Inputs include instructions from the generative AI and data on the user's emotional state. Outputs include advice on optimal interactions with animals displayed on the information terminal screen.

Step 7:

The user interacts with the animal according to the advice. The input is the advice displayed on the information terminal. The output is that the user's appropriate interaction with the animal changes the animal's behavioral patterns, and the sensor again collects that data.

This series of processing steps makes it possible to provide appropriate reactions and stimuli in response to changes in the animal's behavioral patterns, achieving optimal interaction according to the user's emotional state.

The specific processing unit 290 transmits the results of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the results of the specific processing. The microphone 38B acquires audio indicating the user input regarding the results of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

Data generation model 58 is what is known as generative AI (artificial intelligence). An example of data generation model 58 is generative AI such as ChatGPT (registered trademark) (Internet search <URL: https://openai.com/blog/chatgpt>). Data generation model 58 is obtained by performing deep learning on a neural network. A prompt containing an instruction is input to data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. Data generation model 58 performs inference on the input inference data in accordance with the instructions indicated by the prompt, and outputs the inference results in the form of data such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and/or summarization.

Another example of generative AI is Gemini (registered trademark) (Internet search <URL: https://gemini.google.com/?hl=ja>).

In the above embodiment, an example was given in which the specific processing was performed by the data processing device 12, but the technology disclosed herein is not limited to this, and the specific processing may also be performed by the smart device 14.

[Second embodiment]

Figure 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

As shown in FIG. 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

The data processing device 12 includes a computer 22, a database 24, and a communication I/F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and communication I/F 26 are also connected to the bus 34. The communication I/F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and/or a LAN (Local Area Network).

The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I/F 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user 20's surroundings (e.g., an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

The communication I/F 44 is connected to the network 54. The communication I/Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I/Fs 44 and 26 is carried out in a secure manner.

Figure 4 shows an example of the main functions of the data processing device 12 and smart glasses 214. As shown in Figure 4, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32.

The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as the specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

Storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

Next, we will explain the identification process performed by the identification processing unit 290 of the data processing device 12.

"Example 1"

One aspect of the present invention provides a spherical device. This device has an internal driving source such as a motor or battery, and is able to move around freely. A sensor is placed on the outside of the device to detect the cat's movements and behavioral patterns. This sensor detects the cat's movements and behavioral patterns and sends the data to a generative AI. The generative AI analyzes the received data and understands the cat's preferences and play styles. Based on this understanding, it then sends instructions to the device to provide the cat with appropriate reactions and stimuli. The device operates in accordance with the instructions and provides the cat with appropriate reactions and stimuli.

"Example 2"

As a specific example, if a cat exhibits aggressive behavior toward the device, a sensor will detect that behavior and send that information to the generative AI. The generative AI will analyze the information and understand that the cat prefers aggressive play. Based on that understanding, it will instruct the device to perform actions that will stimulate the cat. The device will then act in accordance with those instructions and provide the cat with appropriate stimulation.

"Example 3"

In addition, the generative AI accumulates data on the cat's behavior over time and learns changes in the cat's behavior patterns based on that accumulated data. For example, if a cat initially prefers aggressive play but develops a preference for gentler play over time, the generative AI will learn this change and issue appropriate instructions to the device based on that learning. This makes it possible to provide appropriate reactions and stimuli in response to changes in the cat's behavior patterns.

The processing flow for each example is explained below.

"Example 1"

Step 1: The spherical device starts operating, and the sensors that detect the cat's movements and behavior patterns begin to function.

Step 2: The sensor detects the cat's movements and behavior patterns and sends that data to the generative AI.

Step 3: The generative AI analyzes the received data and understands the cat's preferences and play styles.

Step 4: Based on its understanding, the generative AI sends instructions to the device to provide the cat with appropriate reactions and stimuli.

Step 5: The device acts according to the instructions and provides the cat with the appropriate reaction or stimulus.

"Example 2"

Step 1: The cat exhibits aggressive behavior toward the device.

Step 2: The sensor detects the behavior and sends that information to the generative AI.

Step 3: The generative AI analyzes the information and understands that cats prefer aggressive play.

Step 4: Based on that understanding, the generative AI instructs the device to perform actions that stimulate the cat.

Step 5: The device follows the instructions and provides the appropriate stimulation to the cat.

"Example 3"

Step 1: The generative AI accumulates cat behavior data over time.

Step 2: The generative AI learns changes in the cat's behavioral patterns based on the accumulated data.

Step 3: The generative AI issues appropriate instructions to the device based on its learning.

Step 4: The device operates according to the instructions, providing appropriate reactions and stimuli in response to changes in the cat's behavioral patterns.

(Example 1)

Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Conventional animal play equipment struggled to provide the appropriate reactions and stimulation needed to keep animals interested, resulting in animals quickly becoming bored. Furthermore, the lack of a system capable of analyzing animals' behavioral patterns in real time and controlling their movements accordingly made it difficult to provide play styles tailored to each animal's individual preferences.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavioral patterns, generative artificial intelligence that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the artificial intelligence, means for generating instructions for controlling the operation of the device and sending the instructions to the device, and means for the device to operate in accordance with the instructions and provide appropriate reactions and stimuli to the animal. This makes it possible to analyze the behavioral patterns of animals in real time and provide appropriate reactions and stimuli according to the preferences of each individual animal.

The "device" is a spherical, freely movable device equipped with sensors that detect the movements and behavior patterns of animals.

An "information terminal" is an electronic device that provides a means for operating a device, including smartphones and tablets.

A "sensor" is a device that detects animal movements and behavior patterns and is installed in the device.

"Generative AI" is an artificial intelligence system that analyzes data from sensors and understands animals' preferences and play styles.

"Means for providing reactions and stimuli" refers to mechanisms and methods for providing appropriate reactions and stimuli to animals based on generative artificial intelligence.

"Means for generating instructions" refers to the mechanism or method for generating instructions to control the operation of a device based on data analyzed by generative artificial intelligence.

"Means for sending instructions" refers to communication means for sending the generated instructions to the device.

"Means for controlling behavior" refers to the mechanism or method by which the device operates according to the instructions it receives and provides the animal with an appropriate reaction or stimulus.

This invention is a system that analyzes animal behavior patterns in real time and provides appropriate reactions and stimuli based on the preferences of each individual animal. Specific embodiments of this system are described below.

System Configuration

The system consists of the following main components:

1. Device: A spherical, freely movable device equipped with sensors that detect animal movements and behavior patterns.

2. Information terminal: An electronic device that provides a means for operating a device, including smartphones and tablets.

3. Sensor: A device that detects animal movements and behavior patterns and is installed in the device.

4. Generative AI: An artificial intelligence system that analyzes data from sensors to understand animals' preferences and play styles.

5. Means for providing reactions and stimuli: Mechanisms and methods for providing appropriate reactions and stimuli to animals based on generative artificial intelligence.

6. Means for generating instructions: A mechanism or method for generating instructions to control the operation of a device based on data analyzed by generative artificial intelligence.

7. Means for sending instructions: A communication means for sending the generated instructions to the device.

8. Means for controlling behavior: The mechanism or method by which the device operates according to the instructions it receives and provides the animal with the appropriate reaction or stimulus.

System Operation

1. Initialize the device

The user turns on the device.

The device checks the internal motor and battery to ensure they are working properly.

The device will calibrate the sensors to ensure accurate data collection.

2. Data Collection

The device uses sensors to detect animal movements and behavior patterns in real time.

The device temporarily stores detected data.

3. Data Transmission

The device sends the collected data to the server.

The server receives the data and prepares it for analysis.

4. Data Analysis

The server passes the received data to the generative artificial intelligence.

Generative AI analyzes data to understand animals' preferences and behavioral patterns.

5. Instruction Generation

Based on the analysis results, generative AI generates instructions to provide the animal with appropriate reactions and stimuli.

The server receives the generated instructions.

6. Sending instructions

The server sends the generated instructions to the device.

The terminal receives the instructions and transmits them to the device.

7. Device Operation

The device operates according to the instructions received by the terminal.

The device provides the animal with appropriate reactions and stimuli.

Specific examples

For example, if a cat approaches a device, the device's sensor will detect the movement. The server will determine that the cat is interested in the device and send the data to the generative AI. The generative AI will then generate an instruction to "move the device slightly to attract the cat." The server will then send the instruction to the device, which will then move the device.

Example prompt

"Generate an appropriate reaction when a cat approaches the device."

"If my cat likes to chase the device, what movements should I give it?"

In this way, the system can analyze the animal's behavior in real time and provide appropriate reactions, keeping the animal engaged.

The flow of the identification process in Example 1 will be explained using Figure 11.

Step 1: Initialize your device

Input: The user turns on the device.

Processing: The device checks the internal motors and batteries to ensure they are working properly. It also calibrates the sensors to ensure accurate data collection.

Output: The device is ready to operate normally.

Specific operation: The user presses the device's power button, and the device checks the device's LED indicator to confirm normal operation.

Step 2: Collect data

Input: The device detects animal movements and behavior patterns.

Processing: The device uses its sensors to detect animal movements and behavior patterns in real time and temporarily store the data.

Output: Data on animal movements and behavior patterns is collected.

Specific operation: The device uses a sensor to detect the cat's movement as it approaches the device and stores the data in memory.

Step 3: Send data

Input: Collected animal movement and behavior pattern data.

Processing: The device sends the collected data to the server. The server receives the data and prepares it for analysis.

Output: Data is sent to the server and ready for analysis.

Specific operation: The device sends data to the server via Wi-Fi, and the server receives the data and stores it in a database.

Step 4: Data Analysis

Input: Animal movement and behavior pattern data received by the server.

Processing: The server passes the received data to the generative AI, which analyzes the data to understand the animal's preferences and behavioral patterns.

Output: Analysis results on animal preferences and behavior patterns.

Specific operation: The server inputs data into the generative AI, which then concludes that "cats like to chase balls."

Step 5: Generate instructions

Input: Analysis results from generative artificial intelligence.

Processing: Based on the analysis results, the generative AI generates instructions to provide the animal with appropriate reactions and stimuli. The server receives the generated instructions.

Output: Instructions for providing the appropriate reaction or stimulus to the animal.

Specific operation: The generative artificial intelligence generates the instruction "rotate the device to the right," and the server receives that instruction.

Step 6: Send instructions

Input: Generated instructions.

Processing: The server sends the generated instructions to the terminal, which receives the instructions and transmits them to the device.

Output: Instructions sent to the device.

Specific operation: The server sends instructions to the terminal via Wi-Fi, and the terminal receives the instructions and passes them on to the device.

Step 7: Device Operation

Input: Instructions received by the terminal.

Processing: The terminal operates the device according to the instructions received, providing the animal with the appropriate reaction or stimulus.

Output: The appropriate reaction or stimulus provided to the animal.

Specific behavior: The terminal controls the device's motor and rotates it to the right. The device rotates in front of the cat, and the cat chases it.

(Application Example 1)

Next, we will explain Application Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Existing pet devices struggled to fully understand animals' movements and behavior patterns and provide appropriate reactions and stimuli. Furthermore, physical stores lacked the means to provide a fun environment for animals. This meant that efforts to reduce animal stress and improve customer satisfaction were not fully achieved.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

In this invention, the server includes a spherical device that can move around freely, means for operating the device from a smartphone, a sensor installed in the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and ways of playing, means for providing the animal with appropriate reactions and stimuli based on the AI, and means for the device to detect the animal's movements within the physical store and provide appropriate reactions and play using the generative AI. This allows the animal to have fun within the physical store, improving customer satisfaction.

A "spherical device that can move freely" is a spherical device that has an internal power source such as a motor or battery and can move in any direction.

"Means for operating from a smartphone" refers to interfaces and applications for remotely controlling the operation of a device using a smartphone.

A "sensor that detects animal movements and behavior patterns" is a device that senses the position, speed, direction, and other movements of animals and collects that data.

"Generative AI" is an artificial intelligence model that analyzes collected animal movement and behavior data to understand animals' preferences and play styles.

"Means for providing appropriate reactions and stimuli to animals" refers to a mechanism that allows animals to take appropriate actions or react based on instructions generated by the generative AI.

"Means for detecting animal movements within a physical store and using generative AI to provide appropriate reactions and play" refers to a system that detects animal movements within a physical store in real time, sends that data to generative AI, and provides appropriate reactions and play for the animals.

This invention is a system for providing an environment in a physical store where animals, particularly cats, can have fun. The system includes a spherical, freely moving device, a means for operating it from a smartphone, sensors that detect the animal's movements and behavior patterns, generative AI, and a means for providing the animal with appropriate reactions and stimuli.

System Configuration

1. Spherical device:

It is equipped with a motor and battery inside, allowing it to move in any direction.

Sensors are placed on the exterior to detect animal movement.

2. How to operate from your smartphone:

An application is provided for remotely controlling the device's operation using a smartphone.

3. Sensors that detect animal movements and behavior patterns:

It detects the animal's location, speed, direction, and other movements and collects that data.

4. Generative AI:

Analyze collected animal movement and behavior data to understand animals' preferences and play styles.

Generative AI models are used to generate appropriate reactions and stimuli for animals.

5. How to provide appropriate reactions and stimuli to animals:

The robot will then perform appropriate actions and reactions towards the animal based on the instructions generated by the generative AI.

Program processing explanation

The server sends the animal's movement data collected from the sensors to the generative AI. The generative AI analyzes this data to understand the animal's preferences and play styles. Based on what it understands, it generates instructions to provide the animal with appropriate reactions and stimuli. These instructions are sent to the device, which then performs the appropriate action on the animal.

The hardware used includes sensors to detect animal movement, motors to power the device, and batteries to power the device. The software used includes a generative AI model, a sensor control module, and a motor control module.

Specific examples

For example, when a cat approaches a device in a pet shop, a sensor detects its movement and sends the data to the generative AI. The generative AI then generates movements that will interest the cat and sends those instructions to the device. The device then starts moving as if the cat is chasing it, attracting the cat's interest.

Also, when a cat touches the device in a cafe, a sensor detects the movement and sends the data to the generative AI. The generative AI generates a rotating motion that the cat will enjoy and sends that instruction to the device. The device then rotates in a way that the cat will enjoy, attracting its interest.

Example prompt

"Enter your cat's movement data. This data includes the cat's position, speed, direction, etc. Use this data to generate reactions that will interest your cat."

The above is an embodiment of the invention. This system allows animals to have fun in physical stores, improving customer satisfaction.

The flow of the identification process in Application Example 1 will be explained using Figure 12.

Step 1:

The sensor detects the animal's movement. The sensor collects data such as the animal's position, speed, and direction, and sends that data to the server. The input is the animal's movement data, and the output is the movement data sent to the server.

Step 2:

The server sends the animal's movement data received from the sensors to the generative AI. The generative AI analyzes this data and understands the animal's preferences and play styles. The input is movement data from the sensors, and the output is the analysis results by the generative AI.

Step 3:

The generative AI generates appropriate reactions and stimuli for the animal based on the analysis results. The generative AI generates actions and responses that will interest the animal and sends these instructions to the server. The input is the analysis results of the animal's movement data, and the output is the generated reactions and stimulus instructions.

Step 4:

The server sends the instructions received from the generative AI to the device. The device begins to operate based on the received instructions. The input is the instructions from the generative AI, and the output is the device's operation.

Step 5:

The device provides appropriate reactions and stimuli to the animal. The device responds to the animal's movements and performs actions that the animal enjoys. The input is instructions from the server, and the output is reactions and stimuli to the animal.

Step 6:

The device detects physical stimuli from the animal and feeds that data back to the server. The server then sends this data to the generative AI, where it is stored as animal behavior data. The input is physical stimulus data from the animal, and the output is feedback data for the generative AI.

These are the specific processing steps of this system. The specific actions performed at each step allow animals to have fun in physical stores.

(Example 2)

Next, Example 2 of Form Example 2 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Previous cat devices simply detected a cat's behavior and were unable to provide appropriate stimuli based on the cat's individual behavioral patterns and preferences. They also lacked the functionality to accumulate cat behavior data and learn over time, making it difficult to respond to changes in a cat's behavioral patterns. Furthermore, they lacked the functionality to automatically respond to physical stimuli from the cat and provide feedback on that response. This made it difficult to maintain a cat's interest, and made effective play and training impossible.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

In this invention, the server includes sensor means for detecting the cat's behavior, terminal means for transmitting data from the sensor means to the server, means for analyzing the data using a generative AI model in the server means, device means for providing stimuli to the cat based on instructions from the server means, and terminal means for controlling the device means. This makes it possible to analyze cat behavior data in real time and provide appropriate stimuli based on the individual cat's behavioral patterns and preferences. In addition, by accumulating cat behavior data over time and learning changes in behavioral patterns based on that data, the cat's interest can be sustained. Furthermore, the function of automatically responding to physical stimuli from the cat and providing feedback on that response allows for effective play and training.

"Sensor means" refers to a device for detecting cat behavior, including motion sensors and cameras.

"Terminal means" refers to a device for transmitting data from sensor means to a server, and includes a data transmission module and a communication device.

The "server means" is a device that analyzes the received data using a generative AI model and generates instructions to provide appropriate stimulation to the cat.

A "generative AI model" is an artificial intelligence model that analyzes cat behavior data and generates instructions to provide appropriate stimuli based on the cat's behavioral patterns and preferences.

"Device means" refers to a device for providing stimuli to the cat based on instructions from the server means, and includes a robotic arm, a laser pointer, etc.

"Real-time" means that data is processed immediately the moment it is generated, providing an immediate response without delay.

"Behavioral patterns" refer to the tendencies and habits of a series of behaviors that a cat displays in response to specific situations or stimuli.

"Feedback" refers to the device's means' response to physical stimuli from the cat being sent back to the generative AI model, allowing the generative AI model to learn and generate more appropriate instructions.

This invention is a system that detects cat behavior, analyzes the data, and provides appropriate stimuli to the cat. This system includes sensor means, terminal means, server means, a generative AI model, and device means.

First, the device detects the cat's behavior using a sensor. Sensors include motion sensors and cameras. For example, if the cat scratches the device with its claws, this behavior is detected in real time.

The device then transmits the detected behavioral data to a server via a data transmission module. This data includes the cat's movement patterns and location information. For example, it includes the time and location information when the cat scratches the device.

The server inputs the received data into a generative AI model to analyze the cat's behavior. Examples of generative AI models used include OpenAI's GPT-4. The generative AI model determines whether the cat enjoys aggressive play. For example, if the cat frequently exhibits aggressive behavior toward the device, it learns that behavioral pattern.

Then, based on the analysis results, the server instructs the device to perform appropriate actions to stimulate the cat, for example, moving the robotic arm to attract the cat's interest.

Finally, the terminal receives instructions from the server and controls the device to provide appropriate stimuli to the cat, for example, moving a laser pointer to stimulate the cat.

As a concrete example, consider the following scenario: When a cat scratches its claws at the device, the motion sensor detects this movement. The sensor sends this information to the server via the data transmission module. The generative AI model analyzes the data and understands that cats prefer aggressive play. The generative AI model then instructs the robotic arm to perform actions that will attract the cat's interest. The robotic arm operates according to these instructions, providing the cat with appropriate stimuli.

Examples of prompts to input into a generative AI model include:

"Your cat has clawed at the device. Analyze this behavior and determine whether your cat prefers aggressive play. Then instruct the device on the appropriate action to stimulate your cat."

The above is an embodiment of the present invention.

The flow of the identification process in Example 2 will be explained using Figure 13.

Step 1:

The device uses sensor means to detect the cat's behavior. Specifically, motion sensors and cameras monitor the cat's movements in real time and detect aggressive behavior. For example, if the cat digs its claws into the device, this behavior will be detected.

Input: Cat movement

Output: Detected cat behavior data (e.g., time and location of cat claw movements)

Step 2:

The device sends the detected behavioral data to the server via the data transmission module. Specifically, the data obtained from the sensor is packetized and sent to the server via the network.

Input: Detected cat behavior data

Output: Behavioral data sent to the server

Step 3:

The server inputs the received data into a generative AI model to analyze the cat's behavior. Specifically, it inputs behavioral data into a generative AI model (e.g., GPT-4) to determine whether the cat prefers aggressive play.

Input: Behavioral data sent to the server

Output: Analysis of cat behavior patterns (e.g., cats prefer aggressive play)

Step 4:

Based on the analysis results, the server instructs the device on the appropriate actions to stimulate the cat. Specifically, it generates movement instructions for the robot arm and laser pointer based on the analysis results of the generative AI model.

Input: Analysis results of cat behavior patterns

Output: Commands to the device (e.g., moving the robotic arm to attract the cat's attention)

Step 5:

The terminal receives instructions from the server and controls the device to provide appropriate stimuli to the cat. Specifically, it moves the robotic arm and laser pointer to entertain the cat.

Input: Operation instructions from the server

Output: Appropriate stimuli provided to the cat (e.g., robotic arm movement, laser pointer movement)

The above is the specific flow of processing for this system's program.

(Application Example 2)

Next, we will explain Application Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Conventional safety monitoring systems in factories have the drawback of being unable to detect abnormal worker or machine behavior in real time and quickly respond appropriately. Furthermore, systems that understand animal behavior and provide appropriate stimuli are limited, and they are unable to learn changes in animal behavior patterns. To solve these issues, a system is needed that can monitor animal and worker behavior in real time, detect abnormal behavior, and respond appropriately.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

In this invention, the server includes a spherical device that can move around freely, means for operating the device from an information terminal, a sensor installed in the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, a sensor that detects abnormal behavior of workers and machines within the factory, means for transmitting data from the sensor to the generative AI and analyzing the abnormal behavior, and means for instructing the appropriate response based on the analysis results. This makes it possible to learn changes in the animal's behavior patterns and provide appropriate stimuli, as well as detect abnormal behavior of workers and machines within the factory in real time and respond quickly.

A "spherical, freely movable device" is a device that has a spherical shape and the ability to physically move freely.

An "information terminal" is an electronic device used to remotely control devices such as smartphones and tablets.

A "sensor that detects animal movements and behavior patterns" is a device that detects animal movements and behavior in real time and acquires that data.

"Generative AI" is an artificial intelligence system that analyzes acquired data, understands the behavioral patterns of animals and workers, and generates appropriate responses.

"Means for providing appropriate reactions and stimuli to animals" refers to devices and methods for providing appropriate reactions and stimuli to animals based on the analysis results of generative AI.

"Sensors that detect abnormal behavior of workers and machines in factories" are devices that monitor the behavior of workers and machines in factories and detect abnormal behavior in real time.

"Means for analyzing abnormal behavior" refers to a method or device for sending data on detected abnormal behavior to the generative AI and analyzing that data.

"Means for instructing appropriate responses" refers to a method or device for instructing appropriate responses to abnormal behavior based on the analysis results of generative AI.

As an embodiment of this invention, the following system is constructed.

First, a spherical, freely movable device is prepared. This device is equipped with sensors that detect the animal's movements and behavioral patterns. The device can be controlled from an information terminal (e.g., a smartphone or tablet).

Next, a generative AI is prepared. This generative AI analyzes the data obtained from the sensors to understand the animal's preferences and play styles. The generative AI generates instructions to provide the animal with appropriate reactions and stimuli.

In addition, sensors will be installed within the factory to detect abnormal behavior by workers or machines. These sensors will also send data to the generative AI, which will analyze the abnormal behavior. The generative AI will then instruct the appropriate response to the abnormal behavior.

A specific example would be the following system.

1. Animal behavior monitoring system

If an animal exhibits aggressive behavior toward the device, a sensor detects the behavior and sends that information to the generative AI. The generative AI analyzes the information and understands that the animal prefers aggressive play. Based on this understanding, it then instructs the device to perform actions that will stimulate the animal. The device then acts according to those instructions and provides the animal with appropriate stimulation.

2. Factory Safety Monitoring System

If a worker or machine in a factory behaves abnormally, a sensor detects the behavior and sends the data to the generative AI. The generative AI analyzes the data and detects abnormal behavior. If an abnormality is detected, the generative AI will instruct the appropriate response, such as sounding an alarm or halting work.

The hardware used includes sensors to detect animal movement, sensors to detect abnormal behavior within factories, information terminals, and spherical devices. The software used is a generative AI model.

As a concrete example, the following prompt sentence could be input into a generative AI model:

Example prompt:

"Analyze the data when a worker falls, and if an abnormality is detected, issue an instruction to sound an alarm."

In this way, it is possible to learn changes in animal behavior patterns and provide appropriate stimuli, as well as detect abnormal behavior of workers or machinery within the factory in real time and respond quickly.

The flow of the specific processing in Application Example 2 will be explained using Figure 14.

Step 1:

Sensors detect the movement of animals and workers.

Input: Animal and worker movement data

Data processing: Sensors collect operational data in real time and convert it into digital signals.

Output: Digitized motion data

Step 2:

Data obtained from the sensors is sent to the generative AI.

Input: Digitized motion data

Data processing: The data acquired by the sensor is packetized in order to be sent to the generative AI.

Output: Packetized motion data

Step 3:

Generative AI analyzes movement data.

Input: Packetized motion data

Data calculation: Generative AI analyzes movement data to identify abnormal movements and animal behavior patterns.

Output: Analysis results (detection of abnormal behavior and animal behavior patterns)

Step 4:

Generative AI will instruct appropriate responses based on the analysis results.

Input: Analysis results

Data calculation: Based on the analysis results, generative AI determines the appropriate response (e.g., sound an alarm, activate the device, etc.).

Output: Action instructions

Step 5:

Devices and information terminals operate according to the instructions of generative AI.

Input: Response instructions

Specific actions: The device provides appropriate stimuli to the animal, the information terminal sounds an alarm, etc.

Output: Action taken (stimulates animal, sounds alarm, etc.)

Step 6:

The generative AI receives feedback from the results of its actions.

Input: Result of the action performed

Data processing: Generative AI evaluates the execution results and accumulates data to reflect in the next response.

Output: Updated behavioral database

These steps will enable the system to learn changes in animal behavior patterns and provide appropriate stimuli, as well as detect abnormal behavior of workers or machinery within the factory in real time and respond quickly.

(Example 3)

Next, we will explain Example 3 of Form Example 3. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Previous animal devices struggled to learn an animal's behavioral patterns in real time and provide appropriate reactions and stimuli based on those patterns. Furthermore, there were no systems that could accumulate animal behavioral data over long periods of time and learn from those changes. This made it difficult to provide appropriate reactions and stimuli in response to changes in an animal's behavioral patterns.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

In this invention, the server includes means for storing data from sensors that detect animal movements and behavioral patterns in a database, means for cleansing the stored data and extracting behavioral patterns, means for the generative artificial intelligence to learn changes in behavioral patterns, and means for generating appropriate instructions based on the learning results. This makes it possible to provide appropriate reactions and stimuli in response to changes in the animal's behavioral patterns.

The "device" is a spherical device that can move freely and detects the movements and behavior patterns of animals.

A "personal digital assistant" is a portable electronic device, such as a smartphone or tablet, used to operate the device.

A "sensor" is a sensing device installed in a device to detect animal movements and behavior patterns.

"Generative AI" is AI that analyzes data from sensors, understands animals' preferences and play styles, and provides appropriate reactions and stimuli.

The "database" is an information management system for storing animal behavior data collected from sensors.

"Cleansing" is the process of removing noise from raw data stored in a database and filling in missing data.

A "behavioral pattern" is a series of behaviors that an animal tends to exhibit at a particular time or in a particular situation.

"Learning" is the process by which generative artificial intelligence understands changes in animal behavior patterns based on accumulated data.

