JP7346505B2 - Childcare support system - Google Patents

Description

The present invention relates to a childcare support system.

In recent years, various systems to support childcare have become popular. One such system is a system that notifies caregivers of the condition of infants.
For example, in Patent Document 1, if it is determined based on the infant's cry that the infant is crying because the diaper got wet, it is determined that the infant is crying because the diaper got wet. It is described that the screen is displayed on the display unit.

JP2019-095931A

However, with the above-mentioned system, although it is possible to know the excretion of an infant, it is not possible to know whether the infant is in a healthy state.
The present invention provides a childcare support system that can solve the above problems.

The present invention includes a server device, a client device that communicates with the server device, an excretion sensor that detects the excretion of a childcare recipient, and an environmental sensor that detects environmental information indicating the environment of the childcare recipient. The client device includes an excretion information transmitting means for transmitting excretion information indicating that the excretion has been detected by the excretion sensor to the server device, and a means for transmitting the environmental information detected by the environmental sensor to the server device. environmental information transmitting means for transmitting environmental information to the client; and environmental judgment information receiving means for receiving environment -related information from the server device based on a judgment result of determining the appropriateness of the environment of the subject , the server device a storage means for storing the excretion information received from the device and the environmental information in association with time; and a storage means for storing the excretion information and the environment information received from the device , an excretion cycle determining means for determining the excretion cycle of the subject; and a predicted time in which the time associated with the excretion information stored in the storage means is predicted from the excretion cycle determined by the excretion cycle determining means. If it is determined that the standard is not appropriate, a physical condition change detection means for detecting that a physical condition change has occurred in the subject; and if the physical condition change detection means detects that a physical condition change has occurred in the subject; Based on the environmental information for a predetermined period determined based on the time included in the environmental information stored in the storage means and associated with the excretion information, and the judgment criteria regarding the environment , an environmental adequacy determining means for determining the appropriateness of the environment for a predetermined period ; and transmitting to the client device the environmental information that the environment of the subject is not appropriate for the predetermined period, as determined by the environmental adequacy determining means. Provided is a childcare support system characterized by comprising a means for transmitting environmental judgment information.

According to the present invention, it is possible to provide a childcare support system that can solve the above problems.

FIG. 1 is a conceptual diagram showing a childcare support system according to an embodiment of the present invention. FIG. 2 is a block diagram showing an example of the system configuration of a server device in the childcare support system of FIG. 1. FIG. 3 is a block diagram showing an example of a system configuration of a client device in the childcare support system of FIG. 1. As shown in FIG. FIG. 4 is a conceptual diagram showing a learning model used in the childcare support system of FIG. 1. FIG. 5 is a diagram showing an example of the configuration of a personal database used in the childcare support system of FIG. 1. FIG. 6 is a diagram showing a configuration example of a personal characteristic table used in the childcare support system of FIG. 1. FIG. 7 is a diagram showing an example of the configuration of a childcare database used in the childcare support system of FIG. 1. FIG. 8 is a block diagram showing an example of the functional configuration of the client device shown in FIG. 3. As shown in FIG. FIG. 9 is a block diagram showing an example of the functional configuration of the server device shown in FIG. 2. As shown in FIG. FIG. 10 is a diagram illustrating an example of the operation of determination based on the learned micturition pattern model in the server device of FIG. 2. FIG. 11 is a diagram illustrating an example of the operation of determination based on the updated urination pattern model in the server device of FIG. 2. FIG. 12 is a diagram illustrating an example of a urination pattern model learned by the server device of FIG. 2. FIG. 13 is a schematic diagram showing an example of a daily urination pattern of the subject infant 61 of FIG. 1. FIG. 14 is a flowchart illustrating an example of a procedure of model generation processing executed in the server device of FIG. 2. FIG. 15 is a flowchart illustrating an example of the procedure of the caution notification process executed in the server device of FIG. FIG. 16 is a flowchart illustrating an example of the procedure of appropriate environment notification processing executed in the server device of FIG. 2. FIG. 17 is a conceptual diagram showing the data flow of the growth degree determination process executed in the server device of FIG. 2.

Hereinafter, embodiments will be described with reference to the drawings.
First, with reference to FIG. 1, the configuration of a childcare support system according to an embodiment of the present invention will be described. The childcare support system 1 is a system that processes information to support a childcare worker 62 who takes care of an infant 61. The childcare worker 62 is a user who uses the childcare support system 1. The childcare worker 62 is, for example, a family member of the infant 61 or a person who is engaged in childcare at a childcare facility where the infant 61 is left. The infant 61 is a target of childcare supported by the childcare support system 1.

The childcare support system 1 includes, for example, a server device 2, a client device 3, and a plurality of sensors 5.

The server device 2 is a childcare support device that analyzes data regarding a plurality of infants 61 and provides information for supporting childcare. The server device 2 can be realized as a server computer, for example.

The client device 3 is a childcare support device used by a childcare worker 62. The client device 3 can be realized as, for example, a mobile information terminal, a tablet computer, a personal computer, or an embedded system built into various electronic devices. The portable information terminal is, for example, a mobile phone, a personal digital assistant (PDA), or a smartphone.

The client device 3 can communicate with the server device 2 via the network 4 . Communication via the network 4 may be wired communication or wireless communication. The network 4 includes, for example, Ethernet (registered trademark), a wired local area network (wired LAN), a wireless local area network (wireless LAN), and a mobile wireless communication network.

The plurality of sensors 5 are sensors that detect the excretion of the infant 61 and the childcare environment of the infant 61. The plurality of sensors 5 include a communication section for transmitting signals including detection results to the outside. More specifically, the plurality of sensors 5 transmit signals including detection results to, for example, the client device 3. The plurality of sensors 5 use, for example, Bluetooth (registered trademark) or wireless LAN as a communication method for transmitting signals to the outside. The plurality of sensors 5 include, for example, an excretion sensor 51 and an environmental sensor 52.

The excretion sensor 51 is a sensor that detects excretion by the infant 61. Excretion includes at least one of urination and defecation by the infant 61. The excretion sensor 51 is attached, for example, to an absorbent article (for example, a diaper) worn by the infant 61. Alternatively, the excretion sensor 51 may be built into an absorbent article worn by the infant 61. The excretion sensor 51 detects at least one of urination and defecation by the infant 61 by detecting changes in conductivity, temperature, humidity, odor, etc., for example. Furthermore, the excretion sensor 51 may be attached to not only the absorbent article but also anywhere as long as it can detect the excretion of the infant 61.

For example, the excretion sensor 51 transmits a signal indicating that excretion by the infant 61 has been detected to the client device 3. More specifically, the excretion sensor 51 transmits, for example, a signal indicating that urination by the infant 61 has been detected to the client device 3. The signal indicating that urination has been detected may include information about the time when the urination was detected. Further, the excretion sensor 51 transmits, for example, a signal indicating that defecation by the infant 61 has been detected to the client device 3. The signal indicating that defecation has been detected may include information about the time when the defecation was detected.

The environmental sensor 52 is a sensor that detects the environmental state (measured values, etc.) of the place where the infant 61 is. For example, the place where the infant 61 is located is a room or a bed where the infant 61 spends most of the time. Note that the environmental sensor 52 may be attached to the infant 61 himself or to something worn by the infant 61.

The environmental sensor 52 detects at least one of temperature, humidity, sound volume, illuminance, or gas concentration, and may detect any combination of these elements. Further, the type of gas whose concentration is to be detected may be a gas that is a component found in the normal atmosphere such as oxygen, carbon dioxide, or nitrogen, or volatile organic compounds (VOC) or nitrogen oxides. Gases considered to be harmful, such as Furthermore, any detection method for the environmental sensor 52 may be employed. Hereinafter, the detection target will be mainly explained as oxygen, but oxygen may be replaced with any gas.