"Instructions" are specific operational commands that generative AI issues to a device based on its learning results.

"Reactions" are specific actions or stimuli that the device performs on the animal in accordance with instructions from the generative artificial intelligence.

This invention is a system that learns animal behavior patterns in real time and provides appropriate reactions and stimuli based on those patterns. Specific embodiments of this system are described below.

Hardware and software used

Hardware: Sensors (cameras, microphones, etc.) that detect animal movements and behavior patterns, a spherical device that can move freely, and a mobile information terminal (smartphone or tablet)

Software: Generative AI (e.g., OpenAI's GPT-4), databases (MySQL and MongoDB)

System Configuration

1. Device:

It is equipped with sensors to detect animal movements and behavior patterns.

Data from sensors is collected in real time and sent to a server.

2. Mobile Information Devices:

Used as a means to operate the device.

Users can control the device's operation through their mobile information terminal.

3. Server:

Receives data sent from sensors and stores it in a database.

Clean the accumulated data and extract behavioral patterns.

Uses generative artificial intelligence to learn changes in behavioral patterns.

Based on the learning results, appropriate instructions are generated for the device.

Specific examples

For example, consider a situation where a cat initially prefers aggressive play, but over time begins to prefer gentle play.

1. Data Collection:

The device (camera) captures the cat poking at the toy as it moves vigorously.

The server receives the video data and stores it in a database.

2. Data preprocessing:

The server removes unnecessary parts from the video data and extracts only the cat's movements.

The server organizes the extracted data by time and analyzes the cat's behavioral patterns.

3. Learning behavioral patterns:

The server uses generative artificial intelligence to learn when the cat has changed from aggressive to calm play.

The server saves the learning results and proceeds to the next step.

4. Generating appropriate instructions:

The server inputs a prompt to the generative AI: "Since the cat has started to prefer gentle play, please generate instructions to move a toy with gentle movements."

The server sends the generated instructions to the device.

5. Providing Reactions:

The device (toy) makes gentle movements according to instructions received from the server.

The device provides gentle play for your cat and responds to your cat's behavioral patterns.

Example prompt

By inputting the following prompt sentence into the generative artificial intelligence, instructions based on changes in the cat's behavioral patterns can be generated.

Behavioral data for a cat is shown below. At first, the cat preferred aggressive play, but over time, it began to prefer gentle play. Based on this change, generate instructions to provide the cat with appropriate reactions and stimuli.

In this way, the system is able to provide appropriate reactions and stimuli in response to changes in the animal's behavioral patterns. The flow of the identification process in Example 3 will be explained using Figure 15.

Step 1: Data Collection

The device (sensor) monitors the animal's movements in real time and collects behavioral data. For example, a camera captures a cat's movements and a microphone records the cat's meows.

Input: Real-time animal movements and sounds

Output: Animal behavior data (video and audio data)

Specific operation: The camera captures the cat's movements, and the microphone records the cat's meows. The device collects this data and sends it to the server.

Step 2: Data preprocessing

The server cleanses the raw data stored in the database. Specifically, it removes noise and fills in missing data.

Input: Raw data (video data, audio data)

Output: Cleansed data

Specific operation: The server removes unnecessary parts from the video data and filters noise from the audio data. Any missing data is filled in.

Step 3: Extracting behavioral patterns

The server organizes the cleansed data by time and extracts behavioral patterns.

Input: Cleansed data

Output: Behavioral pattern data

Specific operation: The server analyzes the cleansed data and extracts information about the animal's behavior at specific times of the day.

Step 4: Learning behavioral patterns

The server uses a generative AI model to learn animal behavior patterns based on accumulated data.

Input: Behavioral pattern data

Output: Learning results (changes in behavioral patterns)

Specific operation: The server inputs behavioral pattern data into the generative AI model, which then learns changes in the animal's behavior. For example, it learns that a cat has changed from aggressive play to calm play.

Step 5: Generate appropriate instructions

The server generates appropriate instructions for the device based on the learning results.

Input: Learning results

Output: Instruction data

Specific behavior: The server inputs a prompt to the generative AI model: "Since the cat has started to prefer gentle play, please generate instructions to move a toy with gentle movements," and sends the generated instructions to the device.

Step 6: Provide a response

The terminal (device) operates according to the instructions received from the server.

Input: Instruction data

Output: Reaction to animals

Specific action: The device activates a toy with gentle movements, providing gentle play for the cat.

(Application Example 3)

Next, we will explain Application Example 3 of Form Example 3. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Conventional animal devices and generative AI were limited to learning animal behavior patterns and providing appropriate reactions. However, there were no systems that could learn the behavior patterns of workers in factories and provide appropriate support. As a result, improvements in work efficiency and reductions in worker burden were not fully achieved. Therefore, there is a need for a system that can learn the behavior patterns of workers in factories and provide appropriate support.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

In this invention, the server includes a spherical device that can move around freely, means for operating the device from a smartphone, a sensor installed in the device that detects the animal's movements and behavioral patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and behavioral patterns, means for providing appropriate reactions and stimuli to the animal based on the AI, and means for accumulating worker behavioral data over time, learning changes in behavioral patterns based on the accumulated data, and providing appropriate support. This makes it possible to learn the behavioral patterns of workers within the factory and provide appropriate support.

A "spherical, freely movable device" is a device that has a spherical shape and the ability to physically move freely.

"Means for operating from a smartphone" refers to the interface or software for remotely operating a device using a smartphone.

A "sensor that detects animal movements and behavior patterns" is a device that detects animal movements and behavior in real time and collects that data.

"Generative AI" is an artificial intelligence technology that learns the behavioral patterns of animals and workers based on collected data and provides appropriate reactions and support.

"Means for providing appropriate reactions and stimuli" refers to devices or functions that provide appropriate reactions and stimuli to animals and workers based on the results of learning by the generative AI.

"Means for accumulating worker behavioral data over time" refers to a system that continuously records worker behavior and stores that data for long periods of time.

"Means of learning changes in behavioral patterns and providing appropriate support" is a function that analyzes accumulated behavioral data, recognizes changes in behavioral patterns, and provides optimal support to workers.

The following hardware and software are required to implement this invention. Hardware requires a spherical, freely movable device, a smartphone, a factory robot, and sensors. Software requires Python, scikit-learn, and a generative AI model.

First, the spherical, freely movable device is equipped with sensors that detect the behavior of animals and workers in real time. These sensors detect the movements and behavioral patterns of animals and workers and collect that data. The collected data is sent to a generative AI model for analysis.

The generative AI model learns the behavioral patterns of animals and workers based on collected data. This learning process uses Python and scikit-learn. Specifically, it uses the KMeans clustering algorithm to classify behavioral patterns and learns how behavioral patterns change over time.

Once learning is complete, the generative AI model will provide instructions for providing appropriate reactions and stimuli to animals and workers. For example, if an animal prefers aggressive play, the device will provide appropriate stimuli. Also, if a worker transitions from manual to automated tasks, the robot will provide appropriate support.

For example, if a worker is manually assembling parts in a factory, a robot will help carry the parts. Also, if a worker is operating automated machinery, a robot will help with machine maintenance.

Examples of prompt statements include:

"Develop AI that collects data on worker behavior in factories and learns changes in behavioral patterns based on that data. For example, when workers transition from manual to automated tasks, create a robot that learns this change and provides appropriate support."

In this way, this invention can improve work efficiency within factories and reduce the burden on workers.

The flow of the specific processing in Application Example 3 will be explained using Figure 16.

Step 1:

The server uses sensors to collect behavioral data of animals and workers. The input is real-time behavioral data obtained from the sensors, and the output is a list of collected behavioral data. Specifically, the sensors detect the movements of animals and workers and send that data to the server.

Step 2:

The server accumulates the collected behavioral data. The input is the behavioral data collected in step 1, and the output is a database of accumulated behavioral data. Specifically, the server saves the data it receives in the database.

Step 3:

The server uses the accumulated behavioral data to train a generative AI model. The input is the accumulated behavioral data, and the output is the trained generative AI model. Specifically, the server uses Python and scikit-learn to run the KMeans clustering algorithm and classify behavioral patterns.

Step 4:

When new behavioral data is input, the server uses a generative AI model to predict behavioral patterns. The input is the new behavioral data, and the output is the predicted behavioral pattern. Specifically, the server inputs the new data into the generative AI model and obtains the predicted results.

Step 5:

The server issues instructions to provide appropriate reactions and support based on the prediction results. The input is the predicted behavior pattern, and the output is instructions for reactions and support. In terms of specific operations, the server instructs the device or robot to perform the appropriate action.

Step 6:

The terminal (smartphone) receives instructions from the server and operates the device or robot. The input is the instruction from the server, and the output is the operation of the device or robot. Specifically, the smartphone sends operation commands to the device or robot.

Step 7:

The user monitors the operation of the device or robot and operates it manually as necessary. The input is the operating status of the device or robot, and the output is the user's operation commands. Specifically, the user manually operates the device or robot using a smartphone.

It is also possible to further combine an emotion engine that estimates the user's emotion. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

"Example 1"

One embodiment of the present invention provides a system that incorporates an emotion engine. This system recognizes the user's emotions and adjusts the reactions and stimuli given to the cat according to those emotions. Specifically, when the user is happy, the system encourages the cat to play actively. Conversely, when the user is depressed, the system encourages the cat to play quietly. This enables optimal interaction with the cat according to the user's emotional state.

"Example 2"

The emotion engine also recognizes emotions from the user's tone of voice, facial expressions, or physical reactions. For example, if the user is smiling, the system will recognize that the user is happy and encourage the cat to play actively. Conversely, if the user is crying, the system will recognize that the user is sad and encourage the cat to play quietly. This allows for a more accurate understanding of the user's emotional state and optimal interaction with the cat accordingly.

"Example 3"

Furthermore, the emotion engine adjusts the device's movements and reactions according to the user's emotions, improving the interaction between the user and the cat. For example, when the user is angry, the system suppresses the device's movements to prevent the cat from bothering the user. Conversely, when the user is happy, the system activates the device's movements to allow the cat to play happily with the user. This enables optimal interaction with the cat according to the user's emotional state.

The processing flow for each example is explained below.

"Example 1"

Step 1: The user's emotion engine recognizes the user's emotion.

Step 2: Based on the recognized emotion, the system adjusts its reactions and stimuli to the cat.

Step 3: When the user is happy, the system encourages active play with the cat.

Step 4: When the user is feeling down, the system encourages quiet play with the cat.

"Example 2"

Step 1: The emotion engine recognizes emotions from the user's tone of voice, facial expressions, or physical reactions.

Step 2: If the user is smiling, the system recognizes that the user is happy and encourages active play with the cat.

Step 3: If the user is crying, the system recognizes that the user is sad and prompts the cat to play quietly.

"Example 3"

Step 1: The emotion engine recognizes the user's emotions.

Step 2: Adjust the device's movements and responses based on the user's emotions.

Step 3: When the user is angry, the system inhibits the device's movement to prevent the cat from bothering the user.

Step 4: When the user is happy, the system activates the device's activity, allowing the cat to play happily with the user.

(Example 1)

Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Previous animal devices simply detected animal movements and behavioral patterns, but were unable to understand the animal's preferences and play styles and provide appropriate reactions or stimulation. Furthermore, they lacked the ability to adjust interactions with the animal based on the user's emotional state, making it difficult to deepen the relationship between the user and the animal.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, and an emotion engine that recognizes the user's emotions and adjusts the reactions and stimuli to the animal according to those emotions. This makes it possible to understand the animal's behavior patterns and provide optimal reactions and stimuli according to the user's emotional state.

A "device" is a spherical piece of equipment that can move freely.

An "information terminal" is an electronic device that provides a means for operating a device.

A "sensor" is a device used to detect animal movements and behavior patterns.

"Generative AI" is artificial intelligence that analyzes data from sensors and understands animals' preferences and play styles.

"Means for providing reactions and stimuli" refers to a mechanism for providing appropriate reactions and stimuli to animals based on the analysis results of the generative AI.

The "emotion engine" is a system that recognizes the user's emotions and adjusts the reactions and stimuli given to animals based on those emotions.

"Animal behavior data" is information about animal movements and behavior patterns.

"Feedback" is the process of returning the device's response to physical stimuli from the animal to the generative AI.

This invention is a system that understands animal behavior patterns and provides optimal reactions and stimuli according to the user's emotional state. Specific embodiments of this system are described below.

Hardware and software used

Device: A spherical device that can move freely. It is equipped with motors, batteries, and sensors.

Information terminal: An electronic device that provides a means for operating a device. Examples include smartphones and tablets.

Sensor: A device used to detect animal movements and behavior patterns. Accelerometers and infrared sensors are used.

Generative AI: Artificial intelligence that analyzes data from sensors to understand animals' preferences and play styles. It uses AI models that run on the cloud.

Emotion engine: A system that recognizes the user's emotions and adjusts the animal's reactions and stimuli accordingly. Emotion recognition software is used.

Program processing

The server receives the animal's behavioral data sent from the device and inputs it into the generative AI. The generative AI analyzes the received data to understand the animal's preferences and play styles. Based on the analysis results, the generative AI then generates instructions to provide the animal with appropriate reactions and stimuli, and sends these to the device.

The device collects data to recognize the user's emotions. For example, it uses the smartphone's camera and microphone to analyze the user's facial expressions and tone of voice. The emotion engine receives the user's emotional data and adjusts the animal's reactions and stimuli according to those emotions.

Specific examples

Example 1: When a cat approaches the device, the sensor detects its movement and sends the data to the server. The server uses a generative AI model to determine that the cat is interested and sends the device an instruction to "rotate to attract the cat's attention." The device then begins to rotate in place.

Example 2: When a user is using a smartphone, the device captures the user's facial expression with its camera, and the emotion engine recognizes that the user is happy. The server then sends instructions to the generative AI model to encourage active play, causing the device to act as if it were running around with a cat.

Example prompt

"Describe what happens when a cat approaches the device."

"Describe how users react to cats when they're happy."

The above is a specific embodiment for implementing this invention. This system makes it possible to understand animal behavior patterns and provide optimal reactions and stimuli according to the user's emotional state.

The flow of the identification process in Example 1 will be explained using Figure 17.

Step 1:

Initializing the device

Server: Initializes the device. Checks the status of the motor and battery, and ensures that sensors are working properly.

Input: The signal that powers on the device.

Output: Signal that initialization is complete.

Specific operation: When the device is turned on, the server checks the status of each component of the device and, if everything is normal, sends a signal indicating that initialization is complete.

Step 2:

Cat movement detection

Device: Uses internal sensors to detect your cat's movements and behavior patterns in real time.

Input: Cat movements and behavior.

Output: Detection data.

Specific behavior: When a cat approaches or touches the device, the sensor detects the movement and collects data.

Step 3:

Data transmission

Device: Sends detected data to the server.

Input: Detection data.

Output: Send data to the server.

Specific operation: The data collected by the sensor is sent to the server via wireless communication.

Step 4:

Data analysis

Server: Inputs the received data into a generative AI model to analyze the cat's behavioral patterns and preferences.

Input: Detection data.

Output: Behavioral pattern analysis results.

Specific operation: The server inputs the data "a cat touched the device" into the generated AI model, and the AI determines that "the cat is showing interest."

Step 5:

Generating instructions

Server: Based on the analysis results, generates instructions to provide the cat with appropriate reactions and stimuli.

Input: Behavioral pattern analysis results.

Output: Instructions to the device.

Specific operation: The server generates an instruction to "rotate the device to attract the cat's attention" and sends it to the device.

Step 6:

Device Operation

Device: Operates according to instructions from the server and provides appropriate reactions and stimuli to the cat.

Input: Instructions from the server.

Output: Device operation.

Specific action: The device will start to rotate and act in a way that will attract the cat's interest.

Step 7:

User emotion recognition

Device: Collect data to recognize the user's emotions. For example, use the smartphone's camera and microphone.

Input: User's facial expression and tone of voice.

Output: Emotion data.

Specific operation: The device analyzes the user's facial expressions and tone of voice to recognize their emotional state.

Step 8:

Adjusting instructions based on emotions

Server: Receives the user's emotional data and adjusts the cat's reactions and stimuli.

Input: Emotion data.

Output: Adjusted instructions.

Specific behavior: If the server recognizes that the user is happy, it sends instructions to the generative AI model to encourage active play. The device then behaves as if it is running around with a cat.

(Application Example 1)

Next, we will explain Application Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Previous pet devices simply detected animal behavior patterns and were unable to deeply understand the animal's preferences or play styles. Furthermore, they lacked the ability to adjust interactions with the animal based on the user's emotional state, making it difficult to provide interactions with the pet that best fit the user's emotional state. Furthermore, they lacked a way to control the device or display animal behavior data in real time, making it difficult for users to understand the device's operating status and the animal's behavior.

The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavioral patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, means for recognizing the user's emotional state using an emotion engine and adjusting the reactions and stimuli provided to the animal in accordance with the emotional state, and means for displaying the device's operation and the animal's behavioral data on the information terminal. This makes it possible to deeply understand the animal's behavioral patterns and provide optimal interactions with the pet in accordance with the user's emotional state.

A "spherical device capable of moving freely" is a spherical device that has an internal motor and battery and can move autonomously based on external instructions.

An "information terminal" is an electronic device, such as a smartphone or tablet, that is operated by the user to control the device.

A "sensor that detects animal movements and behavior patterns" is a device that detects an animal's location, speed, movements, etc. in real time and collects that data.

"Generative AI" is an artificial intelligence system that analyzes collected data and understands animals' preferences and play styles.

The "emotion engine" is a system that recognizes the user's emotional state and adjusts interactions with animals based on that information.

"Means for providing appropriate reactions and stimuli to animals" refers to a mechanism that allows appropriate actions and reactions to be taken by animals based on the analysis results of the generative AI.

"Means for displaying the device's operation and animal behavior data on an information terminal" refers to a function for displaying the device's operating status and animal behavior data on an information terminal in real time.

A system for implementing this invention includes a spherical, freely movable device, an information terminal, a sensor that detects animal movements and behavior patterns, a generative AI, an emotion engine, and a means for displaying on the information terminal.

System Configuration

1. Spherical device:

It is equipped with a motor and battery inside and moves autonomously based on external instructions.

Equipped with sensors to detect animal movements and behavior patterns.

2. Information terminal:

Electronic devices operated by users, such as smartphones and tablets.

Displays device operation and animal behavior data in real time.

3. Sensor:

It detects animals' location, speed, movements, etc. in real time and collects that data.

4. Generative AI:

Analyze the collected data to understand the animals' preferences and play styles.

Generative AI models are used to generate instructions to provide appropriate reactions and stimuli to animals.

5. Emotion Engine:

Recognizes the user's emotional state and adjusts interactions with animals based on that information.

6. Display means:

Device operation status and animal behavior data are displayed on the information terminal.

Program processing explanation

The server first collects animal behavior data from sensors. This data is sent to the generative AI, which analyzes the animal's preferences and play styles. Based on the analysis results, the generative AI generates instructions to provide the animal with appropriate reactions and stimuli. Furthermore, an emotion engine recognizes the user's emotional state and adjusts interactions with the animal based on that information. Finally, device operations and animal behavior data are displayed in real time on the information terminal.

Specific examples

For example, if this system were used in a pet shop, when a customer was playing with a cat, the smartphone app would analyze the cat's behavior in real time and adjust how the customer interacted with the cat depending on the customer's emotional state. An example of a prompt sentence to be input into the generative AI model is as follows:

Example prompt:

Cat behavior data: Movement: Active, Play style: Chasing a ball

User's emotional state: State: Happy

Based on this data, generate instructions to provide appropriate reactions and stimuli for your cat.

By inputting this prompt into a generative AI model, we can obtain appropriate reactions and stimulation instructions for the cat.

The flow of the specific processing in Application Example 1 is explained using Figure 18.

Step 1:

The server obtains animal behavior data from sensors. The sensors detect the animal's position, speed, movement, etc. in real time and send the data to the server. The input is raw data from the sensors, and the output is the animal's behavior data sent to the server.

Step 2:

The server sends the acquired animal behavior data to the generative AI. The generative AI analyzes the received data and understands the animal's preferences and play styles. The input is the animal's behavior data, and the output is the analysis results regarding the animal's preferences and play styles.

Step 3:

The server generates instructions to provide appropriate reactions and stimuli to the animal based on the analysis results from the generative AI. It uses the generative AI model to create prompts and generate specific instructions for the animal. The input is the analysis results of the generative AI, and the output is instructions for the animal.

Step 4:

The server uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes data such as the user's facial expressions and voice to identify the user's emotional state. The input is the user's emotional data, and the output is the user's emotional state.

Step 5:

The server adjusts the reactions and stimuli given to the animal based on the user's emotional state. Based on the output of the emotion engine, it modifies the instructions of the generative AI to provide optimal interaction. The input is the user's emotional state and the instructions of the generative AI, and the output is the adjusted instructions given to the animal.

Step 6:

The server sends the adjusted instructions to the spherical device. The device acts based on the received instructions and provides the animal with an appropriate reaction or stimulus. The input is the adjusted instructions, and the output is the device's behavior.

Step 7:

The terminal displays device operation and animal behavior data in real time. Users can check the device's operating status and the animal's behavior through the information terminal. The input is device operation data and animal behavior data, and the output is the information displayed on the information terminal.

(Example 2)

Next, we will explain Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Previous animal devices struggled to provide appropriate responses to animal behavior and were unable to realize interactions that took the user's emotional state into account. This made it difficult to provide an optimal experience for both the animal and the user. Furthermore, there was a lack of systems that could learn changes in the animal's behavioral patterns and adapt over the long term.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

In this invention, the server includes means for operating a spherical, freely mobile device, means for using sensors to detect the animal's movements and behavioral patterns, means for using generative AI to analyze data from the sensors and understand the animal's preferences and play styles, means for using an emotion engine to recognize the user's emotional state, and means for optimizing interactions with the animal based on the generative AI and emotion engine. This makes it possible to provide appropriate responses to the animal's behavior and enable interactions that take the user's emotional state into consideration. It also makes it possible to learn changes in the animal's behavioral patterns and adapt over the long term.

A "device" is a spherical piece of equipment that can move freely.

An "information terminal" is an electronic device that provides a means for operating a device.

A "sensor" is a device that detects animal movements and behavior patterns.

"Generative AI" is artificial intelligence that analyzes data from sensors and understands animals' preferences and how they play.

An "emotion engine" is software or hardware that recognizes the user's emotional state.

"Reactions" are appropriate responses or stimuli provided to animals based on generative AI.

"Interaction optimization" refers to optimizing the interaction between animals and users based on generative AI and an emotion engine.

"Behavioral data" is information about animal movements and behavior patterns.

"Feedback" means that the device automatically responds to physical stimuli from the animal and transmits that response to the generative AI.

This invention is a system that provides optimal interaction based on the animal's behavior and the user's emotional state. Specific embodiments of this system are described below.

Hardware and software used

Device: A spherical, freely movable device that provides physical responses to the animal's behavior.

Information terminal: An electronic device that provides a means for operating a device. Examples include smartphones and tablets.

Sensor: A device that detects animal movements and behavior patterns. It is installed in the device and collects data in real time.

Generative AI: Artificial intelligence that analyzes data from sensors to understand animals' preferences and play styles. An example of this is OpenAI's GPT-4.

Emotion engine: Software or hardware that recognizes the user's emotional state. It analyzes the user's tone of voice, facial expressions, or physical reactions.

System Operation

The server receives the animal's behavior data sent from the sensor and analyzes it using generative AI. The generative AI understands the animal's behavioral patterns and sends instructions to the device to provide appropriate reactions and stimuli.

Furthermore, the server uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes the user's tone of voice and facial expressions to determine whether the user is happy or sad. The server optimizes interactions with the animal based on this emotional state.

Specific examples

For example, if a cat scratches the device, the sensor detects the action. The sensor sends the data to a server, which analyzes the data using generative AI. The generative AI understands that the cat prefers aggressive play and instructs the device to move a cat toy. The device follows this instruction to move the cat toy and provide the cat with the appropriate stimulation.

At the same time, the server uses its emotion engine to recognize the user's smile and determine that the user is happy. The server then encourages the cat to play actively depending on the user's emotional state.

Example prompt

"What should I do if my cat is acting aggressively towards my device?"

"Please tell me what kind of play I should encourage the cat to do when the user is smiling."

This system enables optimal interaction based on the emotional state of the animal and the user.

The flow of the identification process in Example 2 will be explained using Figure 19.

Step 1:

Data collection using sensors

The server monitors the animal's behavior in real time using sensors installed on the device. The sensors detect any aggressive behavior from the animal toward the device. For example, if a cat digs its claws into the device, the sensor detects this behavior. The input is the animal's behavior data, and the output is the detected behavior data.

Step 2:

Data transmission

The sensor sends the detected behavioral data to the server. The server receives this data and passes it on to the generative AI. The input is the behavioral data sent from the sensor, and the output is the behavioral data sent to the server.

Step 3:

Analysis using generative AI

The server uses generative AI to analyze the behavioral data it receives. The generative AI uses, for example, OpenAI's GPT-4, to understand that animals prefer aggressive play. Specifically, it analyzes the behavioral data and determines that the behavior constitutes aggressive play. The input is the behavioral data sent to the server, and the output is the analysis results.

Step 4:

Device instructions

The server issues instructions to the device based on the analysis results of the generative AI. For example, it instructs the device to move a cat toy. The device follows this instruction to move the cat toy and provide the cat with appropriate stimulation. The input is the analysis results of the generative AI, and the output is the instruction to the device.

Step 5:

Recognize user emotions using an emotion engine

The server uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's tone of voice, facial expressions, or physical reactions. For example, if the user is smiling, the emotion engine recognizes that the user is happy. The input is the user's emotion data, and the output is the emotion recognition result.

Step 6:

Cat interaction optimization

The server optimizes interactions with animals according to the user's emotional state. For example, if the user is smiling, it encourages the animal to play actively. Conversely, if the user is crying, it encourages the animal to play quietly. This allows for optimal interaction with animals according to the user's emotional state. The input is the emotion recognition result, and the output is instructions for optimized interactions.

(Application Example 2)

Next, we will explain Application Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Previous pet devices struggled to provide interactions that fully took into account the animal's behavior and the user's emotional state. Furthermore, they lacked a means to provide appropriate stimuli based on the animal's behavioral patterns and the user's emotions, making it difficult to increase satisfaction for both the pet and the user.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing the animal with appropriate reactions and stimuli based on the AI, an emotion engine that recognizes the user's emotional state, and means for adjusting interactions with the animal based on the emotion engine. This enables appropriate interactions that take into account the animal's behavior and the user's emotional state in real time.

A "spherical, freely movable device" is a device that has a spherical shape and can physically move freely.

An "information terminal" is an electronic device operated by a user, such as a smartphone or tablet.

A "sensor that detects animal movements and behavior patterns" is a device that detects animal movements and behavior in real time.

"Generative AI" is an artificial intelligence system that analyzes collected data and understands animals' preferences and behavioral patterns.

"Means for providing appropriate reactions and stimuli" refers to devices and methods for providing appropriate reactions and stimuli to animals based on the analysis results of the generative AI.

The "emotion engine" is a system that recognizes emotions from the user's tone of voice, facial expressions, and physical reactions.

"Means for adjusting interactions with animals" refers to devices and methods for optimizing interactions with animals based on the recognition results of the emotion engine.

This invention is a system that takes into account the animal's behavior and the user's emotional state in real time to provide appropriate interaction. Below, we will show a specific embodiment for realizing this system.

System Configuration

The system consists of the following main components:

1. A spherical, freely movable device:

This device is a spherical device that can be moved freely to induce animal behavior. It is equipped with a motor and battery inside and operates according to instructions from an information terminal.

2. Information terminal:

Electronic devices such as smartphones and tablets that provide an interface for users to operate the device. Dedicated applications are installed on them to control the device's operation.

3. Sensors that detect animal movements and behavior patterns:

The device is equipped with a camera and accelerometer to detect animal movements and behavior in real time.

4. Generation AI:

It is an artificial intelligence system that analyzes collected data to understand animals' preferences and behavioral patterns. Generative AI accumulates animal behavioral data over time and learns changes in behavioral patterns based on that data.

5. How to provide appropriate reactions and stimuli:

This is a device or method for providing appropriate responses or stimuli to animals based on the analysis results of generative AI. For example, the device may stimulate the animal by performing a specific movement.

6. Emotion Engine:

This is a system that recognizes emotions from the user's tone of voice, facial expressions, and physical reactions. The emotion engine detects the user's emotional state in real time through the camera and microphone.

7. Ways to regulate interactions with animals:

An apparatus and method for optimizing interactions with animals based on the recognition results of an emotion engine. For example, if the user is recognized as sad, the device will behave calmly.

Program processing explanation

The server detects the user's emotional state through a camera and microphone and sends it to the generative AI. The generative AI analyzes the animal's behavioral data and the user's emotional data to determine an appropriate reaction. The information terminal receives instructions from the generative AI and instructs the device on how to act.

The hardware used includes a camera (to detect animal behavior and the user's facial expressions), a microphone (to detect the user's tone of voice), and a motor (to control the device's movement). The software includes OpenCV (image processing), Keras (emotion recognition model), and requests (communication with AI services).

Specific examples

For example, if a user comes into the store with a smiling face and a pet, the emotion engine will recognize that the user is happy. The generative AI will analyze the animal's behavioral data and the user's emotional data and instruct the device to behave in a way that encourages active play. Conversely, if the user looks sad, the device will be instructed to behave calmly.

Example prompt

"If the user's emotion is 'happy' and the animal's behavior is 'aggressive,' we will provide a toy that encourages active play with the animal."

The flow of the specific processing in Application Example 2 is explained using Figure 20.

Step 1:

The server captures the user's facial expressions and tone of voice in real time through a camera and microphone. It receives camera footage and audio data as input. It preprocesses this data using OpenCV and audio processing libraries to extract the user's facial features and tone of voice. It generates data indicating the user's emotional state as output.

Step 2:

The server uses an emotion engine to analyze the user's emotional state data obtained in step 1. It uses facial feature points and voice tone data as input. The emotion engine inputs this data into an emotion recognition model (using Keras) and classifies the user's emotions into categories such as "happy" or "sad." As an output, it generates a label indicating the user's emotional state.

Step 3:

The terminal acquires animal behavior data in real time through sensors installed on the device. As input, it receives data from the sensors (acceleration, location information, etc.). It preprocesses this data to extract the animal's movements and behavioral patterns. As output, it generates data indicating the animal's behavioral state.

Step 4:

The server uses generative AI to integrate and analyze the user's emotional state data obtained in step 2 and the animal's behavior data obtained in step 3. The user's emotional state data and the animal's behavior data are used as input. The generative AI determines appropriate reactions and stimuli for the animal based on this data. As output, it generates operational instructions for the device.

Step 5:

The terminal sends the operation instructions generated in step 4 to the device. As input, it receives operation instruction data from the generative AI. The terminal transmits these instructions to the device's motor control system, controlling the device to perform the appropriate operation. As output, the device's physical operation is executed.

Step 6:

The device automatically responds to physical stimuli from the animal and feeds that response back to the generative AI as animal behavior data. As input, it receives physical stimulus data from the animal. The device detects this data with sensors and sends it to the generative AI. As output, the animal's behavior data is updated.

Step 7:

The server re-analyzes the animal's behavior data updated in step 6 and learns changes in the animal's behavior patterns. It uses the updated animal's behavior data as input. The generative AI accumulates this data and learns changes in the animal's behavior patterns. As output, it generates new movement instructions based on the animal's behavior patterns.

(Example 3)

Next, we will explain Example 3 of Form Example 3. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Previous animal devices struggled to provide appropriate reactions and stimuli based on the animal's behavioral patterns and the user's emotional state. Furthermore, they lacked the ability to accumulate animal behavioral data over time and learn from changes in that data, making it impossible to respond appropriately to the animal's interests and preferences. Furthermore, the device's movements and responses were not adjusted to take the user's emotional state into account, resulting in suboptimal interactions between the user and the animal.

The specific processing by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means. In this invention, the server includes a spherical device that can move freely around, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, an emotion engine for analyzing the user's emotional state, and means for adjusting the device's movements and reactions based on the analysis results of the emotion engine. This makes it possible to provide appropriate reactions and stimuli in response to changes in the animal's behavior patterns, enabling optimal interaction according to the user's emotional state.

A "device" is a spherical piece of equipment that can move freely.

An "information terminal" is an electronic device that provides a means for operating a device.

A "sensor" is a device used to detect animal movements and behavior patterns.

"Generative AI" is artificial intelligence that analyzes data from sensors and understands animals' preferences and how they play.

An "emotion engine" is software or hardware for analyzing a user's emotional state.

A "reaction" is an appropriate response or stimulus provided to an animal.

"Animal behavior data" is information about animal movements and behavior patterns.

"User's emotional state" refers to the emotional state the user is feeling.

This invention is a system that analyzes animal behavior data and the user's emotional state to provide optimal interaction. A specific embodiment of this system is described below.

System Configuration

The system consists of the following main components:

1. Device: A spherical, freely movable device. The device is equipped with sensors to detect animal movements and behavior patterns.

2. Information terminal: An electronic device that provides a means for operating a device. Examples include smartphones and tablets.

3. Server: The central component that receives and analyzes data from devices and information terminals.

4. Generative AI: Artificial intelligence that analyzes data from sensors and understands animals' preferences and play styles.

5. Emotion engine: Software or hardware for analyzing the user's emotional state.

Data collection and analysis

The server collects animal behavior data from sensors installed on the device. For example, a camera tracks a cat's movements and a sensor detects which objects the cat touches. The collected data is stored in a database.

Generative AI analyzes accumulated behavioral data and learns the behavioral patterns of animals. For example, it learns that cats become active at 8am every morning and that they prefer certain toys. Based on this learning, it issues appropriate instructions to the device.

User sentiment analysis and device adjustment

The device uses a camera and microphone to analyze the user's emotional state. For example, it analyzes the user's facial expressions and tone of voice to determine whether the user is angry or happy.

The server adjusts the device's movements and reactions based on the analysis results of the emotion engine. For example, when the user is angry, the device's movements will be suppressed so that the animal can remain quiet. Conversely, when the user is happy, the device's movements will be more active so that the user can play with the animal.

Specific examples

For example, if a cat initially likes chasing laser pointers, but after a few weeks starts to prefer rolling a ball, the generative AI will learn this change and instruct it to move the ball-rolling device more frequently.

Also, when the user comes home from work and is tired, the emotion engine detects the user's fatigue and reduces the device's activity so that the cat can stay quiet. Conversely, when the user is relaxing on a day off, the device's activity will be more active so that the user can play with the cat.

Example prompt

"Please explain the generative AI program that accumulates cat behavior data and learns changes in behavior patterns."

"Please explain how the emotion engine works, adjusting the device's behavior and responses based on the user's emotions."

In this way, the system utilizes animal behavior data and user emotion data to provide optimal interaction. The flow of the identification process in Example 3 will be explained using Figure 21.

Step 1:

The server collects animal behavior data from sensors installed on the device. As input, it receives real-time data from the sensors and, as output, generates data on the animal's movements and behavior patterns. Specifically, the camera tracks the cat's movements and the sensor detects which objects the cat touches.

Step 2:

The server stores the collected behavioral data in a database. As input, it receives the animal behavioral data generated in step 1, and as output, it stores the time-stamped behavioral data in the database. Specifically, it records the data "October 1, 2023, 08:00:00 - Cat chases laser pointer."

Step 3:

Generative AI analyzes accumulated behavioral data and learns animal behavior patterns. It receives behavioral data stored in a database as input and generates learning results about the animal's behavior patterns as output. Specifically, it learns the pattern of "chasing a laser pointer every morning at 8 o'clock."

Step 4:

The server issues instructions to the device based on the learning results of the generative AI. It receives the learning results of the generative AI as input and generates specific instructions for the device as output. Specifically, it issues the instruction "move the laser pointer at 8 o'clock every morning."

Step 5:

The device uses a camera and microphone to analyze the user's emotional state. As input, it receives data related to the user's facial expressions and tone of voice, and as output, it generates an analysis result related to the user's emotional state. Specifically, if the user is smiling while speaking, it is determined that they are happy.

Step 6:

The server adjusts the device's movements and reactions based on the analysis results of the emotion engine. It receives the user's emotion analysis results as input and generates specific instructions regarding the device's movements and reactions as output. Specifically, when the user is angry, the device's movements are suppressed so that the animal can remain quiet. Conversely, when the user is happy, the device's movements are made more active so that the user can play with the animal.

(Application Example 3)

Next, we will explain Application Example 3 of Form Example 3. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

Previous pet interaction systems struggled to provide appropriate reactions and stimuli based on changes in animal behavior patterns and the user's emotional state. Furthermore, they lacked the ability to provide real-time advice on how users should interact with animals, making it difficult to achieve optimal interactions with animals.

The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, an emotion engine that senses the user's emotional state and adjusts the device's movements and reactions, and means for advising the user on optimal interactions with the animal. This makes it possible to provide appropriate reactions and stimuli in response to changes in the animal's behavior patterns, and to achieve optimal interactions according to the user's emotional state.

A "spherical, freely movable device" is a device that has a spherical shape and the ability to physically move freely.

An "information terminal" is an electronic device operated by a user, such as a smartphone or tablet.

A "sensor that detects animal movements and behavior patterns" is a device that detects animal movements and behavior in real time and collects that data.

"Generative AI" is artificial intelligence that learns animal behavior patterns based on collected data and generates appropriate reactions and stimuli.

"Means for providing appropriate reactions and stimuli" is a function that provides appropriate reactions and stimuli to animals based on the results of learning by the generative AI.

An "emotion engine" is a system that senses the user's emotional state and adjusts the device's behavior and responses accordingly.

"Means for advising optimal interactions" is a function that provides real-time instructions to users on how best to interact with and play with animals.

A system for implementing this invention has the following configuration:

First, a spherical, freely movable device is required. This device is equipped with sensors that detect the animal's movements and behavior patterns. The sensors detect the animal's movements and behavior in real time and collect that data.

Next, you need an information terminal. An information terminal is an electronic device that users can operate, such as a smartphone or tablet. You can operate the device through this information terminal.

The collected data is analyzed by generative AI, which accumulates data on the animal's behavior over time and learns changes in the animal's behavior patterns based on that accumulated data. This makes it possible to understand the animal's preferences and play styles, and provide appropriate reactions and stimulation.

Furthermore, the emotion engine senses the user's emotional state. The emotion engine adjusts the device's movements and responses according to the user's emotional state. For example, it increases the device's movements when the user is happy, and reduces the device's movements when the user is angry.

Finally, it includes a way to advise users on optimal interactions with animals, allowing them to know in real time how to interact with animals.

For example, if the user types "happy," the system will advise, "Play with your cat more!". Also, if the user types "angry," the system will advise, "Let's give your cat a break."

Examples of prompts are as follows:

Enter the user's emotion (happy, angry, neutral): happy

In this way, it is possible to provide appropriate reactions and stimuli in response to changes in the animal's behavioral patterns, achieving optimal interaction according to the user's emotional state.

The flow of the specific processing in Application Example 3 will be explained using Figure 22.

Step 1:

The user operates the information terminal and starts the device. As input, the user starts the information terminal's application and turns on the device. As output, the device starts operating and the sensor begins to detect animal movement.

Step 2:

Sensors detect animal movements and behavior patterns in real time and collect the data. The animal's movements and behavior are detected by the sensors as input. The collected data is sent to the generative AI as output.

Step 3:

Generative AI analyzes the collected data and learns the animal's behavioral patterns. The input is the animal's behavioral data transmitted from the sensors. The output is the generation of appropriate reactions and stimulus instructions based on changes in the animal's behavioral patterns.

Step 4:

The emotion engine senses the user's emotional state. As input, the user enters their emotional state into the information terminal. As output, the emotion engine analyzes the user's emotional state and sends the results to the generative AI.

Step 5:

The generative AI adjusts the device's movements and responses based on the user's emotional state. The input is data on the user's emotional state sent from the emotion engine. The output is the device's movements and responses adjusted according to the user's emotional state.

Step 6:

Advises the user on optimal interactions with animals. Inputs include instructions from the generative AI and data on the user's emotional state. Outputs include advice on optimal interactions with animals displayed on the information terminal screen.

Step 7:

The user interacts with the animal according to the advice. The input is the advice displayed on the information terminal. The output is that the user's appropriate interaction with the animal changes the animal's behavioral patterns, and the sensor again collects that data.

This series of processing steps makes it possible to provide appropriate reactions and stimuli in response to changes in the animal's behavioral patterns, achieving optimal interaction according to the user's emotional state.

The specific processing unit 290 transmits the results of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the results of the specific processing. The microphone 238 acquires audio indicating the user input regarding the results of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

Data generation model 58 is what is known as generative AI (artificial intelligence). An example of data generation model 58 is generative AI such as ChatGPT (Internet search <URL: https://openai.com/blog/chatgpt>). Data generation model 58 is obtained by performing deep learning on a neural network. A prompt containing an instruction is input to data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. Data generation model 58 performs inference on the input inference data in accordance with the instructions indicated by the prompt, and outputs the inference results in the form of data such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and/or summarization.

Another example of generative AI is Gemini (Internet search <URL: https://gemini.google.com/?hl=ja>).

In the above embodiment, an example was given in which the specific processing was performed by the data processing device 12, but the technology disclosed herein is not limited to this, and the specific processing may also be performed by the smart glasses 214.

[Third embodiment]

Figure 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

As shown in FIG. 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

The data processing device 12 includes a computer 22, a database 24, and a communication I/F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and communication I/F 26 are also connected to the bus 34. The communication I/F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and/or a LAN (Local Area Network).

The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I/F 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user 20's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

The communication I/F 44 is connected to the network 54. The communication I/Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I/Fs 44 and 26 is carried out in a secure manner.

Figure 6 shows an example of the main functions of the data processing device 12 and headset terminal 314. As shown in Figure 6, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32.

The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as the specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

Storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

In the headset terminal 314, the processor 46 performs reception output processing. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

Next, we will explain the identification process performed by the identification processing unit 290 of the data processing device 12.

"Example 1"

One aspect of the present invention provides a spherical device. This device has an internal driving source such as a motor or battery, and is able to move around freely. A sensor is placed on the outside of the device to detect the cat's movements and behavioral patterns. This sensor detects the cat's movements and behavioral patterns and sends the data to a generative AI. The generative AI analyzes the received data and understands the cat's preferences and play styles. Based on this understanding, it then sends instructions to the device to provide the cat with appropriate reactions and stimuli. The device operates in accordance with the instructions and provides the cat with appropriate reactions and stimuli.

"Example 2"

As a specific example, if a cat exhibits aggressive behavior toward the device, a sensor will detect that behavior and send that information to the generative AI. The generative AI will analyze the information and understand that the cat prefers aggressive play. Based on that understanding, it will instruct the device to perform actions that will stimulate the cat. The device will then act in accordance with those instructions and provide the cat with appropriate stimulation.

"Example 3"

In addition, the generative AI accumulates data on the cat's behavior over time and learns changes in the cat's behavior patterns based on that accumulated data. For example, if a cat initially prefers aggressive play but develops a preference for gentler play over time, the generative AI will learn this change and issue appropriate instructions to the device based on that learning. This makes it possible to provide appropriate reactions and stimuli in response to changes in the cat's behavior patterns.

The processing flow for each example form is explained below.

"Example 1"

Step 1: The spherical device starts operating, and the sensors that detect the cat's movements and behavior patterns begin to function.

Step 2: The sensor detects the cat's movements and behavior patterns and sends that data to the generative AI.

Step 3: The generative AI analyzes the received data and understands the cat's preferences and play habits.

Step 4: Based on its understanding, the generative AI sends instructions to the device to provide the cat with appropriate reactions and stimuli.

Step 5: The device acts according to the instructions and provides the cat with the appropriate reaction or stimulus.

"Example 2"

Step 1: The cat exhibits aggressive behavior toward the device.

Step 2: The sensor detects the behavior and sends that information to the generative AI.

Step 3: The generative AI analyzes the information and understands that cats prefer aggressive play.

Step 4: Based on that understanding, the generative AI instructs the device to perform actions that stimulate the cat.

Step 5: The device follows the instructions and provides the appropriate stimulation to the cat.

"Example 3"

Step 1: The generative AI accumulates cat behavior data over time.

Step 2: The generative AI learns changes in the cat's behavioral patterns based on the accumulated data.

Step 3: The generative AI issues appropriate instructions to the device based on its learning.

Step 4: The device operates according to the instructions, providing appropriate reactions and stimuli in response to changes in the cat's behavioral patterns.

(Example 1)

Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Conventional animal play equipment struggled to provide the appropriate reactions and stimulation needed to keep animals interested, resulting in animals quickly becoming bored. Furthermore, the lack of a system capable of analyzing animals' behavioral patterns in real time and controlling their movements accordingly made it difficult to provide play styles tailored to each animal's individual preferences.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavioral patterns, generative artificial intelligence that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the artificial intelligence, means for generating instructions for controlling the operation of the device and sending the instructions to the device, and means for the device to operate in accordance with the instructions and provide appropriate reactions and stimuli to the animal. This makes it possible to analyze the behavioral patterns of animals in real time and provide appropriate reactions and stimuli according to the preferences of each individual animal.

The "device" is a spherical, freely movable device equipped with sensors that detect the movements and behavior patterns of animals.

An "information terminal" is an electronic device that provides a means for operating a device, including smartphones and tablets.

A "sensor" is a device that detects animal movements and behavior patterns and is installed in the device.

"Generative AI" is an artificial intelligence system that analyzes data from sensors and understands animals' preferences and play styles.

"Means for providing reactions and stimuli" refers to mechanisms and methods for providing appropriate reactions and stimuli to animals based on generative artificial intelligence.

"Means for generating instructions" refers to the mechanism or method for generating instructions to control the operation of a device based on data analyzed by generative artificial intelligence.

"Means for sending instructions" refers to communication means for sending the generated instructions to the device.

"Means for controlling behavior" refers to the mechanism or method by which the device operates according to the instructions it receives and provides the animal with an appropriate reaction or stimulus.

This invention is a system that analyzes animal behavior patterns in real time and provides appropriate reactions and stimuli based on the preferences of each individual animal. Specific embodiments of this system are described below.

System Configuration

The system consists of the following main components:

1. Device: A spherical, freely movable device equipped with sensors that detect animal movements and behavior patterns.

2. Information terminal: An electronic device that provides a means for operating a device, including smartphones and tablets.

3. Sensor: A device that detects animal movements and behavior patterns and is installed in the device.

4. Generative AI: An artificial intelligence system that analyzes data from sensors to understand animals' preferences and play styles.

5. Means for providing reactions and stimuli: Mechanisms and methods for providing appropriate reactions and stimuli to animals based on generative artificial intelligence.

6. Means for generating instructions: A mechanism or method for generating instructions to control the operation of a device based on data analyzed by generative artificial intelligence.

7. Means for sending instructions: A communication means for sending the generated instructions to the device.

8. Means for controlling behavior: The mechanism or method by which the device operates according to the instructions it receives and provides the animal with the appropriate reaction or stimulus.

System Operation

1. Initialize the device

The user turns on the device.

The device checks the internal motor and battery to ensure they are working properly.

The device will calibrate the sensors to ensure accurate data collection.

2. Data Collection

The device uses sensors to detect animal movements and behavior patterns in real time.

The device temporarily stores detected data.

3. Data Transmission

The device sends the collected data to the server.

The server receives the data and prepares it for analysis.

4. Data Analysis

The server passes the received data to the generative artificial intelligence.

Generative AI analyzes data to understand animals' preferences and behavioral patterns.

5. Instruction Generation

Based on the analysis results, generative AI generates instructions to provide the animal with appropriate reactions and stimuli.

The server receives the generated instructions.

6. Sending instructions

The server sends the generated instructions to the device.

The terminal receives the instructions and transmits them to the device.

7. Device Operation

The device operates according to the instructions received by the terminal.

The device provides the animal with appropriate reactions and stimuli.

Specific examples

For example, if a cat approaches a device, the device's sensor will detect the movement. The server will determine that the cat is interested in the device and send the data to the generative AI. The generative AI will then generate an instruction to "move the device slightly to attract the cat." The server will then send the instruction to the device, which will then move the device.

Example prompt

"Generate an appropriate reaction when a cat approaches the device."

"If my cat likes to chase the device, what movements should I give it?"

In this way, the system can analyze the animal's behavior in real time and provide appropriate reactions, keeping the animal engaged.

The flow of the identification process in Example 1 will be explained using Figure 11.

Step 1: Initialize your device

Input: The user turns on the device.

Processing: The device checks the internal motors and batteries to ensure they are working properly. It also calibrates the sensors to ensure accurate data collection.

Output: The device is ready to operate normally.

Specific operation: The user presses the device's power button, and the device checks the device's LED indicator to confirm normal operation.

Step 2: Collect data

Input: The device detects animal movements and behavior patterns.

Processing: The device uses its sensors to detect animal movements and behavior patterns in real time and temporarily store the data.

Output: Data on animal movements and behavior patterns is collected.

Specific operation: The device uses a sensor to detect the cat's movement as it approaches the device and stores the data in memory.

Step 3: Send data

Input: Collected animal movement and behavior pattern data.

Processing: The device sends the collected data to the server. The server receives the data and prepares it for analysis.

Output: Data is sent to the server and ready for analysis.

Specific operation: The device sends data to the server via Wi-Fi, and the server receives the data and stores it in a database.

Step 4: Data Analysis

Input: Animal movement and behavior pattern data received by the server.

Processing: The server passes the received data to the generative AI, which analyzes the data to understand the animal's preferences and behavioral patterns.

Output: Analysis results on animal preferences and behavior patterns.

Specific operation: The server inputs data into the generative AI, which then concludes that "cats like to chase balls."

Step 5: Generate instructions

Input: Analysis results from generative artificial intelligence.

Processing: Based on the analysis results, the generative AI generates instructions to provide the animal with appropriate reactions and stimuli. The server receives the generated instructions.

Output: Instructions for providing the appropriate reaction or stimulus to the animal.

Specific operation: The generative artificial intelligence generates the instruction "rotate the device to the right," and the server receives that instruction.

Step 6: Send instructions

Input: Generated instructions.

Processing: The server sends the generated instructions to the terminal, which receives the instructions and transmits them to the device.

Output: Instructions sent to the device.

Specific operation: The server sends instructions to the terminal via Wi-Fi, and the terminal receives the instructions and passes them on to the device.

Step 7: Device Operation

Input: Instructions received by the terminal.

Processing: The terminal operates the device according to the instructions received, providing the animal with the appropriate reaction or stimulus.

Output: The appropriate reaction or stimulus provided to the animal.

Specific behavior: The terminal controls the device's motor and rotates it to the right. The device rotates in front of the cat, and the cat chases it.

(Application Example 1)

Next, we will explain Application Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Existing pet devices struggled to fully understand animals' movements and behavior patterns and provide appropriate reactions and stimuli. Furthermore, physical stores lacked the means to provide a fun environment for animals. This meant that efforts to reduce animal stress and improve customer satisfaction were not fully achieved.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

In this invention, the server includes a spherical device that can move around freely, means for operating the device from a smartphone, a sensor installed in the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and ways of playing, means for providing the animal with appropriate reactions and stimuli based on the AI, and means for the device to detect the animal's movements within the physical store and provide appropriate reactions and play using the generative AI. This allows the animal to have fun within the physical store, improving customer satisfaction.

A "spherical device that can move freely" is a spherical device that has an internal power source such as a motor or battery and can move in any direction.

"Means for operating from a smartphone" refers to interfaces and applications for remotely controlling the operation of a device using a smartphone.

A "sensor that detects animal movements and behavior patterns" is a device that senses the position, speed, direction, and other movements of animals and collects that data.

"Generative AI" is an artificial intelligence model that analyzes collected animal movement and behavior data to understand animals' preferences and play styles.

"Means for providing appropriate reactions and stimuli to animals" refers to a mechanism that allows animals to take appropriate actions or react based on instructions generated by the generative AI.

"Means for detecting animal movements within a physical store and using generative AI to provide appropriate reactions and play" refers to a system that detects animal movements within a physical store in real time, sends that data to generative AI, and provides appropriate reactions and play for the animals.

This invention is a system for providing an environment in a physical store where animals, particularly cats, can have fun. The system includes a spherical, freely moving device, a means for operating it from a smartphone, sensors that detect the animal's movements and behavior patterns, generative AI, and a means for providing the animal with appropriate reactions and stimuli.

System Configuration

1. Spherical device:

It is equipped with a motor and battery inside, allowing it to move in any direction.

Sensors are placed on the exterior to detect animal movement.

2. How to operate from your smartphone:

An application is provided for remotely controlling the device's operation using a smartphone.

3. Sensors that detect animal movements and behavior patterns:

It detects the animal's location, speed, direction, and other movements and collects that data.

4. Generative AI:

Analyze collected animal movement and behavior data to understand animals' preferences and play styles.

Generative AI models are used to generate appropriate reactions and stimuli for animals.

5. How to provide appropriate reactions and stimuli to animals:

The robot will then perform appropriate actions and reactions towards the animal based on the instructions generated by the generative AI.

Program processing explanation

The server sends the animal's movement data collected from the sensors to the generative AI. The generative AI analyzes this data to understand the animal's preferences and play styles. Based on what it understands, it generates instructions to provide the animal with appropriate reactions and stimuli. These instructions are sent to the device, which then performs the appropriate action on the animal.

The hardware used includes sensors to detect animal movement, motors to power the device, and batteries to power the device. The software used includes a generative AI model, a sensor control module, and a motor control module.

Specific examples

For example, when a cat approaches a device in a pet shop, a sensor detects its movement and sends the data to the generative AI. The generative AI then generates movements that will interest the cat and sends those instructions to the device. The device then starts moving as if the cat is chasing it, attracting the cat's interest.

Also, when a cat touches the device in a cafe, a sensor detects the movement and sends the data to the generative AI. The generative AI generates a rotating motion that the cat will enjoy and sends that instruction to the device. The device then rotates in a way that the cat will enjoy, attracting its interest.

Example prompt

"Enter your cat's movement data. This data includes the cat's position, speed, direction, etc. Use this data to generate reactions that will interest your cat."

The above is an embodiment of the invention. This system allows animals to have fun in physical stores, improving customer satisfaction.

The flow of the identification process in Application Example 1 will be explained using Figure 12.

Step 1:

The sensor detects the animal's movement. The sensor collects data such as the animal's position, speed, and direction, and sends that data to the server. The input is the animal's movement data, and the output is the movement data sent to the server.

Step 2:

The server sends the animal's movement data received from the sensors to the generative AI. The generative AI analyzes this data and understands the animal's preferences and play styles. The input is movement data from the sensors, and the output is the analysis results by the generative AI.

Step 3:

The generative AI generates appropriate reactions and stimuli for the animal based on the analysis results. The generative AI generates actions and responses that will interest the animal and sends these instructions to the server. The input is the analysis results of the animal's movement data, and the output is the generated reactions and stimulus instructions.

Step 4:

The server sends the instructions received from the generative AI to the device. The device begins to operate based on the received instructions. The input is the instructions from the generative AI, and the output is the device's operation.

Step 5:

The device provides appropriate reactions and stimuli to the animal. The device responds to the animal's movements and performs actions that the animal enjoys. The input is instructions from the server, and the output is reactions and stimuli to the animal.

Step 6:

The device detects physical stimuli from the animal and feeds that data back to the server. The server then sends this data to the generative AI, where it is stored as animal behavior data. The input is physical stimulus data from the animal, and the output is feedback data for the generative AI.

These are the specific processing steps of this system. The specific actions performed at each step allow animals to have fun in physical stores.

(Example 2)

Next, Example 2 of Form Example 2 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Previous cat devices simply detected a cat's behavior and were unable to provide appropriate stimuli based on the cat's individual behavioral patterns and preferences. They also lacked the functionality to accumulate cat behavior data and learn over time, making it difficult to respond to changes in a cat's behavioral patterns. Furthermore, they lacked the functionality to automatically respond to physical stimuli from the cat and provide feedback on that response. This made it difficult to maintain a cat's interest, and made effective play and training impossible.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

In this invention, the server includes sensor means for detecting the cat's behavior, terminal means for transmitting data from the sensor means to the server, means for analyzing the data using a generative AI model in the server means, device means for providing stimuli to the cat based on instructions from the server means, and terminal means for controlling the device means. This makes it possible to analyze cat behavior data in real time and provide appropriate stimuli based on the individual cat's behavioral patterns and preferences. In addition, by accumulating cat behavior data over time and learning changes in behavioral patterns based on that data, the cat's interest can be sustained. Furthermore, the function of automatically responding to physical stimuli from the cat and providing feedback on that response allows for effective play and training.

"Sensor means" refers to a device for detecting cat behavior, including motion sensors and cameras.

"Terminal means" refers to a device for transmitting data from sensor means to a server, and includes a data transmission module and a communication device.

The "server means" is a device that analyzes the received data using a generative AI model and generates instructions to provide appropriate stimulation to the cat.

A "generative AI model" is an artificial intelligence model that analyzes cat behavior data and generates instructions to provide appropriate stimuli based on the cat's behavioral patterns and preferences.

"Device means" refers to a device for providing stimuli to the cat based on instructions from the server means, and includes a robotic arm, a laser pointer, etc.

"Real-time" means that data is processed immediately the moment it is generated, providing an immediate response without delay.

"Behavioral patterns" refer to the tendencies and habits of a series of behaviors that a cat displays in response to specific situations or stimuli.

"Feedback" refers to the device's means' response to physical stimuli from the cat being sent back to the generative AI model, allowing the generative AI model to learn and generate more appropriate instructions.

This invention is a system that detects cat behavior, analyzes the data, and provides appropriate stimuli to the cat. This system includes sensor means, terminal means, server means, a generative AI model, and device means.

First, the device uses a sensor to detect the cat's behavior. Sensors include motion sensors and cameras. For example, if the cat scratches the device with its claws, this behavior is detected in real time.

The device then transmits the detected behavioral data to a server via a data transmission module. This data includes the cat's movement patterns and location information. For example, it includes the time and location information when the cat scratches the device.

The server inputs the received data into a generative AI model to analyze the cat's behavior. Examples of generative AI models used include OpenAI's GPT-4. The generative AI model determines whether the cat enjoys aggressive play. For example, if the cat frequently exhibits aggressive behavior toward the device, it learns that behavioral pattern.

Then, based on the analysis results, the server instructs the device to perform appropriate actions to stimulate the cat, for example, moving the robotic arm to attract the cat's interest.

Finally, the terminal receives instructions from the server and controls the device to provide appropriate stimuli to the cat, for example, moving a laser pointer to stimulate the cat.

As a concrete example, consider the following scenario: When a cat scratches its claws at the device, the motion sensor detects this movement. The sensor sends this information to the server via the data transmission module. The generative AI model analyzes the data and understands that cats prefer aggressive play. The generative AI model then instructs the robotic arm to perform actions that will attract the cat's interest. The robotic arm operates according to these instructions, providing the cat with appropriate stimuli.

Examples of prompts to input into a generative AI model include:

"Your cat has clawed at the device. Analyze this behavior and determine whether your cat prefers aggressive play. Then instruct the device on the appropriate action to stimulate your cat."

The above is an embodiment of the present invention.

The flow of the identification process in Example 2 will be explained using Figure 13.

Step 1:

The device uses sensor means to detect the cat's behavior. Specifically, motion sensors and cameras monitor the cat's movements in real time and detect aggressive behavior. For example, if the cat digs its claws into the device, this behavior will be detected.

Input: Cat movement

Output: Detected cat behavior data (e.g., time and location of cat claw movements)

Step 2:

The device sends the detected behavioral data to the server via the data transmission module. Specifically, the data obtained from the sensor is packetized and sent to the server via the network.

Input: Detected cat behavior data

Output: Behavioral data sent to the server

Step 3:

The server inputs the received data into a generative AI model to analyze the cat's behavior. Specifically, it inputs behavioral data into a generative AI model (e.g., GPT-4) to determine whether the cat prefers aggressive play.

Input: Behavioral data sent to the server

Output: Analysis of cat behavior patterns (e.g., cats prefer aggressive play)

Step 4:

Based on the analysis results, the server instructs the device on the appropriate actions to stimulate the cat. Specifically, it generates movement instructions for the robot arm and laser pointer based on the analysis results of the generative AI model.

Input: Analysis results of cat behavior patterns

Output: Commands to the device (e.g., moving the robotic arm to attract the cat's attention)

Step 5:

The terminal receives instructions from the server and controls the device to provide appropriate stimuli to the cat. Specifically, it moves the robotic arm and laser pointer to entertain the cat.

Input: Operation instructions from the server

Output: Appropriate stimuli provided to the cat (e.g., robotic arm movement, laser pointer movement)

The above is the specific flow of processing for this system's program.

(Application Example 2)

Next, we will explain Application Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Conventional safety monitoring systems in factories have the drawback of being unable to detect abnormal worker or machine behavior in real time and quickly respond appropriately. Furthermore, systems that understand animal behavior and provide appropriate stimuli are limited, and they are unable to learn changes in animal behavior patterns. To solve these issues, a system is needed that can monitor animal and worker behavior in real time, detect abnormal behavior, and respond appropriately.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

In this invention, the server includes a spherical device that can move around freely, means for operating the device from an information terminal, a sensor installed in the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, a sensor that detects abnormal behavior of workers and machines within the factory, means for transmitting data from the sensor to the generative AI and analyzing the abnormal behavior, and means for instructing an appropriate response based on the analysis results. This makes it possible to learn changes in the animal's behavior patterns and provide appropriate stimuli, as well as detect abnormal behavior of workers and machines within the factory in real time and respond quickly.

A "spherical, freely movable device" is a device that has a spherical shape and the ability to physically move freely.

An "information terminal" is an electronic device used to remotely control devices such as smartphones and tablets.

A "sensor that detects animal movements and behavior patterns" is a device that detects animal movements and behavior in real time and acquires that data.

"Generative AI" is an artificial intelligence system that analyzes acquired data, understands the behavioral patterns of animals and workers, and generates appropriate responses.

"Means for providing appropriate reactions and stimuli to animals" refers to devices and methods for providing appropriate reactions and stimuli to animals based on the analysis results of generative AI.

"Sensors that detect abnormal behavior of workers and machines in factories" are devices that monitor the behavior of workers and machines in factories and detect abnormal behavior in real time.

"Means for analyzing abnormal behavior" refers to a method or device for sending data on detected abnormal behavior to the generative AI and analyzing that data.

"Means for instructing appropriate responses" refers to a method or device for instructing appropriate responses to abnormal behavior based on the analysis results of generative AI.

As an embodiment of this invention, the following system is constructed.

First, a spherical, freely movable device is prepared. This device is equipped with sensors that detect the animal's movements and behavioral patterns. The device can be controlled from an information terminal (e.g., a smartphone or tablet).

Next, a generative AI is prepared. This generative AI analyzes the data obtained from the sensors to understand the animal's preferences and play styles. The generative AI generates instructions to provide the animal with appropriate reactions and stimuli.

In addition, sensors will be installed within the factory to detect abnormal behavior by workers or machines. These sensors will also send data to the generative AI, which will analyze the abnormal behavior. The generative AI will then instruct the appropriate response to the abnormal behavior.

A specific example would be the following system.

1. Animal behavior monitoring system

If an animal exhibits aggressive behavior toward the device, a sensor detects the behavior and sends that information to the generative AI. The generative AI analyzes the information and understands that the animal prefers aggressive play. Based on this understanding, it then instructs the device to perform actions that will stimulate the animal. The device then acts according to those instructions and provides the animal with appropriate stimulation.

2. Factory Safety Monitoring System

If a worker or machine in a factory behaves abnormally, a sensor detects the behavior and sends the data to the generative AI. The generative AI analyzes the data and detects abnormal behavior. If an abnormality is detected, the generative AI will instruct the appropriate response, such as sounding an alarm or halting work.

The hardware used includes sensors to detect animal movement, sensors to detect abnormal behavior within factories, information terminals, and spherical devices. The software used is a generative AI model.

As a concrete example, the following prompt sentence could be input into a generative AI model:

Example prompt:

"Analyze the data when a worker falls, and if an abnormality is detected, issue an instruction to sound an alarm."

In this way, it is possible to learn changes in animal behavior patterns and provide appropriate stimuli, as well as detect abnormal behavior of workers or machinery within the factory in real time and respond quickly.

The flow of the specific processing in Application Example 2 will be explained using Figure 14.

Step 1:

Sensors detect the movement of animals and workers.

Input: Animal and worker movement data

Data processing: Sensors collect operational data in real time and convert it into digital signals.

Output: Digitized motion data

Step 2:

Data obtained from the sensors is sent to the generative AI.

Input: Digitized motion data

Data processing: The data acquired by the sensor is packetized in order to be sent to the generative AI.

Output: Packetized motion data

Step 3:

Generative AI analyzes movement data.

Input: Packetized motion data

Data calculation: Generative AI analyzes movement data to identify abnormal movements and animal behavior patterns.

Output: Analysis results (detection of abnormal behavior and animal behavior patterns)

Step 4:

Generative AI will instruct appropriate responses based on the analysis results.

Input: Analysis results

Data calculation: Based on the analysis results, generative AI determines the appropriate response (e.g., sound an alarm, activate the device, etc.).

Output: Action instructions

Step 5:

Devices and information terminals operate according to the instructions of generative AI.

Input: Response instructions

Specific actions: The device provides appropriate stimuli to the animal, the information terminal sounds an alarm, etc.

Output: Action taken (stimulates animal, sounds alarm, etc.)

Step 6:

The generative AI receives feedback from the results of its actions.

Input: Result of the action performed

Data processing: Generative AI evaluates the execution results and accumulates data to reflect in the next response.

Output: Updated behavioral database

These steps will enable the system to learn changes in animal behavior patterns and provide appropriate stimuli, as well as detect abnormal behavior of workers or machinery within the factory in real time and respond quickly.

(Example 3)

Next, we will explain Example 3 of Form Example 3. In the following explanation, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Previous animal devices struggled to learn an animal's behavioral patterns in real time and provide appropriate reactions and stimuli based on those patterns. Furthermore, there were no systems that could accumulate animal behavioral data over long periods of time and learn from those changes. This made it difficult to provide appropriate reactions and stimuli in response to changes in an animal's behavioral patterns.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

In this invention, the server includes means for storing data from sensors that detect animal movements and behavioral patterns in a database, means for cleansing the stored data and extracting behavioral patterns, means for the generative artificial intelligence to learn changes in behavioral patterns, and means for generating appropriate instructions based on the learning results. This makes it possible to provide appropriate reactions and stimuli in response to changes in the animal's behavioral patterns.

The "device" is a spherical device that can move freely and detects the movements and behavior patterns of animals.

A "personal digital assistant" is a portable electronic device, such as a smartphone or tablet, used to operate the device.

A "sensor" is a sensing device installed in a device to detect animal movements and behavior patterns.

"Generative AI" is AI that analyzes data from sensors, understands animals' preferences and play styles, and provides appropriate reactions and stimuli.

The "database" is an information management system for storing animal behavior data collected from sensors.

"Cleansing" is the process of removing noise from raw data stored in a database and filling in missing data.

A "behavioral pattern" is a series of behaviors that an animal tends to exhibit at a particular time or in a particular situation.

"Learning" is the process by which generative artificial intelligence understands changes in animal behavior patterns based on accumulated data.

"Instructions" are specific operational commands that generative AI issues to a device based on its learning results.

"Reactions" are specific actions or stimuli that the device performs on the animal in accordance with instructions from the generative artificial intelligence.

This invention is a system that learns animal behavior patterns in real time and provides appropriate reactions and stimuli based on those patterns. Specific embodiments of this system are described below.

Hardware and software used

Hardware: Sensors (cameras, microphones, etc.) that detect animal movements and behavior patterns, a spherical device that can move freely, and a mobile information terminal (smartphone or tablet)

Software: Generative AI (e.g., OpenAI's GPT-4), databases (MySQL and MongoDB)

System Configuration

1. Device:

It is equipped with sensors to detect animal movements and behavior patterns.

Data from sensors is collected in real time and sent to a server.

2. Mobile Information Devices:

Used as a means to operate the device.

Users can control the device's operation through their mobile information terminal.

3. Server:

Receives data sent from sensors and stores it in a database.

Clean the accumulated data and extract behavioral patterns.

Uses generative artificial intelligence to learn changes in behavioral patterns.

Based on the learning results, appropriate instructions are generated for the device.

Specific examples

For example, consider a situation where a cat initially prefers aggressive play, but over time begins to prefer gentle play.

1. Data Collection:

The device (camera) captures the cat poking at the toy as it moves vigorously.

The server receives the video data and stores it in a database.

2. Data preprocessing:

The server removes unnecessary parts from the video data and extracts only the cat's movements.

The server organizes the extracted data by time and analyzes the cat's behavioral patterns.

3. Learning behavioral patterns:

The server uses generative artificial intelligence to learn when the cat has changed from aggressive to calm play.

The server saves the learning results and proceeds to the next step.

4. Generating appropriate instructions:

The server inputs a prompt to the generative AI: "Since the cat has started to prefer gentle play, please generate instructions to move a toy with gentle movements."

The server sends the generated instructions to the device.

5. Providing Reactions:

The device (toy) makes gentle movements according to instructions received from the server.

The device provides gentle play for your cat and responds to your cat's behavioral patterns.

Example prompt

By inputting the following prompt sentence into the generative artificial intelligence, instructions based on changes in the cat's behavioral patterns can be generated.

Behavioral data for a cat is shown below. At first, the cat preferred aggressive play, but over time, it began to prefer gentle play. Based on this change, generate instructions to provide the cat with appropriate reactions and stimuli.

In this way, the system is able to provide appropriate reactions and stimuli in response to changes in the animal's behavioral patterns. The flow of the identification process in Example 3 will be explained using Figure 15.

Step 1: Data Collection

The device (sensor) monitors the animal's movements in real time and collects behavioral data. For example, a camera captures a cat's movements and a microphone records the cat's meows.

Input: Real-time animal movements and sounds

Output: Animal behavior data (video and audio data)

Specific operation: The camera captures the cat's movements, and the microphone records the cat's meows. The device collects this data and sends it to the server.

Step 2: Data preprocessing

The server cleanses the raw data stored in the database. Specifically, it removes noise and fills in missing data.

Input: Raw data (video data, audio data)

Output: Cleansed data

Specific operation: The server removes unnecessary parts from the video data and filters noise from the audio data. Any missing data is filled in.

Step 3: Extracting behavioral patterns

The server organizes the cleansed data by time and extracts behavioral patterns.

Input: Cleansed data

Output: Behavioral pattern data

Specific operation: The server analyzes the cleansed data and extracts information about the animal's behavior at specific times of the day.

Step 4: Learning behavioral patterns

The server uses a generative AI model to learn animal behavior patterns based on accumulated data.

Input: Behavioral pattern data

Output: Learning results (changes in behavioral patterns)

Specific operation: The server inputs behavioral pattern data into the generative AI model, which then learns changes in the animal's behavior. For example, it learns that a cat has changed from aggressive play to calm play.

Step 5: Generate appropriate instructions

The server generates appropriate instructions for the device based on the learning results.

Input: Learning results

Output: Instruction data

Specific behavior: The server inputs a prompt to the generative AI model: "Since the cat has started to prefer gentle play, please generate instructions to move a toy with gentle movements," and sends the generated instructions to the device.

Step 6: Provide a reaction

The terminal (device) operates according to the instructions received from the server.

Input: Instruction data

Output: Reaction to animals

Specific action: The device activates a toy with gentle movements, providing gentle play for the cat.

(Application Example 3)

Next, we will explain Application Example 3 of Configuration Example 3. In the following explanation, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Conventional animal devices and generative AI were limited to learning animal behavior patterns and providing appropriate reactions. However, there were no systems that could learn the behavior patterns of workers in factories and provide appropriate support. As a result, improvements in work efficiency and reductions in worker burden were not fully achieved. Therefore, there is a need for a system that can learn the behavior patterns of workers in factories and provide appropriate support.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

In this invention, the server includes a spherical device that can move around freely, means for operating the device from a smartphone, a sensor installed in the device that detects the animal's movements and behavioral patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and behavioral patterns, means for providing appropriate reactions and stimuli to the animal based on the AI, and means for accumulating worker behavioral data over time, learning changes in behavioral patterns based on the accumulated data, and providing appropriate support. This makes it possible to learn the behavioral patterns of workers within the factory and provide appropriate support.

A "spherical, freely movable device" is a device that has a spherical shape and the ability to physically move freely.

"Means for operating from a smartphone" refers to the interface or software for remotely operating a device using a smartphone.

A "sensor that detects animal movements and behavior patterns" is a device that detects animal movements and behavior in real time and collects that data.

"Generative AI" is an artificial intelligence technology that learns the behavioral patterns of animals and workers based on collected data and provides appropriate reactions and support.

"Means for providing appropriate reactions and stimuli" refers to devices or functions that provide appropriate reactions and stimuli to animals and workers based on the results of learning by the generative AI.

"Means for accumulating worker behavioral data over time" refers to a system that continuously records worker behavior and stores that data for long periods of time.

"Means of learning changes in behavioral patterns and providing appropriate support" is a function that analyzes accumulated behavioral data, recognizes changes in behavioral patterns, and provides optimal support to workers.

The following hardware and software are required to implement this invention. Hardware requires a spherical, freely movable device, a smartphone, a factory robot, and sensors. Software requires Python, scikit-learn, and a generative AI model.

First, the spherical, freely movable device is equipped with sensors that detect the behavior of animals and workers in real time. These sensors detect the movements and behavioral patterns of animals and workers and collect that data. The collected data is sent to a generative AI model for analysis.

The generative AI model learns the behavioral patterns of animals and workers based on collected data. This learning process uses Python and scikit-learn. Specifically, it uses the KMeans clustering algorithm to classify behavioral patterns and learns how behavioral patterns change over time.

Once learning is complete, the generative AI model will provide instructions for providing appropriate reactions and stimuli to animals and workers. For example, if an animal prefers aggressive play, the device will provide appropriate stimuli. Also, if a worker transitions from manual to automated tasks, the robot will provide appropriate support.

For example, if a worker is manually assembling parts in a factory, a robot will help carry the parts. Also, if a worker is operating automated machinery, a robot will help with machine maintenance.

Examples of prompt statements include:

"Develop AI that collects data on worker behavior in factories and learns changes in behavioral patterns based on that data. For example, when workers transition from manual to automated tasks, create a robot that learns this change and provides appropriate support."

In this way, this invention can improve work efficiency within factories and reduce the burden on workers.

The flow of the specific processing in Application Example 3 will be explained using Figure 16.

Step 1:

The server uses sensors to collect behavioral data of animals and workers. The input is real-time behavioral data obtained from the sensors, and the output is a list of collected behavioral data. Specifically, the sensors detect the movements of animals and workers and send that data to the server.

Step 2:

The server accumulates the collected behavioral data. The input is the behavioral data collected in step 1, and the output is a database of accumulated behavioral data. Specifically, the server saves the data it receives in the database.

Step 3:

The server uses the accumulated behavioral data to train a generative AI model. The input is the accumulated behavioral data, and the output is the trained generative AI model. Specifically, the server uses Python and scikit-learn to run the KMeans clustering algorithm and classify behavioral patterns.

Step 4:

When new behavioral data is input, the server uses a generative AI model to predict behavioral patterns. The input is the new behavioral data, and the output is the predicted behavioral pattern. Specifically, the server inputs the new data into the generative AI model and obtains the predicted results.

Step 5:

The server issues instructions to provide appropriate reactions and support based on the prediction results. The input is the predicted behavior pattern, and the output is instructions for reactions and support. In terms of specific operations, the server instructs the device or robot to perform the appropriate action.

Step 6:

The terminal (smartphone) receives instructions from the server and operates the device or robot. The input is the instruction from the server, and the output is the operation of the device or robot. Specifically, the smartphone sends operation commands to the device or robot.

Step 7:

The user monitors the operation of the device or robot and operates it manually as necessary. The input is the operating status of the device or robot, and the output is the user's operation commands. Specifically, the user manually operates the device or robot using a smartphone.

It is also possible to further combine an emotion engine that estimates the user's emotion. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

"Example 1"

One embodiment of the present invention provides a system that incorporates an emotion engine. This system recognizes the user's emotions and adjusts the reactions and stimuli given to the cat according to those emotions. Specifically, when the user is happy, the system encourages the cat to play actively. Conversely, when the user is depressed, the system encourages the cat to play quietly. This enables optimal interaction with the cat according to the user's emotional state.

"Example 2"

The emotion engine also recognizes emotions from the user's tone of voice, facial expressions, or physical reactions. For example, if the user is smiling, the system will recognize that the user is happy and encourage the cat to play actively. Conversely, if the user is crying, the system will recognize that the user is sad and encourage the cat to play quietly. This allows for a more accurate understanding of the user's emotional state and optimal interaction with the cat accordingly.

"Example 3"

Furthermore, the emotion engine adjusts the device's movements and reactions according to the user's emotions, improving the interaction between the user and the cat. For example, when the user is angry, the system suppresses the device's movements to prevent the cat from bothering the user. Conversely, when the user is happy, the system activates the device's movements to allow the cat to play happily with the user. This enables optimal interaction with the cat according to the user's emotional state.

The processing flow for each example form is explained below.

"Example 1"

Step 1: The user's emotion engine recognizes the user's emotion.

Step 2: Based on the recognized emotion, the system adjusts its reactions and stimuli to the cat.

Step 3: When the user is happy, the system encourages active play with the cat.

Step 4: When the user is feeling down, the system encourages quiet play with the cat.

"Example 2"

Step 1: The emotion engine recognizes emotions from the user's tone of voice, facial expressions, or physical reactions.

Step 2: If the user is smiling, the system recognizes that the user is happy and encourages active play with the cat.

Step 3: If the user is crying, the system recognizes that the user is sad and prompts the cat to play quietly.

"Example 3"

Step 1: The emotion engine recognizes the user's emotions.

Step 2: Adjust the device's movements and responses based on the user's emotions.

Step 3: When the user is angry, the system inhibits the device's movement to prevent the cat from bothering the user.

Step 4: When the user is happy, the system activates the device's activity, allowing the cat to play happily with the user.

(Example 1)

Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Previous animal devices simply detected animal movements and behavioral patterns, but were unable to understand the animal's preferences and play styles and provide appropriate reactions or stimulation. Furthermore, they lacked the ability to adjust interactions with the animal based on the user's emotional state, making it difficult to deepen the relationship between the user and the animal.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, and an emotion engine that recognizes the user's emotions and adjusts the reactions and stimuli to the animal according to those emotions. This makes it possible to understand the animal's behavior patterns and provide optimal reactions and stimuli according to the user's emotional state.

A "device" is a spherical piece of equipment that can move freely.

An "information terminal" is an electronic device that provides a means for operating a device.

A "sensor" is a device used to detect animal movements and behavior patterns.

"Generative AI" is artificial intelligence that analyzes data from sensors and understands animals' preferences and play styles.

"Means for providing reactions and stimuli" refers to a mechanism for providing appropriate reactions and stimuli to animals based on the analysis results of the generative AI.

The "emotion engine" is a system that recognizes the user's emotions and adjusts the reactions and stimuli given to animals based on those emotions.

"Animal behavior data" is information about animal movements and behavior patterns.

"Feedback" is the process of returning the device's response to physical stimuli from the animal to the generative AI.

This invention is a system that understands animal behavior patterns and provides optimal reactions and stimuli according to the user's emotional state. Specific embodiments of this system are described below.

Hardware and software used

Device: A spherical device that can move freely. It is equipped with motors, batteries, and sensors.

Information terminal: An electronic device that provides a means for operating a device. Examples include smartphones and tablets.

Sensor: A device used to detect animal movements and behavior patterns. Accelerometers and infrared sensors are used.

Generative AI: Artificial intelligence that analyzes data from sensors to understand animals' preferences and play styles. It uses AI models that run on the cloud.

Emotion engine: A system that recognizes the user's emotions and adjusts the animal's reactions and stimuli accordingly. Emotion recognition software is used.

Program processing

The server receives the animal's behavioral data sent from the device and inputs it into the generative AI. The generative AI analyzes the received data to understand the animal's preferences and play styles. Based on the analysis results, the generative AI then generates instructions to provide the animal with appropriate reactions and stimuli, and sends these to the device.

The device collects data to recognize the user's emotions. For example, it uses the smartphone's camera and microphone to analyze the user's facial expressions and tone of voice. The emotion engine receives the user's emotional data and adjusts the animal's reactions and stimuli according to those emotions.

Specific examples

Example 1: When a cat approaches the device, the sensor detects its movement and sends the data to the server. The server uses a generative AI model to determine that the cat is interested and sends the device an instruction to "rotate to attract the cat's attention." The device then begins to rotate in place.

Example 2: When a user is using a smartphone, the device captures the user's facial expression with its camera, and the emotion engine recognizes that the user is happy. The server then sends instructions to the generative AI model to encourage active play, causing the device to act as if it were running around with a cat.

Example prompt

"Please explain what happens when a cat approaches the device."

"Please explain how users react to cats when they are happy."

The above is a specific form for implementing this invention. This system makes it possible to understand animal behavior patterns and provide optimal reactions and stimuli according to the user's emotional state.

The flow of the identification process in Example 1 will be explained using Figure 17.

Step 1:

Initializing the device

Server: Initializes the device. Checks the status of the motor and battery, and ensures that sensors are working properly.

Input: The signal that powers on the device.

Output: Signal that initialization is complete.

Specific operation: When the device is turned on, the server checks the status of each component of the device and, if everything is normal, sends a signal indicating initialization is complete.

Step 2:

Cat movement detection

Device: Uses internal sensors to detect your cat's movements and behavior patterns in real time.

Input: Cat movements and behavior.

Output: Detection data.

Specific behavior: When a cat approaches or touches the device, the sensor detects the movement and collects data.

Step 3:

Data transmission

Device: Sends detected data to the server.

Input: Detection data.

Output: Send data to the server.

Specific operation: The data collected by the sensor is sent to the server via wireless communication.

Step 4:

Data analysis

Server: Inputs the received data into a generative AI model to analyze the cat's behavioral patterns and preferences.

Input: Detection data.

Output: Behavioral pattern analysis results.

Specific operation: The server inputs the data "a cat touched the device" into the generated AI model, and the AI determines that "the cat is showing interest."

Step 5:

Generating instructions

Server: Based on the analysis results, generates instructions to provide the cat with appropriate reactions and stimuli.

Input: Behavioral pattern analysis results.

Output: Instructions to the device.

Specific operation: The server generates an instruction to "rotate the device to attract the cat's attention" and sends it to the device.

Step 6:

Device Operation

Device: Operates according to instructions from the server and provides appropriate reactions and stimuli to the cat.

Input: Instructions from the server.

Output: Device operation.

Specific action: The device will start to rotate and act in a way that will attract the cat's interest.

Step 7:

User emotion recognition

Device: Collect data to recognize the user's emotions. For example, use the smartphone's camera and microphone.

Input: User's facial expression and tone of voice.

Output: Emotion data.

Specific operation: The device analyzes the user's facial expressions and tone of voice to recognize their emotional state.

Step 8:

Adjusting instructions based on emotions

Server: Receives the user's emotional data and adjusts the cat's reactions and stimuli.

Input: Emotion data.

Output: Adjusted instructions.

Specific behavior: If the server recognizes that the user is happy, it sends instructions to the generative AI model to encourage active play. The device then behaves as if it is running around with a cat.

(Application Example 1)

Next, we will explain Application Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Previous pet devices simply detected animal behavior patterns and were unable to deeply understand the animal's preferences or play styles. Furthermore, they lacked the ability to adjust interactions with the animal based on the user's emotional state, making it difficult to provide interactions with the pet that best fit the user's emotional state. Furthermore, they lacked a way to control the device or display animal behavior data in real time, making it difficult for users to understand the device's operating status and the animal's behavior.

The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavioral patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, means for recognizing the user's emotional state using an emotion engine and adjusting the reactions and stimuli provided to the animal in accordance with the emotional state, and means for displaying the device's operation and the animal's behavioral data on the information terminal. This makes it possible to deeply understand the animal's behavioral patterns and provide optimal interactions with the pet in accordance with the user's emotional state.

A "spherical device capable of moving freely" is a spherical device that has an internal motor and battery and can move autonomously based on external instructions.

An "information terminal" is an electronic device, such as a smartphone or tablet, that is operated by the user to control the device.

A "sensor that detects animal movements and behavior patterns" is a device that detects an animal's location, speed, movements, etc. in real time and collects that data.

"Generative AI" is an artificial intelligence system that analyzes collected data and understands animals' preferences and play styles.

The "emotion engine" is a system that recognizes the user's emotional state and adjusts interactions with animals based on that information.

"Means for providing appropriate reactions and stimuli to animals" refers to a mechanism that allows appropriate actions and reactions to be taken by animals based on the analysis results of the generative AI.

"Means for displaying the device's operation and animal behavior data on an information terminal" refers to a function for displaying the device's operating status and animal behavior data on an information terminal in real time.

A system for implementing this invention includes a spherical, freely movable device, an information terminal, a sensor that detects animal movements and behavior patterns, a generative AI, an emotion engine, and a means for displaying on the information terminal.

System Configuration

1. Spherical device:

It is equipped with a motor and battery inside and moves autonomously based on external instructions.

Equipped with sensors to detect animal movements and behavior patterns.

2. Information terminal:

Electronic devices operated by users, such as smartphones and tablets.

Displays device operation and animal behavior data in real time.

3. Sensor:

It detects animals' location, speed, movements, etc. in real time and collects that data.

4. Generative AI:

Analyze the collected data to understand the animals' preferences and play styles.

Generative AI models are used to generate instructions to provide appropriate reactions and stimuli to animals.

5. Emotion Engine:

Recognizes the user's emotional state and adjusts interactions with animals based on that information.

6. Display means:

Device operating status and animal behavior data are displayed on the information terminal.

Program processing explanation

The server first collects animal behavior data from sensors. This data is sent to the generative AI, which analyzes the animal's preferences and play styles. Based on the analysis results, the generative AI generates instructions to provide the animal with appropriate reactions and stimuli. Furthermore, an emotion engine recognizes the user's emotional state and adjusts interactions with the animal based on that information. Finally, device operations and animal behavior data are displayed in real time on the information terminal.

Specific examples

For example, if this system were used in a pet shop, when a customer was playing with a cat, the smartphone app would analyze the cat's behavior in real time and adjust how the customer interacted with the cat depending on the customer's emotional state. An example of a prompt sentence to be input into the generative AI model is as follows:

Example prompt:

Cat behavior data: Movement: Active, Play style: Chasing a ball

User's emotional state: State: Happy

Based on this data, generate instructions to provide appropriate reactions and stimuli for your cat.

By inputting this prompt into a generative AI model, we can obtain appropriate reactions and stimulation instructions for the cat.

The flow of the specific processing in Application Example 1 is explained using Figure 18.

Step 1:

The server obtains animal behavior data from sensors. The sensors detect the animal's position, speed, movement, etc. in real time and send the data to the server. The input is raw data from the sensors, and the output is the animal's behavior data sent to the server.

Step 2:

The server sends the acquired animal behavior data to the generative AI. The generative AI analyzes the received data and understands the animal's preferences and play styles. The input is the animal's behavior data, and the output is the analysis results regarding the animal's preferences and play styles.

Step 3:

The server generates instructions to provide appropriate reactions and stimuli to the animal based on the analysis results from the generative AI. It uses the generative AI model to create prompts and generate specific instructions for the animal. The input is the analysis results of the generative AI, and the output is instructions for the animal.

Step 4:

The server uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes data such as the user's facial expressions and voice to identify the user's emotional state. The input is the user's emotional data, and the output is the user's emotional state.

Step 5:

The server adjusts the reactions and stimuli given to the animal based on the user's emotional state. Based on the output of the emotion engine, it modifies the instructions of the generative AI to provide optimal interaction. The input is the user's emotional state and the instructions of the generative AI, and the output is the adjusted instructions given to the animal.

Step 6:

The server sends the adjusted instructions to the spherical device. The device acts based on the received instructions and provides the animal with an appropriate reaction or stimulus. The input is the adjusted instructions, and the output is the device's behavior.

Step 7:

The terminal displays device operation and animal behavior data in real time. Users can check the device's operating status and the animal's behavior through the information terminal. The input is device operation data and animal behavior data, and the output is the information displayed on the information terminal.

(Example 2)

Next, Example 2 of Form Example 2 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Previous animal devices struggled to provide appropriate responses to animal behavior and were unable to realize interactions that took the user's emotional state into account. This made it difficult to provide an optimal experience for both the animal and the user. Furthermore, there was a lack of systems that could learn changes in the animal's behavioral patterns and adapt over the long term.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

In this invention, the server includes means for operating a spherical, freely mobile device, means for using sensors to detect the animal's movements and behavioral patterns, means for using generative AI to analyze data from the sensors and understand the animal's preferences and play styles, means for using an emotion engine to recognize the user's emotional state, and means for optimizing interactions with the animal based on the generative AI and emotion engine. This makes it possible to provide appropriate responses to the animal's behavior and enable interactions that take the user's emotional state into consideration. It also makes it possible to learn changes in the animal's behavioral patterns and adapt over the long term.

A "device" is a spherical piece of equipment that can move freely.

An "information terminal" is an electronic device that provides a means for operating a device.

A "sensor" is a device that detects animal movements and behavior patterns.

"Generative AI" is artificial intelligence that analyzes data from sensors and understands animals' preferences and how they play.

An "emotion engine" is software or hardware that recognizes the user's emotional state.

"Reactions" are appropriate responses or stimuli provided to animals based on generative AI.

"Interaction optimization" refers to optimizing the interaction between animals and users based on generative AI and an emotion engine.

"Behavioral data" is information about animal movements and behavior patterns.

"Feedback" means that the device automatically responds to physical stimuli from the animal and transmits that response to the generative AI.

This invention is a system that provides optimal interaction based on the animal's behavior and the user's emotional state. Specific embodiments of this system are described below.

Hardware and software used

Device: A spherical, freely movable device that provides physical responses to the animal's behavior.

Information terminal: An electronic device that provides a means for operating a device. Examples include smartphones and tablets.

Sensor: A device that detects animal movements and behavior patterns. It is installed in the device and collects data in real time.

Generative AI: Artificial intelligence that analyzes data from sensors to understand animals' preferences and play styles. An example of this is OpenAI's GPT-4.

Emotion engine: Software or hardware that recognizes the user's emotional state. It analyzes the user's tone of voice, facial expressions, or physical reactions.

System Operation

The server receives the animal's behavior data sent from the sensor and analyzes it using generative AI. The generative AI understands the animal's behavioral patterns and sends instructions to the device to provide appropriate reactions and stimuli.

Furthermore, the server uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes the user's tone of voice and facial expressions to determine whether the user is happy or sad. The server optimizes interactions with the animal based on this emotional state.

Specific examples

For example, if a cat scratches the device, the sensor detects the action. The sensor sends the data to a server, which analyzes the data using generative AI. The generative AI understands that the cat prefers aggressive play and instructs the device to move a cat toy. The device follows this instruction to move the cat toy and provide the cat with the appropriate stimulation.

At the same time, the server uses its emotion engine to recognize the user's smile and determine that the user is happy. The server then encourages the cat to play actively depending on the user's emotional state.

Example prompt

"What should I do if my cat is acting aggressively towards my device?"

"Please tell me what kind of play should I encourage the cat to do when the user is smiling?"

This system enables optimal interaction based on the emotional state of the animal and the user.

The flow of the identification process in Example 2 will be explained using Figure 19.

Step 1:

Data collection using sensors

The server monitors the animal's behavior in real time using sensors installed on the device. The sensors detect any aggressive behavior from the animal toward the device. For example, if a cat digs its claws into the device, the sensor detects this behavior. The input is the animal's behavior data, and the output is the detected behavior data.

Step 2:

Data transmission

The sensor sends the detected behavioral data to the server. The server receives this data and passes it on to the generative AI. The input is the behavioral data sent from the sensor, and the output is the behavioral data sent to the server.

Step 3:

Analysis using generative AI

The server uses generative AI to analyze the behavioral data it receives. The generative AI uses, for example, OpenAI's GPT-4, to understand that animals prefer aggressive play. Specifically, it analyzes the behavioral data and determines that the behavior constitutes aggressive play. The input is the behavioral data sent to the server, and the output is the analysis results.

Step 4:

Device instructions

The server issues instructions to the device based on the analysis results of the generative AI. For example, it instructs the device to move a cat toy. The device follows this instruction to move the cat toy and provide the cat with appropriate stimulation. The input is the analysis results of the generative AI, and the output is the instruction to the device.

Step 5:

Recognize user emotions using an emotion engine

The server uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's tone of voice, facial expressions, or physical reactions. For example, if the user is smiling, the emotion engine recognizes that the user is happy. The input is the user's emotion data, and the output is the emotion recognition result.

Step 6:

Cat interaction optimization

The server optimizes interactions with animals according to the user's emotional state. For example, if the user is smiling, it encourages the animal to play actively. Conversely, if the user is crying, it encourages the animal to play quietly. This allows for optimal interaction with animals according to the user's emotional state. The input is the emotion recognition result, and the output is instructions for optimized interactions.

(Application Example 2)

Next, we will explain Application Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Previous pet devices struggled to provide interactions that fully took into account the animal's behavior and the user's emotional state. Furthermore, they lacked a means to provide appropriate stimuli based on the animal's behavioral patterns and the user's emotions, making it difficult to increase satisfaction for both the pet and the user.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing the animal with appropriate reactions and stimuli based on the AI, an emotion engine that recognizes the user's emotional state, and means for adjusting interactions with the animal based on the emotion engine. This enables appropriate interactions that take into account the animal's behavior and the user's emotional state in real time.

A "spherical, freely movable device" is a device that has a spherical shape and can physically move freely.

An "information terminal" is an electronic device operated by a user, such as a smartphone or tablet.

A "sensor that detects animal movements and behavior patterns" is a device that detects animal movements and behavior in real time.

"Generative AI" is an artificial intelligence system that analyzes collected data and understands animals' preferences and behavioral patterns.

"Means for providing appropriate reactions and stimuli" refers to devices and methods for providing appropriate reactions and stimuli to animals based on the analysis results of the generative AI.

The "emotion engine" is a system that recognizes emotions from the user's tone of voice, facial expressions, and physical reactions.

"Means for adjusting interactions with animals" refers to devices and methods for optimizing interactions with animals based on the recognition results of the emotion engine.

This invention is a system that takes into account the animal's behavior and the user's emotional state in real time to provide appropriate interaction. Below, we will show a specific embodiment for realizing this system.

System Configuration

The system consists of the following main components:

1. A spherical, freely movable device:

This device is a spherical device that can be moved freely to induce animal behavior. It is equipped with a motor and battery inside and operates according to instructions from an information terminal.

2. Information terminal:

Electronic devices such as smartphones and tablets that provide an interface for users to operate the device. Dedicated applications are installed on them to control the device's operation.

3. Sensors that detect animal movements and behavior patterns:

The device is equipped with a camera and accelerometer to detect animal movements and behavior in real time.

4. Generation AI:

It is an artificial intelligence system that analyzes collected data to understand animals' preferences and behavioral patterns. Generative AI accumulates animal behavioral data over time and learns changes in behavioral patterns based on that data.

5. How to provide appropriate reactions and stimuli:

This is a device or method for providing appropriate responses or stimuli to animals based on the analysis results of generative AI. For example, the device may stimulate the animal by making specific movements.

6. Emotion Engine:

This is a system that recognizes emotions from the user's tone of voice, facial expressions, and physical reactions. The emotion engine detects the user's emotional state in real time through the camera and microphone.

7. Ways to regulate interactions with animals:

An apparatus and method for optimizing interactions with animals based on the recognition results of an emotion engine. For example, if the user is recognized as sad, the device will behave calmly.

Program processing explanation

The server detects the user's emotional state through a camera and microphone and sends it to the generative AI. The generative AI analyzes the animal's behavioral data and the user's emotional data to determine an appropriate reaction. The information terminal receives instructions from the generative AI and instructs the device on how to act.

The hardware used includes a camera (to detect animal behavior and the user's facial expressions), a microphone (to detect the user's tone of voice), and a motor (to control the device's movement). The software includes OpenCV (image processing), Keras (emotion recognition model), and requests (communication with AI services).

Specific examples

For example, if a user comes into the store with a smiling face and a pet, the emotion engine will recognize that the user is happy. The generative AI will analyze the animal's behavioral data and the user's emotional data and instruct the device to behave in a way that encourages active play. Conversely, if the user looks sad, the device will be instructed to behave calmly.

Example prompt

"If the user's emotion is 'happy' and the animal's behavior is 'aggressive,' we will provide a toy that encourages active play with the animal."

The flow of the specific processing in Application Example 2 is explained using Figure 20.

Step 1:

The server captures the user's facial expressions and tone of voice in real time through a camera and microphone. It receives camera footage and audio data as input. It preprocesses this data using OpenCV and audio processing libraries to extract the user's facial features and tone of voice. It generates data indicating the user's emotional state as output.

Step 2:

The server uses an emotion engine to analyze the user's emotional state data obtained in step 1. It uses facial feature points and voice tone data as input. The emotion engine inputs this data into an emotion recognition model (using Keras) and classifies the user's emotions into categories such as "happy" or "sad." As an output, it generates a label indicating the user's emotional state.

Step 3:

The terminal acquires animal behavior data in real time through sensors installed on the device. As input, it receives data from the sensors (acceleration, location information, etc.). It preprocesses this data to extract the animal's movements and behavioral patterns. As output, it generates data indicating the animal's behavioral state.

Step 4:

The server uses generative AI to integrate and analyze the user's emotional state data obtained in step 2 and the animal's behavior data obtained in step 3. The user's emotional state data and the animal's behavior data are used as input. The generative AI determines appropriate reactions and stimuli for the animal based on this data. As output, it generates operational instructions for the device.

Step 5:

The terminal sends the operation instructions generated in step 4 to the device. As input, it receives operation instruction data from the generative AI. The terminal transmits these instructions to the device's motor control system, controlling the device to perform the appropriate operation. As output, the device's physical operation is executed.

Step 6:

The device automatically responds to physical stimuli from the animal and feeds that response back to the generative AI as animal behavior data. As input, it receives physical stimulus data from the animal. The device detects this data with sensors and sends it to the generative AI. As output, the animal's behavior data is updated.

Step 7:

The server re-analyzes the animal's behavior data updated in step 6 and learns changes in the animal's behavior patterns. It uses the updated animal's behavior data as input. The generative AI accumulates this data and learns changes in the animal's behavior patterns. As output, it generates new movement instructions based on the animal's behavior patterns.

(Example 3)

Next, we will explain Example 3 of Form Example 3. In the following explanation, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Previous animal devices struggled to provide appropriate reactions and stimuli based on the animal's behavioral patterns and the user's emotional state. Furthermore, they lacked the ability to accumulate animal behavioral data over time and learn from changes in that data, making it impossible to respond appropriately to the animal's interests and preferences. Furthermore, the device's movements and responses were not adjusted to take the user's emotional state into account, resulting in suboptimal interactions between the user and the animal.

The specific processing by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means. In this invention, the server includes a spherical device that can move freely around, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, an emotion engine for analyzing the user's emotional state, and means for adjusting the device's movements and reactions based on the analysis results of the emotion engine. This makes it possible to provide appropriate reactions and stimuli in response to changes in the animal's behavior patterns, enabling optimal interaction according to the user's emotional state.

A "device" is a spherical piece of equipment that can move freely.

An "information terminal" is an electronic device that provides a means for operating a device.

A "sensor" is a device used to detect animal movements and behavior patterns.

"Generative AI" is artificial intelligence that analyzes data from sensors and understands animals' preferences and how they play.

An "emotion engine" is software or hardware for analyzing a user's emotional state.

A "reaction" is an appropriate response or stimulus provided to an animal.

"Animal behavior data" is information about animal movements and behavior patterns.

"User's emotional state" refers to the emotional state the user is feeling.

This invention is a system that analyzes animal behavior data and the user's emotional state to provide optimal interaction. A specific embodiment of this system is described below.

System Configuration

The system consists of the following main components:

1. Device: A spherical, freely movable device. The device is equipped with sensors to detect animal movements and behavior patterns.

2. Information terminal: An electronic device that provides a means for operating a device. Examples include smartphones and tablets.

3. Server: The central component that receives and analyzes data from devices and information terminals.

4. Generative AI: Artificial intelligence that analyzes data from sensors and understands animals' preferences and play styles.

5. Emotion engine: Software or hardware for analyzing the user's emotional state.

Data collection and analysis

The server collects animal behavior data from sensors installed on the device. For example, a camera tracks a cat's movements and a sensor detects which objects the cat touches. The collected data is stored in a database.

Generative AI analyzes accumulated behavioral data and learns the behavioral patterns of animals. For example, it learns that cats become active at 8am every morning and that they prefer certain toys. Based on this learning, it issues appropriate instructions to the device.

User sentiment analysis and device adjustment

The device uses a camera and microphone to analyze the user's emotional state. For example, it analyzes the user's facial expressions and tone of voice to determine whether the user is angry or happy.

The server adjusts the device's movements and reactions based on the analysis results of the emotion engine. For example, when the user is angry, the device's movements will be suppressed so that the animal can remain quiet. Conversely, when the user is happy, the device's movements will be more active so that the user can play with the animal.

Specific examples

For example, if a cat initially likes chasing laser pointers, but after a few weeks starts to prefer rolling a ball, the generative AI will learn this change and instruct it to move the ball-rolling device more frequently.

Also, when the user comes home from work and is tired, the emotion engine detects the user's fatigue and reduces the device's activity so that the cat can stay quiet. Conversely, when the user is relaxing on a day off, the device's activity will be more active so that the user can play with the cat.

Example prompt

"Please explain the generative AI program that accumulates cat behavior data and learns changes in behavior patterns."

"Please explain how the emotion engine works, adjusting the device's behavior and responses based on the user's emotions."

In this way, the system utilizes animal behavior data and user emotion data to provide optimal interaction. The flow of the identification process in Example 3 will be explained using Figure 21.

Step 1:

The server collects animal behavior data from sensors installed on the device. As input, it receives real-time data from the sensors and, as output, generates data on the animal's movements and behavior patterns. Specifically, the camera tracks the cat's movements and the sensor detects which objects the cat touches.

Step 2:

The server stores the collected behavioral data in a database. As input, it receives the animal behavioral data generated in step 1, and as output, it stores the time-stamped behavioral data in the database. Specifically, it records the data "October 1, 2023, 08:00:00 - Cat chases laser pointer."

Step 3:

Generative AI analyzes accumulated behavioral data and learns animal behavior patterns. It receives behavioral data stored in a database as input and generates learning results about the animal's behavior patterns as output. Specifically, it learns the pattern of "chasing a laser pointer every morning at 8 o'clock."

Step 4:

The server issues instructions to the device based on the learning results of the generative AI. It receives the learning results of the generative AI as input and generates specific instructions for the device as output. Specifically, it issues the instruction "move the laser pointer at 8 o'clock every morning."

Step 5:

The device uses a camera and microphone to analyze the user's emotional state. As input, it receives data related to the user's facial expressions and tone of voice, and as output, it generates an analysis result related to the user's emotional state. Specifically, if the user is smiling while speaking, it is determined that they are happy.

Step 6:

The server adjusts the device's movements and reactions based on the analysis results of the emotion engine. It receives the user's emotion analysis results as input and generates specific instructions regarding the device's movements and reactions as output. Specifically, when the user is angry, the device's movements are suppressed so that the animal can remain quiet. Conversely, when the user is happy, the device's movements are made more active so that the user can play with the animal.

(Application Example 3)

Next, we will explain Application Example 3 of Form Example 3. In the following explanation, the data processing device 12 will be referred to as the "server" and the headset-type terminal 314 will be referred to as the "terminal."

Previous pet interaction systems struggled to provide appropriate reactions and stimuli based on changes in animal behavior patterns and the user's emotional state. Furthermore, they lacked the ability to provide real-time advice on how users should interact with animals, making it difficult to achieve optimal interactions with animals.

The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, an emotion engine that senses the user's emotional state and adjusts the device's movements and reactions, and means for advising the user on optimal interactions with the animal. This makes it possible to provide appropriate reactions and stimuli in response to changes in the animal's behavior patterns, and to achieve optimal interactions according to the user's emotional state.

A "spherical, freely movable device" is a device that has a spherical shape and the ability to physically move freely.

An "information terminal" is an electronic device operated by a user, such as a smartphone or tablet.

A "sensor that detects animal movements and behavior patterns" is a device that detects animal movements and behavior in real time and collects that data.

"Generative AI" is artificial intelligence that learns animal behavior patterns based on collected data and generates appropriate reactions and stimuli.

"Means for providing appropriate reactions and stimuli" is a function that provides appropriate reactions and stimuli to animals based on the results of learning by the generative AI.

An "emotion engine" is a system that senses the user's emotional state and adjusts the device's behavior and responses accordingly.

"Means for advising optimal interactions" is a function that provides real-time instructions to users on how best to interact with and play with animals.

A system for implementing this invention has the following configuration:

First, a spherical, freely movable device is required. This device is equipped with sensors that detect the animal's movements and behavior patterns. The sensors detect the animal's movements and behavior in real time and collect that data.

Next, you need an information terminal. An information terminal is an electronic device that users can operate, such as a smartphone or tablet. You can operate the device through this information terminal.

The collected data is analyzed by generative AI, which accumulates data on the animal's behavior over time and learns changes in the animal's behavior patterns based on that accumulated data. This makes it possible to understand the animal's preferences and play styles, and provide appropriate reactions and stimulation.

Furthermore, the emotion engine senses the user's emotional state. The emotion engine adjusts the device's movements and responses according to the user's emotional state. For example, it increases the device's movements when the user is happy, and reduces the device's movements when the user is angry.

Finally, it includes a way to advise users on optimal interactions with animals, allowing them to know in real time how to interact with animals.

For example, if the user types "happy," the system will advise, "Play with your cat more!". Also, if the user types "angry," the system will advise, "Let's give your cat a break."

Examples of prompts are as follows:

Enter the user's emotion (happy, angry, neutral): happy

In this way, it is possible to provide appropriate reactions and stimuli in response to changes in the animal's behavioral patterns, achieving optimal interaction according to the user's emotional state.

The flow of the specific processing in Application Example 3 will be explained using Figure 22.

Step 1:

The user operates the information terminal and starts the device. As input, the user starts the information terminal's application and turns on the device. As output, the device starts operating and the sensor begins to detect animal movement.

Step 2:

Sensors detect animal movements and behavior patterns in real time and collect the data. The animal's movements and behavior are detected by the sensors as input. The collected data is sent to the generative AI as output.

Step 3:

Generative AI analyzes the collected data and learns the animal's behavioral patterns. The input is the animal's behavioral data transmitted from the sensors. The output is the generation of appropriate reactions and stimulus instructions based on changes in the animal's behavioral patterns.

Step 4:

The emotion engine senses the user's emotional state. As input, the user enters their emotional state into the information terminal. As output, the emotion engine analyzes the user's emotional state and sends the results to the generative AI.

Step 5:

The generative AI adjusts the device's movements and responses based on the user's emotional state. The input is data on the user's emotional state sent from the emotion engine. The output is the device's movements and responses adjusted according to the user's emotional state.

Step 6:

Advises the user on optimal interactions with animals. Inputs include instructions from the generative AI and data on the user's emotional state. Outputs include advice on optimal interactions with animals displayed on the information terminal screen.

Step 7:

The user interacts with the animal according to the advice. The input is the advice displayed on the information terminal. The output is that the user's appropriate interaction with the animal changes the animal's behavioral patterns, and the sensor again collects that data.

This series of processing steps makes it possible to provide appropriate reactions and stimuli in response to changes in the animal's behavioral patterns, achieving optimal interaction according to the user's emotional state.

The specific processing unit 290 transmits the results of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the results of the specific processing. The microphone 238 acquires audio indicating the user input regarding the results of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

Data generation model 58 is what is known as generative AI (artificial intelligence). An example of data generation model 58 is generative AI such as ChatGPT (Internet search <URL: https://openai.com/blog/chatgpt>). Data generation model 58 is obtained by performing deep learning on a neural network. A prompt containing an instruction is input to data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. Data generation model 58 performs inference on the input inference data in accordance with the instructions indicated by the prompt, and outputs the inference results in the form of data such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and/or summarization.

Another example of generative AI is Gemini (Internet search <URL: https://gemini.google.com/?hl=ja>).

In the above embodiment, an example was given in which the specific processing was performed by the data processing device 12, but the technology disclosed herein is not limited to this, and the specific processing may also be performed by the headset-type terminal 314.

[Fourth embodiment]

Figure 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

As shown in FIG. 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

The data processing device 12 includes a computer 22, a database 24, and a communication I/F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and communication I/F 26 are also connected to the bus 34. The communication I/F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and/or a LAN (Local Area Network).

The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I/F 44, and a control target 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and control target 443 are also connected to the bus 52.

The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user 20's surroundings (e.g., an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

The communication I/F 44 is connected to the network 54. The communication I/Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I/Fs 44 and 26 is carried out in a secure manner.

The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32.

The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as the specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

Storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

In the robot 414, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

Next, we will explain the identification process performed by the identification processing unit 290 of the data processing device 12.

"Example 1"

One aspect of the present invention provides a spherical device. This device has an internal driving source such as a motor or battery, and is able to move around freely. A sensor is placed on the outside of the device to detect the cat's movements and behavioral patterns. This sensor detects the cat's movements and behavioral patterns and sends the data to a generative AI. The generative AI analyzes the received data and understands the cat's preferences and play styles. Based on this understanding, it then sends instructions to the device to provide the cat with appropriate reactions and stimuli. The device operates in accordance with the instructions and provides the cat with appropriate reactions and stimuli.

"Example 2"

As a specific example, if a cat exhibits aggressive behavior toward the device, a sensor will detect that behavior and send that information to the generative AI. The generative AI will analyze the information and understand that the cat prefers aggressive play. Based on that understanding, it will instruct the device to perform actions that will stimulate the cat. The device will then act in accordance with those instructions and provide the cat with appropriate stimulation.

"Example 3"

In addition, the generative AI accumulates data on the cat's behavior over time and learns changes in the cat's behavior patterns based on that accumulated data. For example, if a cat initially prefers aggressive play but develops a preference for gentler play over time, the generative AI will learn this change and issue appropriate instructions to the device based on that learning. This makes it possible to provide appropriate reactions and stimuli in response to changes in the cat's behavior patterns.

The processing flow for each example form is explained below.

"Example 1"

Step 1: The spherical device starts operating, and the sensors that detect the cat's movements and behavior patterns begin to function.

Step 2: The sensor detects the cat's movements and behavior patterns and sends that data to the generative AI.

Step 3: The generative AI analyzes the received data and understands the cat's preferences and play habits.

Step 4: Based on its understanding, the generative AI sends instructions to the device to provide the cat with appropriate reactions and stimuli.

Step 5: The device acts according to the instructions and provides the cat with the appropriate reaction or stimulus.

"Example 2"

Step 1: The cat exhibits aggressive behavior toward the device.

Step 2: The sensor detects the behavior and sends that information to the generative AI.

Step 3: The generative AI analyzes the information and understands that cats prefer aggressive play.

Step 4: Based on that understanding, the generative AI instructs the device to perform actions that stimulate the cat.

Step 5: The device follows the instructions and provides the appropriate stimulation to the cat.

"Example 3"

Step 1: The generative AI accumulates cat behavior data over time.

Step 2: The generative AI learns changes in the cat's behavioral patterns based on the accumulated data.

Step 3: The generative AI issues appropriate instructions to the device based on its learning.

Step 4: The device operates according to the instructions, providing appropriate reactions and stimuli in response to changes in the cat's behavioral patterns.

(Example 1)

Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Conventional animal play equipment struggled to provide the appropriate reactions and stimulation needed to keep animals interested, resulting in animals quickly becoming bored. Furthermore, the lack of a system capable of analyzing animals' behavioral patterns in real time and controlling their movements accordingly made it difficult to provide play styles tailored to each animal's individual preferences.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavioral patterns, generative artificial intelligence that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the artificial intelligence, means for generating instructions for controlling the operation of the device and sending the instructions to the device, and means for the device to operate in accordance with the instructions and provide appropriate reactions and stimuli to the animal. This makes it possible to analyze the behavioral patterns of animals in real time and provide appropriate reactions and stimuli according to the preferences of each individual animal.

The "device" is a spherical, freely movable device equipped with sensors that detect the movements and behavior patterns of animals.

An "information terminal" is an electronic device that provides a means for operating a device, including smartphones and tablets.

A "sensor" is a device that detects animal movements and behavior patterns and is installed in the device.

"Generative AI" is an artificial intelligence system that analyzes data from sensors and understands animals' preferences and play styles.

"Means for providing reactions and stimuli" refers to mechanisms and methods for providing appropriate reactions and stimuli to animals based on generative artificial intelligence.

"Means for generating instructions" refers to the mechanism or method for generating instructions to control the operation of a device based on data analyzed by generative artificial intelligence.

"Means for sending instructions" refers to communication means for sending the generated instructions to the device.

"Means for controlling behavior" refers to the mechanism or method by which the device operates according to the instructions it receives and provides the animal with an appropriate reaction or stimulus.

This invention is a system that analyzes animal behavior patterns in real time and provides appropriate reactions and stimuli based on the preferences of each individual animal. Specific embodiments of this system are described below.

System Configuration

The system consists of the following main components:

1. Device: A spherical, freely movable device equipped with sensors that detect animal movements and behavior patterns.

2. Information terminal: An electronic device that provides a means for operating a device, including smartphones and tablets.

3. Sensor: A device that detects animal movements and behavior patterns and is installed in the device.

4. Generative AI: An artificial intelligence system that analyzes data from sensors to understand animals' preferences and play styles.

5. Means for providing reactions and stimuli: Mechanisms and methods for providing appropriate reactions and stimuli to animals based on generative artificial intelligence.

6. Means for generating instructions: A mechanism or method for generating instructions to control the operation of a device based on data analyzed by generative artificial intelligence.

7. Means for sending instructions: A communication means for sending the generated instructions to the device.

8. Means for controlling behavior: The mechanism or method by which the device operates according to the instructions it receives and provides the animal with the appropriate reaction or stimulus.

System Operation

1. Initialize the device

The user turns on the device.

The device checks the internal motor and battery to ensure they are working properly.

The device will calibrate the sensors to ensure accurate data collection.

2. Data Collection

The device uses sensors to detect animal movements and behavior patterns in real time.

The device temporarily stores detected data.

3. Data Transmission

The device sends the collected data to the server.

The server receives the data and prepares it for analysis.

4. Data Analysis

The server passes the received data to the generative artificial intelligence.

Generative AI analyzes data to understand animals' preferences and behavioral patterns.

5. Instruction Generation

Based on the analysis results, generative AI generates instructions to provide the animal with appropriate reactions and stimuli.

The server receives the generated instructions.

6. Sending instructions

The server sends the generated instructions to the device.

The terminal receives the instructions and transmits them to the device.

7. Device Operation

The device operates according to the instructions received by the terminal.

The device provides the animal with appropriate reactions and stimuli.

Specific examples

For example, if a cat approaches a device, the device's sensor will detect the movement. The server will determine that the cat is interested in the device and send the data to the generative AI. The generative AI will then generate an instruction to "move the device slightly to attract the cat." The server will then send the instruction to the device, which will then move the device.

Example prompt

"Generate an appropriate reaction when a cat approaches the device."

"If my cat likes to chase the device, what movements should I give it?"

In this way, the system can analyze the animal's behavior in real time and provide appropriate reactions, keeping the animal engaged.

The flow of the identification process in Example 1 will be explained using Figure 11.

Step 1: Initialize your device

Input: The user turns on the device.

Processing: The device checks the internal motors and batteries to ensure they are working properly. It also calibrates the sensors to ensure accurate data collection.

Output: The device is ready to operate normally.

Specific operation: The user presses the device's power button, and the device checks the device's LED indicator to confirm normal operation.

Step 2: Collect data

Input: The device detects animal movements and behavior patterns.

Processing: The device uses its sensors to detect animal movements and behavior patterns in real time and temporarily store the data.

Output: Data on animal movements and behavior patterns is collected.

Specific operation: The device uses a sensor to detect the cat's movement as it approaches the device and stores the data in memory.

Step 3: Send data

Input: Collected animal movement and behavior pattern data.

Processing: The device sends the collected data to the server. The server receives the data and prepares it for analysis.

Output: Data is sent to the server and ready for analysis.

Specific operation: The device sends data to the server via Wi-Fi, and the server receives the data and stores it in a database.

Step 4: Data Analysis

Input: Animal movement and behavior pattern data received by the server.

Processing: The server passes the received data to the generative AI, which analyzes the data to understand the animal's preferences and behavioral patterns.

Output: Analysis results on animal preferences and behavior patterns.

Specific operation: The server inputs data into the generative AI, which then concludes that "cats like to chase balls."

Step 5: Generate instructions

Input: Analysis results from generative artificial intelligence.

Processing: Based on the analysis results, the generative AI generates instructions to provide the animal with appropriate reactions and stimuli. The server receives the generated instructions.

Output: Instructions for providing the appropriate reaction or stimulus to the animal.

Specific operation: The generative artificial intelligence generates the instruction "rotate the device to the right," and the server receives that instruction.

Step 6: Send instructions

Input: Generated instructions.

Processing: The server sends the generated instructions to the terminal, which receives the instructions and transmits them to the device.

Output: Instructions sent to the device.

Specific operation: The server sends instructions to the terminal via Wi-Fi, and the terminal receives the instructions and passes them on to the device.

Step 7: Device Operation

Input: Instructions received by the terminal.

Processing: The terminal operates the device according to the instructions received, providing the animal with the appropriate reaction or stimulus.

Output: The appropriate reaction or stimulus provided to the animal.

Specific behavior: The terminal controls the device's motor and rotates it to the right. The device rotates in front of the cat, and the cat chases it.

(Application Example 1)

Next, we will explain Application Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Existing pet devices struggled to fully understand animals' movements and behavior patterns and provide appropriate reactions and stimuli. Furthermore, physical stores lacked the means to provide a fun environment for animals. This meant that efforts to reduce animal stress and improve customer satisfaction were not fully achieved.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

In this invention, the server includes a spherical device that can move around freely, means for operating the device from a smartphone, a sensor installed in the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and ways of playing, means for providing the animal with appropriate reactions and stimuli based on the AI, and means for the device to detect the animal's movements within the physical store and provide appropriate reactions and play using the generative AI. This allows the animal to have fun within the physical store, improving customer satisfaction.

A "spherical device that can move freely" is a spherical device that has an internal power source such as a motor or battery and can move in any direction.

"Means for operating from a smartphone" refers to interfaces and applications for remotely controlling the operation of a device using a smartphone.

A "sensor that detects animal movements and behavior patterns" is a device that senses the position, speed, direction, and other movements of animals and collects that data.

"Generative AI" is an artificial intelligence model that analyzes collected animal movement and behavior data to understand animals' preferences and play styles.

"Means for providing appropriate reactions and stimuli to animals" refers to a mechanism that allows animals to take appropriate actions or react based on instructions generated by the generative AI.

"Means for detecting animal movements within a physical store and using generative AI to provide appropriate reactions and play" refers to a system that detects animal movements within a physical store in real time, sends that data to generative AI, and provides appropriate reactions and play for the animals.

This invention is a system for providing an environment in a physical store where animals, particularly cats, can have fun. The system includes a spherical, freely moving device, a means for operating it from a smartphone, sensors that detect the animal's movements and behavior patterns, generative AI, and a means for providing the animal with appropriate reactions and stimuli.

System Configuration

1. Spherical device:

It is equipped with a motor and battery inside, allowing it to move in any direction.

Sensors are placed on the exterior to detect animal movement.

2. How to operate from your smartphone:

An application is provided for remotely controlling the device's operation using a smartphone.

3. Sensors that detect animal movements and behavior patterns:

It detects the animal's location, speed, direction, and other movements and collects that data.

4. Generative AI:

Analyze collected animal movement and behavior data to understand animals' preferences and play styles.

Generative AI models are used to generate appropriate reactions and stimuli for animals.

5. How to provide appropriate reactions and stimuli to animals:

The robot will then perform appropriate actions and reactions towards the animal based on the instructions generated by the generative AI.

Program processing explanation

The server sends the animal's movement data collected from the sensors to the generative AI. The generative AI analyzes this data to understand the animal's preferences and play styles. Based on what it understands, it generates instructions to provide the animal with appropriate reactions and stimuli. These instructions are sent to the device, which then performs the appropriate action on the animal.

The hardware used includes sensors to detect animal movement, motors to power the device, and batteries to power the device. The software used includes a generative AI model, a sensor control module, and a motor control module.

Specific examples

For example, when a cat approaches a device in a pet shop, a sensor detects its movement and sends the data to the generative AI. The generative AI then generates movements that will interest the cat and sends those instructions to the device. The device then starts moving as if the cat is chasing it, attracting the cat's interest.

Also, when a cat touches the device in a cafe, a sensor detects the movement and sends the data to the generative AI. The generative AI generates a rotating motion that the cat will enjoy and sends that instruction to the device. The device then rotates in a way that the cat will enjoy, attracting its interest.

Example prompt

"Enter your cat's movement data. This data includes the cat's position, speed, direction, etc. Use this data to generate reactions that will interest your cat."

The above is an embodiment of the invention. This system allows animals to have fun in physical stores, improving customer satisfaction.

The flow of the specific processing in Application Example 1 will be explained using Figure 12.

Step 1:

The sensor detects the animal's movement. The sensor collects data such as the animal's position, speed, and direction, and sends that data to the server. The input is the animal's movement data, and the output is the movement data sent to the server.

Step 2:

The server sends the animal's movement data received from the sensors to the generative AI. The generative AI analyzes this data and understands the animal's preferences and play styles. The input is movement data from the sensors, and the output is the analysis results by the generative AI.

Step 3:

The generative AI generates appropriate reactions and stimuli for the animal based on the analysis results. The generative AI generates actions and responses that will interest the animal and sends these instructions to the server. The input is the analysis results of the animal's movement data, and the output is the generated reactions and stimulus instructions.

Step 4:

The server sends the instructions received from the generative AI to the device. The device begins to operate based on the received instructions. The input is the instructions from the generative AI, and the output is the device's operation.

Step 5:

The device provides appropriate reactions and stimuli to the animal. The device responds to the animal's movements and performs actions that the animal enjoys. The input is instructions from the server, and the output is reactions and stimuli to the animal.

Step 6:

The device detects physical stimuli from the animal and feeds that data back to the server. The server then sends this data to the generative AI, where it is stored as animal behavior data. The input is physical stimulus data from the animal, and the output is feedback data for the generative AI.

These are the specific processing steps of this system. The specific actions performed at each step allow animals to have fun in physical stores.

(Example 2)

Next, Example 2 of Form Example 2 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Previous cat devices simply detected a cat's behavior and were unable to provide appropriate stimuli based on the cat's individual behavioral patterns and preferences. They also lacked the functionality to accumulate cat behavior data and learn over time, making it difficult to respond to changes in a cat's behavioral patterns. Furthermore, they lacked the functionality to automatically respond to physical stimuli from the cat and provide feedback on that response. This made it difficult to maintain a cat's interest, and made effective play and training impossible.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

In this invention, the server includes sensor means for detecting the cat's behavior, terminal means for transmitting data from the sensor means to the server, means for analyzing the data using a generative AI model in the server means, device means for providing stimuli to the cat based on instructions from the server means, and terminal means for controlling the device means. This makes it possible to analyze cat behavior data in real time and provide appropriate stimuli based on the individual cat's behavioral patterns and preferences. In addition, by accumulating cat behavior data over time and learning changes in behavioral patterns based on that data, the cat's interest can be sustained. Furthermore, the function of automatically responding to physical stimuli from the cat and providing feedback on that response allows for effective play and training.

"Sensor means" refers to a device for detecting cat behavior, including motion sensors and cameras.

"Terminal means" refers to a device for transmitting data from sensor means to a server, and includes a data transmission module and a communication device.

The "server means" is a device that analyzes the received data using a generative AI model and generates instructions to provide appropriate stimulation to the cat.

A "generative AI model" is an artificial intelligence model that analyzes cat behavior data and generates instructions to provide appropriate stimuli based on the cat's behavioral patterns and preferences.

"Device means" refers to a device for providing stimuli to the cat based on instructions from the server means, and includes a robotic arm, a laser pointer, etc.

"Real-time" means that data is processed immediately the moment it is generated, providing an immediate response without delay.

"Behavioral patterns" refer to the tendencies and habits of a series of behaviors that a cat displays in response to specific situations or stimuli.

"Feedback" refers to the device's means' response to physical stimuli from the cat being sent back to the generative AI model, allowing the generative AI model to learn and generate more appropriate instructions.

This invention is a system that detects cat behavior, analyzes the data, and provides appropriate stimuli to the cat. This system includes sensor means, terminal means, server means, a generative AI model, and device means.

First, the device detects the cat's behavior using a sensor. Sensors include motion sensors and cameras. For example, if the cat scratches the device with its claws, this behavior is detected in real time.

The device then transmits the detected behavioral data to a server via a data transmission module. This data includes the cat's movement patterns and location information. For example, it includes the time and location information when the cat scratches the device.

The server inputs the received data into a generative AI model to analyze the cat's behavior. Examples of generative AI models used include OpenAI's GPT-4. The generative AI model determines whether the cat enjoys aggressive play. For example, if the cat frequently exhibits aggressive behavior toward the device, it learns that behavioral pattern.

Then, based on the analysis results, the server instructs the device to perform appropriate actions to stimulate the cat, for example, moving the robotic arm to attract the cat's interest.

Finally, the terminal receives instructions from the server and controls the device to provide appropriate stimuli to the cat, for example, moving a laser pointer to stimulate the cat.

As a concrete example, consider the following scenario: When a cat scratches its claws at the device, the motion sensor detects this movement. The sensor sends this information to the server via the data transmission module. The generative AI model analyzes the data and understands that cats prefer aggressive play. The generative AI model then instructs the robotic arm to perform actions that will attract the cat's interest. The robotic arm operates according to these instructions, providing the cat with appropriate stimuli.

Examples of prompts to input into a generative AI model include:

"Your cat has clawed at the device. Analyze this behavior and determine whether your cat prefers aggressive play. Then instruct the device on the appropriate action to stimulate your cat."

The above is a form for implementing this invention.

The flow of the identification process in Example 2 will be explained using Figure 13.

Step 1:

The device uses sensor means to detect the cat's behavior. Specifically, motion sensors and cameras monitor the cat's movements in real time and detect aggressive behavior. For example, if the cat digs its claws into the device, this behavior will be detected.

Input: Cat movement

Output: Detected cat behavior data (e.g., time and location of cat claw movements)

Step 2:

The device sends the detected behavioral data to the server via the data transmission module. Specifically, the data obtained from the sensor is packetized and sent to the server via the network.

Input: Detected cat behavior data

Output: Behavioral data sent to the server

Step 3:

The server inputs the received data into a generative AI model to analyze the cat's behavior. Specifically, it inputs behavioral data into a generative AI model (e.g., GPT-4) to determine whether the cat prefers aggressive play.

Input: Behavioral data sent to the server

Output: Analysis of cat behavior patterns (e.g., cats prefer aggressive play)

Step 4:

Based on the analysis results, the server instructs the device on the appropriate actions to stimulate the cat. Specifically, it generates movement instructions for the robot arm and laser pointer based on the analysis results of the generative AI model.

Input: Analysis results of cat behavior patterns

Output: Commands to the device (e.g., moving the robotic arm to attract the cat's attention)

Step 5:

The terminal receives instructions from the server and controls the device to provide appropriate stimuli to the cat. Specifically, it moves the robotic arm and laser pointer to entertain the cat.

Input: Operation instructions from the server

Output: Appropriate stimuli provided to the cat (e.g., robotic arm movement, laser pointer movement)

The above is the specific flow of processing for this system's program.

(Application Example 2)

Next, we will explain Application Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Conventional safety monitoring systems in factories have the drawback of being unable to detect abnormal worker or machine behavior in real time and quickly respond appropriately. Furthermore, systems that understand animal behavior and provide appropriate stimuli are limited, and they are unable to learn changes in animal behavior patterns. To solve these issues, a system is needed that can monitor animal and worker behavior in real time, detect abnormal behavior, and respond appropriately.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

In this invention, the server includes a spherical device that can move around freely, means for operating the device from an information terminal, a sensor installed in the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, a sensor that detects abnormal behavior of workers and machines within the factory, means for transmitting data from the sensor to the generative AI and analyzing the abnormal behavior, and means for instructing an appropriate response based on the analysis results. This makes it possible to learn changes in the animal's behavior patterns and provide appropriate stimuli, as well as detect abnormal behavior of workers and machines within the factory in real time and respond quickly.

A "spherical, freely movable device" is a device that has a spherical shape and the ability to physically move freely.

An "information terminal" is an electronic device used to remotely control devices such as smartphones and tablets.

A "sensor that detects animal movements and behavior patterns" is a device that detects animal movements and behavior in real time and acquires that data.

"Generative AI" is an artificial intelligence system that analyzes acquired data, understands the behavioral patterns of animals and workers, and generates appropriate responses.

"Means for providing appropriate reactions and stimuli to animals" refers to devices and methods for providing appropriate reactions and stimuli to animals based on the analysis results of generative AI.

"Sensors that detect abnormal behavior of workers and machines in factories" are devices that monitor the behavior of workers and machines in factories and detect abnormal behavior in real time.

"Means for analyzing abnormal behavior" refers to a method or device for sending data on detected abnormal behavior to the generative AI and analyzing that data.

"Means for instructing appropriate responses" refers to a method or device for instructing appropriate responses to abnormal behavior based on the analysis results of generative AI.

As an embodiment of this invention, the following system is constructed.

First, a spherical, freely movable device is prepared. This device is equipped with sensors that detect the animal's movements and behavioral patterns. The device can be controlled from an information terminal (e.g., a smartphone or tablet).

Next, we prepare the generative AI. This generative AI analyzes the data obtained from the sensors to understand the animal's preferences and play styles. The generative AI generates instructions to provide the animal with appropriate reactions and stimuli.

In addition, sensors will be installed within the factory to detect abnormal behavior by workers or machines. These sensors will also send data to the generative AI, which will analyze the abnormal behavior. The generative AI will then instruct the appropriate response to the abnormal behavior.

A specific example would be the following system.

1. Animal behavior monitoring system

If an animal exhibits aggressive behavior toward the device, a sensor detects the behavior and sends that information to the generative AI. The generative AI analyzes the information and understands that the animal prefers aggressive play. Based on this understanding, it then instructs the device to perform actions that will stimulate the animal. The device then acts according to those instructions and provides the animal with appropriate stimulation.

2. Factory Safety Monitoring System

If a worker or machine in a factory behaves abnormally, a sensor detects the behavior and sends the data to the generative AI. The generative AI analyzes the data and detects abnormal behavior. If an abnormality is detected, the generative AI will instruct the appropriate response, such as sounding an alarm or halting work.

The hardware used includes sensors to detect animal movement, sensors to detect abnormal behavior in factories, information terminals, and spherical devices. The software used is a generative AI model.

As a concrete example, the following prompt sentence could be input into a generative AI model:

Example prompt:

"Analyze the data when a worker falls, and if an abnormality is detected, issue an instruction to sound an alarm."

In this way, it is possible to learn changes in animal behavior patterns and provide appropriate stimuli, as well as detect abnormal behavior of workers or machinery within the factory in real time and respond quickly.

The flow of the specific processing in Application Example 2 will be explained using Figure 14.

Step 1:

Sensors detect the movement of animals and workers.

Input: Animal and worker movement data

Data processing: Sensors collect operational data in real time and convert it into digital signals.

Output: Digitized motion data

Step 2:

Data obtained from the sensors is sent to the generative AI.

Input: Digitized motion data

Data processing: The data acquired by the sensor is packetized in order to be sent to the generative AI.

Output: Packetized motion data

Step 3:

Generative AI analyzes movement data.

Input: Packetized motion data

Data calculation: Generative AI analyzes movement data to identify abnormal movements and animal behavior patterns.

Output: Analysis results (detection of abnormal behavior and animal behavior patterns)

Step 4:

Generative AI will instruct appropriate responses based on the analysis results.

Input: Analysis results

Data calculation: Based on the analysis results, generative AI determines the appropriate response (e.g., sound an alarm, activate the device, etc.).

Output: Action instructions

Step 5:

Devices and information terminals operate according to the instructions of generative AI.

Input: Response instructions

Specific actions: The device provides appropriate stimuli to the animal, the information terminal sounds an alarm, etc.

Output: Action taken (stimulates animal, sounds alarm, etc.)

Step 6:

The generative AI receives feedback from the results of its actions.

Input: Result of the action performed

Data processing: Generative AI evaluates the execution results and accumulates data to reflect in the next response.

Output: Updated behavioral database

These steps will enable the system to learn changes in animal behavior patterns and provide appropriate stimuli, as well as detect abnormal behavior of workers or machinery within the factory in real time and respond quickly.

(Example 3)

Next, Example 3 of Form Example 3 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Previous animal devices struggled to learn an animal's behavioral patterns in real time and provide appropriate reactions and stimuli based on those patterns. Furthermore, there were no systems that could accumulate animal behavioral data over long periods of time and learn from those changes. This made it difficult to provide appropriate reactions and stimuli in response to changes in an animal's behavioral patterns.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

In this invention, the server includes means for storing data from sensors that detect animal movements and behavioral patterns in a database, means for cleansing the stored data and extracting behavioral patterns, means for the generative artificial intelligence to learn changes in behavioral patterns, and means for generating appropriate instructions based on the learning results. This makes it possible to provide appropriate reactions and stimuli in response to changes in the animal's behavioral patterns.

The "device" is a spherical device that can move freely and detects the movements and behavior patterns of animals.

A "personal digital assistant" is a portable electronic device, such as a smartphone or tablet, used to operate the device.

A "sensor" is a sensing device installed in a device to detect animal movements and behavior patterns.

"Generative AI" is AI that analyzes data from sensors, understands animals' preferences and play styles, and provides appropriate reactions and stimuli.

The "database" is an information management system for storing animal behavior data collected from sensors.

"Cleansing" is the process of removing noise from raw data stored in a database and filling in missing data.

A "behavioral pattern" is a series of behaviors that an animal tends to exhibit at a particular time or in a particular situation.

"Learning" is the process by which generative artificial intelligence understands changes in animal behavior patterns based on accumulated data.

"Instructions" are specific operational commands that generative AI issues to a device based on its learning results.

"Reactions" are specific actions or stimuli that the device performs on the animal in accordance with instructions from the generative artificial intelligence.

This invention is a system that learns animal behavior patterns in real time and provides appropriate reactions and stimuli based on those patterns. Specific embodiments of this system are described below.

Hardware and software used

Hardware: Sensors (cameras, microphones, etc.) that detect animal movements and behavior patterns, a spherical device that can move freely, and a mobile information terminal (smartphone or tablet)

Software: Generative AI (e.g., OpenAI's GPT-4), databases (MySQL and MongoDB)

System Configuration

1. Device:

It is equipped with sensors to detect animal movements and behavior patterns.

Data from sensors is collected in real time and sent to a server.

2. Mobile Information Devices:

Used as a means to operate the device.

Users can control the device's operation through their mobile information terminal.

3. Server:

Receives data sent from sensors and stores it in a database.

Clean the accumulated data and extract behavioral patterns.

Uses generative artificial intelligence to learn changes in behavioral patterns.

Based on the learning results, appropriate instructions are generated for the device.

Specific examples

For example, consider a situation where a cat initially prefers aggressive play, but over time begins to prefer gentle play.

1. Data Collection:

The device (camera) captures the cat poking at the toy as it moves vigorously.

The server receives the video data and stores it in a database.

2. Data preprocessing:

The server removes unnecessary parts from the video data and extracts only the cat's movements.

The server organizes the extracted data by time and analyzes the cat's behavioral patterns.

3. Learning behavioral patterns:

The server uses generative artificial intelligence to learn when the cat has changed from aggressive to calm play.

The server saves the learning results and proceeds to the next step.

4. Generating appropriate instructions:

The server inputs a prompt to the generative AI: "Since the cat has started to prefer gentle play, please generate instructions to move a toy with gentle movements."

The server sends the generated instructions to the device.

5. Providing Reactions:

The device (toy) makes gentle movements according to instructions received from the server.

The device provides gentle play for your cat and responds to your cat's behavioral patterns.

Example prompt

By inputting the following prompt sentence into the generative artificial intelligence, instructions based on changes in the cat's behavioral patterns can be generated.

Behavioral data for a cat is shown below. At first, the cat preferred aggressive play, but over time, it began to prefer gentle play. Based on this change, generate instructions to provide the cat with appropriate reactions and stimuli.

In this way, the system is able to provide appropriate reactions and stimuli in response to changes in the animal's behavioral patterns. The flow of the identification process in Example 3 will be explained using Figure 15.

Step 1: Data Collection

The device (sensor) monitors the animal's movements in real time and collects behavioral data. For example, a camera captures a cat's movements and a microphone records the cat's meows.

Input: Real-time animal movements and sounds

Output: Animal behavior data (video and audio data)

Specific operation: The camera captures the cat's movements, and the microphone records the cat's meows. The device collects this data and sends it to the server.

Step 2: Data preprocessing

The server cleanses the raw data stored in the database. Specifically, it removes noise and fills in missing data.

Input: Raw data (video data, audio data)

Output: Cleansed data

Specific operation: The server removes unnecessary parts from the video data and filters noise from the audio data. Any missing data is filled in.

Step 3: Extracting behavioral patterns

The server organizes the cleansed data by time and extracts behavioral patterns.

Input: Cleansed data

Output: Behavioral pattern data

Specific operation: The server analyzes the cleansed data and extracts information about the animal's behavior at specific times of the day.

Step 4: Learning behavioral patterns

The server uses a generative AI model to learn animal behavior patterns based on accumulated data.

Input: Behavioral pattern data

Output: Learning results (changes in behavioral patterns)

Specific operation: The server inputs behavioral pattern data into the generative AI model, which then learns changes in the animal's behavior. For example, it learns that a cat has changed from aggressive play to calm play.

Step 5: Generate appropriate instructions

The server generates appropriate instructions for the device based on the learning results.

Input: Learning results

Output: Instruction data

Specific behavior: The server inputs a prompt to the generative AI model: "Since the cat has started to prefer gentle play, please generate instructions to move a toy with gentle movements," and sends the generated instructions to the device.

Step 6: Provide a reaction

The terminal (device) operates according to the instructions received from the server.

Input: Instruction data

Output: Reaction to animals

Specific action: The device activates a toy with gentle movements, providing gentle play for the cat.

(Application Example 3)

Next, we will explain Application Example 3 of Form Example 3. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Conventional animal devices and generative AI were limited to learning animal behavior patterns and providing appropriate reactions. However, there were no systems that could learn the behavior patterns of workers in factories and provide appropriate support. As a result, improvements in work efficiency and reductions in worker burden were not fully achieved. Therefore, there is a need for a system that can learn the behavior patterns of workers in factories and provide appropriate support.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

In this invention, the server includes a spherical device that can move around freely, means for operating the device from a smartphone, a sensor installed in the device that detects the animal's movements and behavioral patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and behavioral patterns, means for providing appropriate reactions and stimuli to the animal based on the AI, and means for accumulating worker behavioral data over time, learning changes in behavioral patterns based on the accumulated data, and providing appropriate support. This makes it possible to learn the behavioral patterns of workers within the factory and provide appropriate support.

A "spherical, freely movable device" is a device that has a spherical shape and the ability to physically move freely.

"Means for operating from a smartphone" refers to the interface or software for remotely operating a device using a smartphone.

A "sensor that detects animal movements and behavior patterns" is a device that detects animal movements and behavior in real time and collects that data.

"Generative AI" is an artificial intelligence technology that learns the behavioral patterns of animals and workers based on collected data and provides appropriate reactions and support.

"Means for providing appropriate reactions and stimuli" refers to devices or functions that provide appropriate reactions and stimuli to animals or workers based on the results of learning by the generative AI.

"Means for accumulating worker behavioral data over time" refers to a system that continuously records worker behavior and stores that data for long periods of time.

"Means of learning changes in behavioral patterns and providing appropriate support" is a function that analyzes accumulated behavioral data, recognizes changes in behavioral patterns, and provides optimal support to workers.

The following hardware and software are required to implement this invention. Hardware requires a spherical, freely movable device, a smartphone, a factory robot, and sensors. Software requires Python, scikit-learn, and a generative AI model.

First, the spherical, freely movable device is equipped with sensors that detect the behavior of animals and workers in real time. These sensors detect the movements and behavioral patterns of animals and workers and collect that data. The collected data is sent to a generative AI model for analysis.

The generative AI model learns the behavioral patterns of animals and workers based on collected data. This learning process uses Python and scikit-learn. Specifically, it uses the KMeans clustering algorithm to classify behavioral patterns and learns how behavioral patterns change over time.

Once learning is complete, the generative AI model will provide instructions for providing appropriate reactions and stimuli to animals and workers. For example, if an animal prefers aggressive play, the device will provide appropriate stimuli. Also, if a worker transitions from manual to automated tasks, the robot will provide appropriate support.

For example, if a worker is manually assembling parts in a factory, a robot will help carry the parts. Also, if a worker is operating automated machinery, a robot will help with machine maintenance.

Examples of prompt statements include:

"Develop AI that collects data on worker behavior in factories and learns changes in behavioral patterns based on that data. For example, when workers transition from manual to automated tasks, create a robot that learns this change and provides appropriate support."

In this way, this invention can improve work efficiency within factories and reduce the burden on workers.

The flow of the specific processing in Application Example 3 will be explained using Figure 16.

Step 1:

The server uses sensors to collect behavioral data of animals and workers. The input is real-time behavioral data obtained from the sensors, and the output is a list of collected behavioral data. Specifically, the sensors detect the movements of animals and workers and send that data to the server.

Step 2:

The server accumulates the collected behavioral data. The input is the behavioral data collected in step 1, and the output is a database of accumulated behavioral data. Specifically, the server saves the data it receives in the database.

Step 3:

The server uses the accumulated behavioral data to train a generative AI model. The input is the accumulated behavioral data, and the output is the trained generative AI model. Specifically, the server uses Python and scikit-learn to run the KMeans clustering algorithm and classify behavioral patterns.

Step 4:

When new behavioral data is input, the server uses a generative AI model to predict behavioral patterns. The input is the new behavioral data, and the output is the predicted behavioral pattern. Specifically, the server inputs the new data into the generative AI model and obtains the predicted results.

Step 5:

The server issues instructions to provide appropriate reactions and support based on the prediction results. The input is the predicted behavior pattern, and the output is instructions for reactions and support. In terms of specific operations, the server instructs the device or robot to perform the appropriate action.

Step 6:

The terminal (smartphone) receives instructions from the server and operates the device or robot. The input is the instruction from the server, and the output is the operation of the device or robot. Specifically, the smartphone sends operation commands to the device or robot.

Step 7:

The user monitors the operation of the device or robot and operates it manually as necessary. The input is the operating status of the device or robot, and the output is the user's operation commands. Specifically, the user manually operates the device or robot using a smartphone.

It is also possible to further combine an emotion engine that estimates the user's emotion. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

"Example 1"

One embodiment of the present invention provides a system that incorporates an emotion engine. This system recognizes the user's emotions and adjusts the reactions and stimuli given to the cat according to those emotions. Specifically, when the user is happy, the system encourages the cat to play actively. Conversely, when the user is depressed, the system encourages the cat to play quietly. This enables optimal interaction with the cat according to the user's emotional state.

"Example 2"

The emotion engine also recognizes emotions from the user's tone of voice, facial expressions, or physical reactions. For example, if the user is smiling, the system will recognize that the user is happy and encourage the cat to play actively. Conversely, if the user is crying, the system will recognize that the user is sad and encourage the cat to play quietly. This allows for a more accurate understanding of the user's emotional state and optimal interaction with the cat accordingly.

"Example 3"

Furthermore, the emotion engine adjusts the device's movements and reactions according to the user's emotions, improving the interaction between the user and the cat. For example, when the user is angry, the system suppresses the device's movements to prevent the cat from bothering the user. Conversely, when the user is happy, the system activates the device's movements to allow the cat to play happily with the user. This enables optimal interaction with the cat according to the user's emotional state.

The processing flow for each example form is explained below.

"Example 1"

Step 1: The user's emotion engine recognizes the user's emotion.

Step 2: Based on the recognized emotion, the system adjusts its reactions and stimuli to the cat.

Step 3: When the user is happy, the system encourages active play with the cat.

Step 4: When the user is feeling down, the system encourages quiet play with the cat.

"Example 2"

Step 1: The emotion engine recognizes emotions from the user's tone of voice, facial expressions, or physical reactions.

Step 2: If the user is smiling, the system recognizes that the user is happy and encourages active play with the cat.

Step 3: If the user is crying, the system recognizes that the user is sad and prompts the cat to play quietly.

"Example 3"

Step 1: The emotion engine recognizes the user's emotions.

Step 2: Adjust the device's movements and responses based on the user's emotions.

Step 3: When the user is angry, the system inhibits the device's movement to prevent the cat from bothering the user.

Step 4: When the user is happy, the system activates the device's activity, allowing the cat to play happily with the user.

(Example 1)

Next, Example 1 of Form Example 1 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Previous animal devices simply detected animal movements and behavioral patterns, but were unable to understand the animal's preferences and play styles and provide appropriate reactions or stimulation. Furthermore, they lacked the ability to adjust interactions with the animal based on the user's emotional state, making it difficult to deepen the relationship between the user and the animal.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, and an emotion engine that recognizes the user's emotions and adjusts the reactions and stimuli to the animal according to those emotions. This makes it possible to understand the animal's behavior patterns and provide optimal reactions and stimuli according to the user's emotional state.

A "device" is a spherical piece of equipment that can move freely.

An "information terminal" is an electronic device that provides a means for operating a device.

A "sensor" is a device used to detect animal movements and behavior patterns.

"Generative AI" is artificial intelligence that analyzes data from sensors and understands animals' preferences and play styles.

"Means for providing reactions and stimuli" refers to a mechanism for providing appropriate reactions and stimuli to animals based on the analysis results of the generative AI.

The "emotion engine" is a system that recognizes the user's emotions and adjusts the reactions and stimuli given to animals based on those emotions.

"Animal behavior data" is information about animal movements and behavior patterns.

"Feedback" is the process of returning the device's response to physical stimuli from the animal to the generative AI.

This invention is a system that understands animal behavior patterns and provides optimal reactions and stimuli according to the user's emotional state. Specific embodiments of this system are described below.

Hardware and software used

Device: A spherical device that can move freely. It is equipped with motors, batteries, and sensors.

Information terminal: An electronic device that provides a means for operating a device. Examples include smartphones and tablets.

Sensor: A device used to detect animal movements and behavior patterns. Accelerometers and infrared sensors are used.

Generative AI: Artificial intelligence that analyzes data from sensors to understand animals' preferences and play styles. It uses AI models that run on the cloud.

Emotion engine: A system that recognizes the user's emotions and adjusts the animal's reactions and stimuli accordingly. Emotion recognition software is used.

Program processing

The server receives the animal's behavioral data sent from the device and inputs it into the generative AI. The generative AI analyzes the received data to understand the animal's preferences and play styles. Based on the analysis results, the generative AI then generates instructions to provide the animal with appropriate reactions and stimuli, and sends these to the device.

The device collects data to recognize the user's emotions. For example, it uses the smartphone's camera and microphone to analyze the user's facial expressions and tone of voice. The emotion engine receives the user's emotional data and adjusts the animal's reactions and stimuli according to those emotions.

Specific examples

Example 1: When a cat approaches the device, the sensor detects its movement and sends the data to the server. The server uses a generative AI model to determine that the cat is interested and sends the device an instruction to "rotate to attract the cat's attention." The device then begins to rotate in place.

Example 2: When a user is using a smartphone, the device captures the user's facial expression with its camera, and the emotion engine recognizes that the user is happy. The server then sends instructions to the generative AI model to encourage active play, causing the device to act as if it were running around with a cat.

Example prompt

"Please explain what happens when a cat approaches the device."

"Please explain how users react to cats when they are happy."

The above is a specific form for implementing this invention. This system makes it possible to understand animal behavior patterns and provide optimal reactions and stimuli according to the user's emotional state.

The flow of the identification process in Example 1 will be explained using Figure 17.

Step 1:

Initializing the device

Server: Initializes the device. Checks the status of the motor and battery, and ensures that sensors are working properly.

Input: The signal that powers on the device.

Output: Signals that initialization is complete.

Specific operation: When the device is turned on, the server checks the status of each component of the device and, if everything is normal, sends a signal indicating initialization is complete.

Step 2:

Cat movement detection

Device: Uses internal sensors to detect your cat's movements and behavior patterns in real time.

Input: Cat movements and behavior.

Output: Detection data.

Specific behavior: When a cat approaches or touches the device, the sensor detects the movement and collects data.

Step 3:

Data transmission

Device: Sends detected data to the server.

Input: Detection data.

Output: Send data to the server.

Specific operation: The data collected by the sensor is sent to the server via wireless communication.

Step 4:

Data analysis

Server: Inputs the received data into a generative AI model to analyze the cat's behavioral patterns and preferences.

Input: Detection data.

Output: Behavioral pattern analysis results.

Specific operation: The server inputs the data "a cat touched the device" into the generated AI model, and the AI determines that "the cat is showing interest."

Step 5:

Generating instructions

Server: Based on the analysis results, generates instructions to provide the cat with appropriate reactions and stimuli.

Input: Behavioral pattern analysis results.

Output: Instructions to the device.

Specific operation: The server generates an instruction to "rotate the device to attract the cat's attention" and sends it to the device.

Step 6:

Device Operation

Device: Operates according to instructions from the server and provides appropriate reactions and stimuli to the cat.

Input: Instructions from the server.

Output: Device operation.

Specific action: The device will start to rotate and act in a way that will attract the cat's interest.

Step 7:

User emotion recognition

Device: Collect data to recognize the user's emotions. For example, use the smartphone's camera and microphone.

Input: User's facial expression and tone of voice.

Output: Emotion data.

Specific operation: The device analyzes the user's facial expressions and tone of voice to recognize their emotional state.

Step 8:

Adjusting instructions based on emotions

Server: Receives the user's emotional data and adjusts the cat's reactions and stimuli.

Input: Emotion data.

Output: Adjusted instructions.

Specific behavior: If the server recognizes that the user is happy, it sends instructions to the generative AI model to encourage active play. The device then behaves as if it is running around with a cat.

(Application Example 1)

Next, we will explain Application Example 1 of Form Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Previous pet devices simply detected animal behavior patterns and were unable to deeply understand the animal's preferences or play styles. Furthermore, they lacked the ability to adjust interactions with the animal based on the user's emotional state, making it difficult to provide interactions with the pet that best fit the user's emotional state. Furthermore, they lacked a way to control the device or display animal behavior data in real time, making it difficult for users to understand the device's operating status and the animal's behavior.

The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavioral patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, means for recognizing the user's emotional state using an emotion engine and adjusting the reactions and stimuli provided to the animal in accordance with the emotional state, and means for displaying the device's operation and the animal's behavioral data on the information terminal. This makes it possible to deeply understand the animal's behavioral patterns and provide optimal interactions with the pet in accordance with the user's emotional state.

A "spherical device capable of moving freely" is a spherical device that has an internal motor and battery and can move autonomously based on external instructions.

An "information terminal" is an electronic device, such as a smartphone or tablet, that is operated by the user to control the device.

A "sensor that detects animal movements and behavior patterns" is a device that detects an animal's location, speed, movements, etc. in real time and collects that data.

"Generative AI" is an artificial intelligence system that analyzes collected data and understands animals' preferences and play styles.

The "emotion engine" is a system that recognizes the user's emotional state and adjusts interactions with animals based on that information.

"Means for providing appropriate reactions and stimuli to animals" refers to a mechanism that allows appropriate actions and reactions to be taken by animals based on the analysis results of the generative AI.

"Means for displaying the device's operation and animal behavior data on an information terminal" refers to a function for displaying the device's operating status and animal behavior data on an information terminal in real time.

A system for implementing this invention includes a spherical, freely movable device, an information terminal, a sensor that detects animal movements and behavior patterns, a generative AI, an emotion engine, and a means for displaying on the information terminal.

System Configuration

1. Spherical device:

It is equipped with a motor and battery inside and moves autonomously based on external instructions.

Equipped with sensors to detect animal movements and behavior patterns.

2. Information terminal:

Electronic devices operated by users, such as smartphones and tablets.

Displays device operation and animal behavior data in real time.

3. Sensor:

It detects animals' location, speed, movements, etc. in real time and collects that data.

4. Generative AI:

Analyze the collected data to understand the animals' preferences and play styles.

Generative AI models are used to generate instructions to provide appropriate reactions and stimuli to animals.

5. Emotion Engine:

Recognizes the user's emotional state and adjusts interactions with animals based on that information.

6. Display means:

Device operation status and animal behavior data are displayed on the information terminal.

Program processing explanation

The server first collects animal behavior data from sensors. This data is sent to the generative AI, which analyzes the animal's preferences and play styles. Based on the analysis results, the generative AI generates instructions to provide the animal with appropriate reactions and stimuli. Furthermore, an emotion engine recognizes the user's emotional state and adjusts interactions with the animal based on that information. Finally, device operations and animal behavior data are displayed in real time on the information terminal.

Specific examples

For example, if this system were used in a pet shop, when a customer was playing with a cat, the smartphone app would analyze the cat's behavior in real time and adjust how the customer interacted with the cat depending on the customer's emotional state. An example of a prompt sentence to be input into the generative AI model is as follows:

Example prompt:

Cat behavior data: Movement: Active, Play style: Chasing a ball

User's emotional state: State: Happy

Based on this data, generate instructions to provide appropriate reactions and stimuli for your cat.

By inputting this prompt into a generative AI model, we can obtain appropriate reactions and stimulation instructions for the cat.

The flow of the specific processing in Application Example 1 is explained using Figure 18.

Step 1:

The server obtains animal behavior data from sensors. The sensors detect the animal's position, speed, movement, etc. in real time and send the data to the server. The input is raw data from the sensors, and the output is the animal's behavior data sent to the server.

Step 2:

The server sends the acquired animal behavior data to the generative AI. The generative AI analyzes the received data and understands the animal's preferences and play styles. The input is the animal's behavior data, and the output is the analysis results regarding the animal's preferences and play styles.

Step 3:

The server generates instructions to provide appropriate reactions and stimuli to the animal based on the analysis results from the generative AI. It uses the generative AI model to create prompts and generate specific instructions for the animal. The input is the analysis results of the generative AI, and the output is instructions for the animal.

Step 4:

The server uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes data such as the user's facial expressions and voice to identify the user's emotional state. The input is the user's emotional data, and the output is the user's emotional state.

Step 5:

The server adjusts the reactions and stimuli given to the animal based on the user's emotional state. Based on the output of the emotion engine, it modifies the instructions of the generative AI to provide optimal interaction. The input is the user's emotional state and the instructions of the generative AI, and the output is the adjusted instructions given to the animal.

Step 6:

The server sends the adjusted instructions to the spherical device. The device acts based on the received instructions and provides the animal with an appropriate reaction or stimulus. The input is the adjusted instructions, and the output is the device's behavior.

Step 7:

The terminal displays device operation and animal behavior data in real time. Users can check the device's operating status and the animal's behavior through the information terminal. The input is device operation data and animal behavior data, and the output is the information displayed on the information terminal.

(Example 2)

Next, Example 2 of Form Example 2 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Previous animal devices struggled to provide appropriate responses to animal behavior and were unable to realize interactions that took the user's emotional state into account. This made it difficult to provide an optimal experience for both the animal and the user. Furthermore, there was a lack of systems that could learn changes in the animal's behavioral patterns and adapt over the long term.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

In this invention, the server includes means for operating a spherical, freely mobile device, means for using sensors to detect the animal's movements and behavioral patterns, means for using generative AI to analyze data from the sensors and understand the animal's preferences and play styles, means for using an emotion engine to recognize the user's emotional state, and means for optimizing interactions with the animal based on the generative AI and emotion engine. This makes it possible to provide appropriate responses to the animal's behavior and enable interactions that take the user's emotional state into consideration. It also makes it possible to learn changes in the animal's behavioral patterns and adapt over the long term.

A "device" is a spherical piece of equipment that can move freely.

An "information terminal" is an electronic device that provides a means for operating a device.

A "sensor" is a device that detects animal movements and behavior patterns.

"Generative AI" is artificial intelligence that analyzes data from sensors and understands animals' preferences and how they play.

An "emotion engine" is software or hardware that recognizes the user's emotional state.

"Reactions" are appropriate responses or stimuli provided to animals based on generative AI.

"Interaction optimization" refers to optimizing the interaction between animals and users based on generative AI and an emotion engine.

"Behavioral data" is information about animal movements and behavior patterns.

"Feedback" means that the device automatically responds to physical stimuli from the animal and transmits that response to the generative AI.

This invention is a system that provides optimal interaction based on the animal's behavior and the user's emotional state. Specific embodiments of this system are described below.

Hardware and software used

Device: A spherical, freely movable device that provides physical responses to the animal's behavior.

Information terminal: An electronic device that provides a means for operating a device. Examples include smartphones and tablets.

Sensor: A device that detects animal movements and behavior patterns. It is installed in the device and collects data in real time.

Generative AI: Artificial intelligence that analyzes data from sensors to understand animals' preferences and play styles. An example of this is OpenAI's GPT-4.

Emotion engine: Software or hardware that recognizes the user's emotional state. It analyzes the user's tone of voice, facial expressions, or physical reactions.

System Operation

The server receives the animal's behavior data sent from the sensor and analyzes it using generative AI. The generative AI understands the animal's behavioral patterns and sends instructions to the device to provide appropriate reactions and stimuli.

Furthermore, the server uses an emotion engine to recognize the user's emotional state. The emotion engine analyzes the user's tone of voice and facial expressions to determine whether the user is happy or sad. The server optimizes interactions with the animal based on this emotional state.

Specific examples

For example, if a cat scratches the device, the sensor detects the action. The sensor sends the data to a server, which analyzes the data using generative AI. The generative AI understands that the cat prefers aggressive play and instructs the device to move a cat toy. The device follows this instruction to move the cat toy and provide the cat with the appropriate stimulation.

At the same time, the server uses its emotion engine to recognize the user's smile and determine that the user is happy. The server then encourages the cat to play actively depending on the user's emotional state.

Example prompt

"What should I do if my cat is acting aggressively towards my device?"

"Please tell me what kind of play should I encourage the cat to do when the user is smiling?"

This system enables optimal interaction based on the emotional state of the animal and the user.

The flow of the identification process in Example 2 will be explained using Figure 19.

Step 1:

Data collection using sensors

The server monitors the animal's behavior in real time using sensors installed on the device. The sensors detect any aggressive behavior from the animal toward the device. For example, if a cat digs its claws into the device, the sensor detects this behavior. The input is the animal's behavior data, and the output is the detected behavior data.

Step 2:

Data transmission

The sensor sends the detected behavioral data to the server. The server receives this data and passes it on to the generative AI. The input is the behavioral data sent from the sensor, and the output is the behavioral data sent to the server.

Step 3:

Analysis using generative AI

The server uses generative AI to analyze the behavioral data it receives. The generative AI uses, for example, OpenAI's GPT-4, to understand that animals prefer aggressive play. Specifically, it analyzes the behavioral data and determines that the behavior constitutes aggressive play. The input is the behavioral data sent to the server, and the output is the analysis results.

Step 4:

Device instructions

The server issues instructions to the device based on the analysis results of the generative AI. For example, it instructs the device to move a cat toy. The device follows this instruction to move the cat toy and provide the cat with appropriate stimulation. The input is the analysis results of the generative AI, and the output is the instruction to the device.

Step 5:

Recognize user emotions using an emotion engine

The server uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's tone of voice, facial expressions, or physical reactions. For example, if the user is smiling, the emotion engine recognizes that the user is happy. The input is the user's emotion data, and the output is the emotion recognition result.

Step 6:

Cat interaction optimization

The server optimizes interactions with animals according to the user's emotional state. For example, if the user is smiling, it encourages the animal to play actively. Conversely, if the user is crying, it encourages the animal to play quietly. This allows for optimal interaction with animals according to the user's emotional state. The input is the emotion recognition result, and the output is instructions for optimized interactions.

(Application Example 2)

Next, we will explain Application Example 2 of Form Example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Previous pet devices struggled to provide interactions that fully took into account the animal's behavior and the user's emotional state. Furthermore, they lacked a means to provide appropriate stimuli based on the animal's behavioral patterns and the user's emotions, making it difficult to increase satisfaction for both the pet and the user.

The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing the animal with appropriate reactions and stimuli based on the AI, an emotion engine that recognizes the user's emotional state, and means for adjusting interactions with the animal based on the emotion engine. This enables appropriate interactions that take into account the animal's behavior and the user's emotional state in real time.

A "spherical, freely movable device" is a device that has a spherical shape and can physically move freely.

An "information terminal" is an electronic device operated by a user, such as a smartphone or tablet.

A "sensor that detects animal movements and behavior patterns" is a device that detects animal movements and behavior in real time.

"Generative AI" is an artificial intelligence system that analyzes collected data and understands animals' preferences and behavioral patterns.

"Means for providing appropriate reactions and stimuli" refers to devices and methods for providing appropriate reactions and stimuli to animals based on the analysis results of the generative AI.

The "emotion engine" is a system that recognizes emotions from the user's tone of voice, facial expressions, and physical reactions.

"Means for adjusting interactions with animals" refers to devices and methods for optimizing interactions with animals based on the recognition results of the emotion engine.

This invention is a system that takes into account the animal's behavior and the user's emotional state in real time to provide appropriate interaction. Below, we will show a specific embodiment for realizing this system.

System Configuration

The system consists of the following main components:

1. A spherical, freely movable device:

This device is a spherical device that can be moved freely to induce animal behavior. It is equipped with a motor and battery inside and operates according to instructions from an information terminal.

2. Information terminal:

Electronic devices such as smartphones and tablets that provide an interface for users to operate the device. Dedicated applications are installed on them to control the device's operation.

3. Sensors that detect animal movements and behavior patterns:

The device is equipped with a camera and accelerometer to detect animal movements and behavior in real time.

4. Generation AI:

It is an artificial intelligence system that analyzes collected data to understand animals' preferences and behavioral patterns. Generative AI accumulates animal behavioral data over time and learns changes in behavioral patterns based on that data.

5. How to provide appropriate reactions and stimuli:

This is a device or method for providing appropriate responses or stimuli to animals based on the analysis results of generative AI. For example, the device may stimulate the animal by performing a specific movement.

6. Emotion Engine:

This is a system that recognizes emotions from the user's tone of voice, facial expressions, and physical reactions. The emotion engine detects the user's emotional state in real time through the camera and microphone.

7. Ways to regulate interactions with animals:

An apparatus and method for optimizing interactions with animals based on the recognition results of an emotion engine. For example, if the user is recognized as sad, the device will behave calmly.

Program processing explanation

The server detects the user's emotional state through a camera and microphone and sends it to the generative AI. The generative AI analyzes the animal's behavioral data and the user's emotional data to determine an appropriate reaction. The information terminal receives instructions from the generative AI and instructs the device on how to act.

The hardware used includes a camera (to detect animal behavior and the user's facial expressions), a microphone (to detect the user's tone of voice), and a motor (to control the device's movement). The software includes OpenCV (image processing), Keras (emotion recognition model), and requests (communication with AI services).

Specific examples

For example, if a user comes into the store with a smiling face and a pet, the emotion engine will recognize that the user is happy. The generative AI will analyze the animal's behavioral data and the user's emotional data and instruct the device to behave in a way that encourages active play. Conversely, if the user looks sad, the device will be instructed to behave calmly.

Example prompt

"If the user's emotion is 'happy' and the animal's behavior is 'aggressive,' we will provide a toy that encourages active play with the animal."

The flow of the specific processing in Application Example 2 is explained using Figure 20.

Step 1:

The server captures the user's facial expressions and tone of voice in real time through a camera and microphone. It receives camera footage and audio data as input. It preprocesses this data using OpenCV and audio processing libraries to extract the user's facial features and tone of voice. It generates data indicating the user's emotional state as output.

Step 2:

The server uses an emotion engine to analyze the user's emotional state data obtained in step 1. It uses facial feature points and voice tone data as input. The emotion engine inputs this data into an emotion recognition model (using Keras) and classifies the user's emotions into categories such as "happy" or "sad." As an output, it generates a label indicating the user's emotional state.

Step 3:

The terminal acquires animal behavior data in real time through sensors installed on the device. As input, it receives data from the sensors (acceleration, location information, etc.). It preprocesses this data to extract the animal's movements and behavioral patterns. As output, it generates data indicating the animal's behavioral state.

Step 4:

The server uses generative AI to integrate and analyze the user's emotional state data obtained in step 2 and the animal's behavior data obtained in step 3. The user's emotional state data and the animal's behavior data are used as input. The generative AI determines appropriate reactions and stimuli for the animal based on this data. As output, it generates operational instructions for the device.

Step 5:

The terminal sends the operation instructions generated in step 4 to the device. As input, it receives operation instruction data from the generative AI. The terminal transmits these instructions to the device's motor control system, controlling the device to perform the appropriate operation. As output, the device's physical operation is executed.

Step 6:

The device automatically responds to physical stimuli from the animal and feeds that response back to the generative AI as animal behavior data. As input, it receives physical stimulus data from the animal. The device detects this data with sensors and sends it to the generative AI. As output, the animal's behavior data is updated.

Step 7:

The server re-analyzes the animal's behavior data updated in step 6 and learns changes in the animal's behavior patterns. It uses the updated animal's behavior data as input. The generative AI accumulates this data and learns changes in the animal's behavior patterns. As output, it generates new movement instructions based on the animal's behavior patterns.

(Example 3)

Next, Example 3 of Form Example 3 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Previous animal devices struggled to provide appropriate reactions and stimuli based on the animal's behavioral patterns and the user's emotional state. Furthermore, they lacked the ability to accumulate animal behavioral data over time and learn from changes in that data, making it impossible to respond appropriately to the animal's interests and preferences. Furthermore, the device's movements and responses were not adjusted to take the user's emotional state into account, resulting in suboptimal interactions between the user and the animal.

The specific processing by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means. In this invention, the server includes a spherical device that can move freely around, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, an emotion engine for analyzing the user's emotional state, and means for adjusting the device's movements and reactions based on the analysis results of the emotion engine. This makes it possible to provide appropriate reactions and stimuli in response to changes in the animal's behavior patterns, enabling optimal interaction according to the user's emotional state.

A "device" is a spherical piece of equipment that can move freely.

An "information terminal" is an electronic device that provides a means for operating a device.

A "sensor" is a device used to detect animal movements and behavior patterns.

"Generative AI" is artificial intelligence that analyzes data from sensors and understands animals' preferences and play styles.

An "emotion engine" is software or hardware for analyzing a user's emotional state.

A "reaction" is an appropriate response or stimulus provided to an animal.

"Animal behavior data" is information about animal movements and behavior patterns.

"User's emotional state" refers to the emotional state the user is feeling.

This invention is a system that analyzes animal behavior data and the user's emotional state to provide optimal interaction. A specific embodiment of this system is described below.

System Configuration

The system consists of the following main components:

1. Device: A spherical, freely movable device. The device is equipped with sensors to detect animal movements and behavior patterns.

2. Information terminal: An electronic device that provides a means for operating a device. Examples include smartphones and tablets.

3. Server: The central component that receives and analyzes data from devices and information terminals.

4. Generative AI: Artificial intelligence that analyzes data from sensors and understands animals' preferences and play styles.

5. Emotion engine: Software or hardware for analyzing the user's emotional state.

Data collection and analysis

The server collects animal behavior data from sensors installed on the device. For example, a camera tracks a cat's movements and a sensor detects which objects the cat touches. The collected data is stored in a database.

Generative AI analyzes accumulated behavioral data and learns the behavioral patterns of animals. For example, it learns that cats become active at 8am every morning and that they prefer certain toys. Based on this learning, it issues appropriate instructions to the device.

User sentiment analysis and device adjustment

The device uses a camera and microphone to analyze the user's emotional state. For example, it analyzes the user's facial expressions and tone of voice to determine whether the user is angry or happy.

The server adjusts the device's movements and reactions based on the analysis results of the emotion engine. For example, when the user is angry, the device's movements will be suppressed so that the animal can remain quiet. Conversely, when the user is happy, the device's movements will be more active so that the user can play with the animal.

Specific examples

For example, if a cat initially likes chasing laser pointers, but after a few weeks starts to prefer rolling a ball, the generative AI will learn this change and instruct the cat to move the ball-rolling device more frequently.

Also, when the user comes home from work and is tired, the emotion engine detects the user's fatigue and reduces the device's activity so that the cat can stay quiet. Conversely, when the user is relaxing on a day off, the device's activity will be more active so that the user can play with the cat.

Example prompt

"Please explain the generative AI program that accumulates cat behavior data and learns changes in behavior patterns."

"Please explain how the emotion engine works, adjusting the device's behavior and responses based on the user's emotions."

In this way, the system utilizes animal behavior data and user emotion data to provide optimal interaction. The flow of the identification process in Example 3 is explained using Figure 21.

Step 1:

The server collects animal behavior data from sensors installed on the device. As input, it receives real-time data from the sensors and, as output, generates data on the animal's movements and behavior patterns. Specifically, the camera tracks the cat's movements and the sensor detects which objects the cat touches.

Step 2:

The server stores the collected behavioral data in a database. As input, it receives the animal behavioral data generated in step 1, and as output, it stores the time-stamped behavioral data in the database. Specifically, it records the data "October 1, 2023, 08:00:00 - Cat chases laser pointer."

Step 3:

Generative AI analyzes accumulated behavioral data and learns animal behavior patterns. It receives behavioral data stored in a database as input and generates learning results about the animal's behavior patterns as output. Specifically, it learns the pattern of "chasing a laser pointer every morning at 8 o'clock."

Step 4:

The server issues instructions to the device based on the learning results of the generative AI. It receives the learning results of the generative AI as input and generates specific instructions for the device as output. Specifically, it issues the instruction "move the laser pointer at 8 o'clock every morning."

Step 5:

The device uses a camera and microphone to analyze the user's emotional state. As input, it receives data related to the user's facial expressions and tone of voice, and as output, it generates an analysis result related to the user's emotional state. Specifically, if the user is smiling while speaking, it is determined that they are happy.

Step 6:

The server adjusts the device's movements and reactions based on the analysis results of the emotion engine. It receives the user's emotion analysis results as input and generates specific instructions regarding the device's movements and reactions as output. Specifically, when the user is angry, the device's movements are suppressed so that the animal can remain quiet. Conversely, when the user is happy, the device's movements are made more active so that the user can play with the animal.

(Application Example 3)

Next, we will explain Application Example 3 of Form Example 3. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 will be referred to as the "terminal."

Previous pet interaction systems struggled to provide appropriate reactions and stimuli based on changes in animal behavior patterns and the user's emotional state. Furthermore, they lacked the ability to provide real-time advice on how users should interact with animals, making it difficult to achieve optimal interactions with animals.

The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes a spherical, freely mobile device, means for operating the device from an information terminal, a sensor mounted on the device that detects the animal's movements and behavior patterns, generative AI that analyzes data from the sensor and understands the animal's preferences and play styles, means for providing appropriate reactions and stimuli to the animal based on the AI, an emotion engine that senses the user's emotional state and adjusts the device's movements and reactions, and means for advising the user on optimal interactions with the animal. This makes it possible to provide appropriate reactions and stimuli in response to changes in the animal's behavior patterns, and to achieve optimal interactions according to the user's emotional state.

A "spherical, freely movable device" is a device that has a spherical shape and the ability to physically move freely.

An "information terminal" is an electronic device operated by a user, such as a smartphone or tablet.

A "sensor that detects animal movements and behavior patterns" is a device that detects animal movements and behavior in real time and collects that data.

"Generative AI" is artificial intelligence that learns animal behavior patterns based on collected data and generates appropriate reactions and stimuli.

"Means for providing appropriate reactions and stimuli" is a function that provides appropriate reactions and stimuli to animals based on the results of learning by the generative AI.

An "emotion engine" is a system that senses the user's emotional state and adjusts the device's behavior and responses accordingly.

"Means for advising optimal interactions" is a function that provides real-time instructions to users on how best to interact with and play with animals.

A system for implementing this invention has the following configuration:

First, a spherical, freely movable device is required. This device is equipped with sensors that detect the animal's movements and behavior patterns. The sensors detect the animal's movements and behavior in real time and collect that data.

Next, you need an information terminal. An information terminal is an electronic device that users can operate, such as a smartphone or tablet. You can operate the device through this information terminal.

The collected data is analyzed by generative AI, which accumulates data on the animal's behavior over time and learns changes in the animal's behavior patterns based on that accumulated data. This makes it possible to understand the animal's preferences and play styles, and provide appropriate reactions and stimulation.

Furthermore, the emotion engine senses the user's emotional state. The emotion engine adjusts the device's movements and responses according to the user's emotional state. For example, it increases the device's movements when the user is happy, and reduces the device's movements when the user is angry.

Finally, it includes a way to advise users on optimal interactions with animals, allowing them to know in real time how to interact with animals.

For example, if the user types "happy," the system will advise, "Play with your cat more!". Also, if the user types "angry," the system will advise, "Let's give your cat a break."

Example prompts are as follows:

Enter the user's emotion (happy, angry, neutral): happy

In this way, it is possible to provide appropriate reactions and stimuli in response to changes in the animal's behavioral patterns, achieving optimal interaction according to the user's emotional state.

The flow of the specific processing in Application Example 3 is explained using Figure 22.

Step 1:

The user operates the information terminal and starts the device. As input, the user starts the information terminal's application and turns on the device. As output, the device starts operating and the sensor begins to detect animal movement.

Step 2:

Sensors detect animal movements and behavior patterns in real time and collect the data. The animal's movements and behavior are detected by the sensors as input. The collected data is sent to the generative AI as output.

Step 3:

Generative AI analyzes the collected data and learns the animal's behavioral patterns. The input is the animal's behavioral data transmitted from the sensors. The output is the generation of appropriate reactions and stimulus instructions based on changes in the animal's behavioral patterns.

Step 4:

The emotion engine senses the user's emotional state. As input, the user enters their emotional state into the information terminal. As output, the emotion engine analyzes the user's emotional state and sends the results to the generative AI.

Step 5:

The generative AI adjusts the device's movements and responses based on the user's emotional state. The input is data on the user's emotional state sent from the emotion engine. The output is the device's movements and responses adjusted according to the user's emotional state.

Step 6:

Advises the user on optimal interactions with animals. Inputs include instructions from the generative AI and data on the user's emotional state. Outputs include advice on optimal interactions with animals displayed on the information terminal screen.

Step 7:

The user interacts with the animal according to the advice. The input is the advice displayed on the information terminal. The output is that the user's appropriate interaction with the animal changes the animal's behavioral patterns, and the sensor again collects that data.

This series of processing steps makes it possible to provide appropriate reactions and stimuli in response to changes in the animal's behavioral patterns, achieving optimal interaction according to the user's emotional state.

The specific processing unit 290 transmits the results of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the results of the specific processing. The microphone 238 acquires audio indicating the user input regarding the results of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

Data generation model 58 is what is known as generative AI (artificial intelligence). An example of data generation model 58 is generative AI such as ChatGPT (Internet search <URL: https://openai.com/blog/chatgpt>). Data generation model 58 is obtained by performing deep learning on a neural network. A prompt containing an instruction is input to data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. Data generation model 58 performs inference on the input inference data in accordance with the instructions indicated by the prompt, and outputs the inference results in the form of data such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and/or summarization.

Another example of generative AI is Gemini (Internet search <URL: https://gemini.google.com/?hl=ja>).

In the above embodiment, an example was given in which the specific processing was performed by the data processing device 12, but the technology disclosed herein is not limited to this, and the specific processing may also be performed by the robot 414.

The emotion identification model 59, which serves as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see Figure 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

Figure 9 shows an emotion map 400 on which multiple emotions are mapped. In emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both emotions and mental states. Emotions that are generally generated from reactions that occur in the brain are arranged on the left side of the concentric circles. Emotions that are generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions that are generally generated from reactions that occur in the brain and are induced by situational judgment are arranged above and below the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the top side of the concentric circles, and the emotion of "discomfort" is arranged on the bottom side. In this way, emotion map 400 maps multiple emotions based on the structure by which emotions are generated, with emotions that tend to occur simultaneously being mapped close together.

These emotions are distributed in the 3 o'clock direction on emotion map 400, and usually fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness takes precedence over internal sensations, resulting in a sense of calm.

The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further out you go on emotion map 400, the more visible (expressed in behavior) the emotion becomes.

Here, human emotions are based on various balances such as posture and blood sugar levels, and when these balances deviate from the ideal, it indicates discomfort, and when they approach the ideal, it indicates pleasure. Emotions can also be created for robots, cars, motorcycles, etc., based on various balances such as posture and remaining battery life, so that when these balances deviate from the ideal, it indicates discomfort, and when they approach the ideal, it indicates pleasure. Emotion maps may be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and emotional brain physiological signal analysis systems, Tokushima University, doctoral dissertation: https://ci.nii.ac.jp/naid/500000375379). The left half of the emotion map is lined with emotions belonging to an area called "reaction," where sensation is dominant. The right half of the emotion map is lined with emotions belonging to an area called "situation," where situational awareness is dominant.

The emotion map defines two emotions that encourage learning. One is the negative emotion around the middle of "repentance" or "reflection" on the situation side. In other words, this is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the positive emotion around "desire" on the response side. In other words, this is when the robot experiences positive feelings such as "I want more" or "I want to know more."

The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are close to each other have similar values, as in the emotion map 900 shown in Figure 10. Figure 10 shows an example in which multiple emotions, such as "relieved," "calm," and "reassuring," have similar emotion values.

In the above embodiment, an example was given in which a specific process is performed by a single computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may also be performed by multiple computers, including computer 22.

In the above embodiment, an example was described in which the specific processing program 56 is stored in the storage 32, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

It is not necessary to store the entire specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entire specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

The following types of processors can be used as hardware resources for executing specific processes. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource for executing specific processes by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which are processors with a circuit configuration designed specifically for executing specific processes. All processors have built-in or connected memory, and all use the memory to execute specific processes.

The hardware resource that executes the specific processing may be composed of one of these various processors, or may be composed of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). The hardware resource that executes the specific processing may also be a single processor.

As an example of a configuration using a single processor, first, there is a configuration in which one processor is configured using a combination of one or more CPUs and software, and this processor functions as a hardware resource that executes specific processing. Second, there is a configuration in which a processor is used to realize the functions of an entire system, including multiple hardware resources that execute specific processing, on a single IC chip, as typified by SoC (System-on-a-chip). In this way, specific processing is realized using one or more of the various processors listed above as hardware resources.

More specifically, the hardware structure of these various processors can be an electrical circuit that combines circuit elements such as semiconductor devices. Furthermore, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps can be added, or the processing order can be rearranged, all within the scope of the spirit of the invention.

The above-described written content and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above explanation of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or substitutions may be made to the above-described written content and illustrations, as long as they do not deviate from the spirit of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described written content and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

All publications, patent applications, and technical standards mentioned in this specification are incorporated by reference herein to the same extent as if each individual publication, patent application, and technical standard was specifically and individually indicated to be incorporated by reference.

The following is further disclosed regarding the above embodiments.

(Claim 1)

A system comprising a spherical, freely mobile device, a means for operating the device from a smartphone, a sensor installed in the device that detects the cat's movements and behavior patterns, generative AI that analyzes data from the sensor to understand the cat's preferences and play styles, and a means for providing the cat with appropriate reactions and stimuli based on the AI.

(Claim 2)

The system described in claim 1, characterized in that the generative AI accumulates cat behavior data over time and learns changes in the cat's behavior patterns based on the accumulated data.

(Claim 3)

The system described in claim 1, characterized in that the device automatically responds to physical stimuli from the cat and feeds that response back to the generative AI as cat behavior data.

(Claim 4)

The system described in claim 1, characterized in that the generative AI further combines an emotion engine that recognizes the user's emotions and adjusts the reactions and stimuli toward the cat according to the user's emotions.

(Claim 5)

The system of claim 4, wherein the emotion engine recognizes emotions from the user's tone of voice, facial expressions, or physical reactions.

(Claim 6)

The system described in claim 4, characterized in that the emotion engine adjusts the device's movements and reactions according to the user's emotions, thereby improving interaction between the user and the cat.

"Example 1"

(Claim 1)

A spherical device that can move freely,
means for operating the device from an information terminal;
a sensor mounted on the device that detects animal movements and behavior patterns;
A generative AI that analyzes data from the sensors and understands the animal's preferences and play styles.
A means for providing an appropriate reaction or stimulus to the animal based on the artificial intelligence;
means for generating instructions for controlling the operation of the device and transmitting the instructions to the device;
means for the device to operate in accordance with the instructions and provide an appropriate reaction or stimulus to the animal;
A system including:

(Claim 2)

The system described in claim 1, characterized in that the generative artificial intelligence accumulates animal behavior data over time and learns changes in the animal's behavior patterns based on the accumulated data.

(Claim 3)

The system described in claim 1, characterized in that the device automatically responds to physical stimuli from the animal and feeds that response back to the generative artificial intelligence as animal behavior data.

"Application Example 1"

(Claim 1)

A spherical device that can move freely,
means for operating the device from a smartphone;
a sensor mounted on the device that detects animal movements and behavior patterns;
A generative AI that analyzes data from the sensors and understands the animal's preferences and play styles;
A means for providing an appropriate reaction or stimulus to the animal based on the AI;
The system includes a means for the device to detect animal movements within a physical store and provide appropriate reactions and play using generative AI.

(Claim 2)

The system described in claim 1, characterized in that the generative AI accumulates animal behavior data over time and learns changes in the animal's behavior patterns based on the accumulated data.

(Claim 3)

The system described in claim 1, characterized in that the device automatically responds to physical stimuli from the animal and feeds that response back to the generative AI as animal behavior data.

"Example 2"

(Claim 1)

a sensor means for detecting cat activity;
terminal means for transmitting data from the sensor means to a server;
means for analyzing data using a generative AI model in the server means;
device means for providing stimuli to the cat based on instructions from the server means;
terminal means for controlling the device means;
A system including:

(Claim 2)

The system described in claim 1, characterized in that the generative AI model accumulates cat behavior data over time and learns changes in the cat's behavior patterns based on the accumulated data.

(Claim 3)

The system described in claim 1, characterized in that the device means automatically responds to physical stimuli from the cat and feeds back the response to the generative AI model as cat behavior data.

"Application Example 2"

(Claim 1)

A spherical device that can move freely,
means for operating the device from an information terminal;
a sensor mounted on the device that detects animal movements and behavior patterns;
A generative AI that analyzes data from the sensors and understands the animal's preferences and play styles;
A means for providing an appropriate reaction or stimulus to the animal based on the AI;
Sensors that detect abnormal behavior of workers and machines in factories,
means for transmitting data from the sensors to a generative AI for analyzing abnormal behavior;
The system includes a means for instructing an appropriate response based on the analysis results.

(Claim 2)

The system described in claim 1, characterized in that the generative AI accumulates animal behavior data over time and learns changes in the animal's behavior patterns based on the accumulated data.

(Claim 3)

The system described in claim 1, characterized in that the device automatically responds to physical stimuli from the animal and feeds that response back to the generative AI as animal behavior data.

"Example 3"

(Claim 1)

A spherical device that can move freely,
means for operating the device from a personal digital assistant;
a sensor mounted on the device that detects animal movements and behavior patterns;
A generative AI that analyzes data from the sensors and understands the animal's preferences and play styles.
A means for providing an appropriate reaction or stimulus to the animal based on the artificial intelligence;
means for storing the data in a database;
means for cleansing the data and extracting behavioral patterns;
means for the artificial intelligence to learn changes in behavioral patterns;
means for generating appropriate instructions based on the learning results;
and means for operating the device based on the instructions.

(Claim 2)

The system described in claim 1, characterized in that the generative artificial intelligence accumulates animal behavior data over time and learns changes in the animal's behavior patterns based on the accumulated data.

(Claim 3)

The system described in claim 1, characterized in that the device automatically responds to physical stimuli from the animal and feeds that response back to the generative artificial intelligence as animal behavior data.

"Application Example 3"

(Claim 1)

A spherical device that can move freely,
means for operating the device from a smartphone;
a sensor mounted on the device that detects animal movements and behavior patterns;
A generative AI that analyzes data from the sensors to understand the preferences and behavioral patterns of animals;
A means for providing an appropriate reaction or stimulus to the animal based on the AI;
A system that accumulates data on worker behavior over time, learns changes in behavior patterns based on the accumulated data, and provides appropriate support.

(Claim 2)

The system described in claim 1, characterized in that the generative AI accumulates animal behavioral data over time and learns changes in behavioral patterns based on the accumulated data.

(Claim 3)

The system described in claim 1, characterized in that the device automatically responds to physical stimuli from the animal and feeds that response back to the generative AI as animal behavior data.

"Example 1: Combining Emotion Engines"

(Claim 1)

A spherical device that can move freely,
means for operating the device from an information terminal;
a sensor mounted on the device that detects animal movements and behavior patterns;
A generative AI that analyzes data from the sensors and understands the animal's preferences and play styles.
A means for providing appropriate reactions and stimuli to animals based on the AI;
The system includes an emotion engine that recognizes the user's emotions and adjusts the reactions and stimuli of the animal accordingly.

(Claim 2)

The system described in claim 1, characterized in that the generative AI accumulates animal behavior data over time and learns changes in the animal's behavior patterns based on the accumulated data.

(Claim 3)

The system described in claim 1, characterized in that the device automatically responds to physical stimuli from the animal and feeds that response back to the generative AI as animal behavior data.

"Application example 1: Combining emotion engines"

(Claim 1)

A spherical device that can move freely,
means for operating the device from an information terminal;
a sensor mounted on the device that detects animal movements and behavior patterns;
A generative AI that analyzes data from the sensors and understands the animal's preferences and play styles;
A means for providing an appropriate reaction or stimulus to the animal based on the AI;
means for recognizing the emotional state of the user using an emotion engine and adjusting reactions and stimuli for the animal in accordance with the emotional state;
A means for displaying the device operation and animal behavior data on an information terminal.

A system including

(Claim 2)

The system described in claim 1, characterized in that the generative AI accumulates animal behavior data over time and learns changes in the animal's behavior patterns based on the accumulated data.

(Claim 3)

The system described in claim 1, characterized in that the device automatically responds to physical stimuli from the animal and feeds that response back to the generative AI as animal behavior data.

"Example 2: Combining Emotion Engines"

(Claim 1)

A spherical device that can move freely,
means for operating the device from an information terminal;
a sensor mounted on the device that detects animal movements and behavior patterns;
A generative AI that analyzes data from the sensors and understands the animal's preferences and play styles.
A means for providing appropriate reactions and stimuli to animals based on the AI;
an emotion engine that recognizes the user's emotional state;
The system includes means for optimizing interaction with the animal based on the emotion engine.

(Claim 2)

The system described in claim 1, characterized in that the generative AI accumulates animal behavior data over time and learns changes in the animal's behavior patterns based on the accumulated data.

(Claim 3)

The system described in claim 1, characterized in that the device automatically responds to physical stimuli from the animal and feeds that response back to the generative AI as animal behavior data.

"Application Example 2: Combining Emotion Engines"

(Claim 1)

A spherical device that can move freely,
means for operating the device from an information terminal;
a sensor mounted on the device that detects animal movements and behavior patterns;
A generative AI that analyzes data from the sensors and understands the animal's preferences and play styles;
A means for providing an appropriate reaction or stimulus to the animal based on the AI;
an emotion engine that recognizes the user's emotional state;
means for adjusting an interaction with an animal based on the emotion engine;

A system including

(Claim 2)

The system described in claim 1, characterized in that the generative AI accumulates animal behavior data over time and learns changes in the animal's behavior patterns based on the accumulated data.

(Claim 3)

The system described in claim 1, characterized in that the device automatically responds to physical stimuli from the animal and feeds that response back to the generative AI as animal behavior data.

"Example 3: Combining Emotion Engines"

(Claim 1)

A spherical device that can move freely,
means for operating the device from an information terminal;
a sensor mounted on the device that detects animal movements and behavior patterns;
A generative AI that analyzes data from the sensors and understands the animal's preferences and play styles.
A means for providing appropriate reactions and stimuli to animals based on the AI;
an emotion engine for analyzing the user's emotional state;
means for adjusting the behavior and response of the device based on the analysis results of the emotion engine;
A system including:

(Claim 2)

The system described in claim 1, characterized in that the generative AI accumulates animal behavior data over time and learns changes in the animal's behavior patterns based on the accumulated data.

(Claim 3)

The system described in claim 1, characterized in that the device automatically responds to physical stimuli from the animal and feeds that response back to the generative AI as animal behavior data.

"Application Example 3: Combining Emotion Engines"

(Claim 1)

A spherical device that can move freely,
means for operating the device from an information terminal;
a sensor mounted on the device that detects animal movements and behavior patterns;
A generative AI that analyzes data from the sensors and understands the animal's preferences and play styles;
A means for providing an appropriate reaction or stimulus to the animal based on the AI;
An emotion engine that senses the user's emotional state and adjusts the device's behavior and response;
A system including means for advising a user on optimal interactions with animals.

(Claim 2)

The system described in claim 1, characterized in that the generative AI accumulates animal behavior data over time and learns changes in the animal's behavior patterns based on the accumulated data.

(Claim 3)

The system described in claim 1, characterized in that the device automatically responds to physical stimuli from the animal and feeds that response back to the generative AI as animal behavior data.

10, 210, 310, 410 Data processing system 12 Data processing device 14 Smart device 214 Smart glasses 314 Headset type terminal 414 Robot

Claims (1)

A spherical device that can move in any direction ;
a sensor mounted on the device for detecting the location, speed, and direction of the animal;
A generative AI that analyzes data from the sensors and understands the animal's preferences and play styles;
a server that issues instructions to the device based on the generative AI to provide the animal with appropriate reactions, stimulation, and play;
an information terminal that receives instructions from the server and operates the device;
an emotion engine that analyzes an emotional state of a user playing with the animal ;
The system wherein the server adjusts the device's reactions, stimuli, and play based on the results of the emotion engine's analysis .