The environment sensor 52 transmits signals indicating the environment of the infant 61 to the client device 3 in time series. For example, the environmental sensor 52 transmits, for each unit period, a signal indicating a plurality of time-series environments within one unit period to the client device 3. Alternatively, the environment sensor 52 may transmit a signal indicating the environment to the client device 3 in real time. The signal indicating the environment may include information about the time when the environment was detected.

One client device 3 is associated with one infant 61, for example. Hereinafter, one associated infant 61 will also be referred to as a target infant 61. The target infant 61 is an infant who is the target of childcare by the childcare worker 62 who uses the one client device 3 .

The client device 3 cooperates with the plurality of sensors 5 to transmit data regarding the excretion and environment of the target infant 61 to the server device 2.

More specifically, the client device 3 cooperates with the excretion sensor 51 to transmit the excretion data of the target infant 61 to the server device 2 . The excretion data indicates that excretion by the target infant 61 has been detected. The excretion data includes at least one of urination data and defecation data. The urination data indicates that urination by the target infant 61 has been detected. The defecation data indicates that defecation by the target infant 61 has been detected. The excretion data may include the time at which excretion (ie, urination or defecation) by the target infant 61 was detected.

The client device 3 cooperates with the environmental sensor 52 to transmit environmental data of the target infant 61 to the server device 2 . The environmental data indicates the time-series environment of the place where the target infant 61 is. The environmental data may include the time at which the environmental condition was detected.

The client device 3 may transmit data regarding the condition of the target infant 61 to the server device 2 based on information input by the childcare worker 62. The client device 3 may have a function that allows input of meal data related to meals, such as meal amount or meal time. For example, the amount of breast milk may be input manually, or may be automatically input by detecting the weight of the baby bottle with a weight sensor or the like. Any information related to the physical condition of the target infant 61 (for example, information related to excretion) may be input to the client device 3. For example, the amount of perspiration may be input by analyzing an image taken with a camera or by using a moisture sensor installed on a sheet.

Further, the client device 3 receives information for supporting childcare of the target infant 61 from the server device 2, and notifies the childcare worker 62 of the information.

The client device 3 may further transmit feedback data regarding the information received from the server device 2 to the server device 2. Feedback data is information indicating an evaluation regarding received information. For example, the feedback data indicates the result of the child care worker 62 determining whether the received information was appropriate. Specifically, the feedback data includes an excretion notice that foretells the infant's 61's next excretion, a warning notice of a change in the infant's 61's physical condition, information regarding an environment that has been determined to be inappropriate for the infant's 61, and information regarding an appropriate environment for the infant's 61. This information is information for supporting, and information indicating the evaluation result of the caregiver 62 regarding at least one of the length of the infant 61.

Note that one client device 3 may be associated with a plurality of infants 61. In that case, the client device 3 cooperates with the plurality of sensors 5 provided for each of the plurality of infants 61 to transmit data regarding the state and environment of each of the plurality of infants 61 to the server device 2. Further, the client device 3 receives information for supporting childcare of each of the plurality of infants 61 from the server device 2, and notifies the childcare worker 62 of the information. The client device 3 can notify information in a form that allows the caregiver 62 to recognize which of the plurality of infants 61 the information relates to. The client device 3 notifies the information together with the name of the corresponding infant 61, for example.

Further, a plurality of client devices 3 may be associated with one infant 61. The plurality of client devices 3 are each used by, for example, a plurality of childcare workers 62. Alternatively, one childcare worker 62 may use multiple client devices 3. At least one client device 3 among the plurality of client devices 3 cooperates with a plurality of sensors 5 provided for the infant 61 to transmit data regarding the condition and environment of the infant 61 to the server device 2. This at least one client device 3 is located within a range where short-range wireless communication with the sensor 5 is possible, for example. The remaining client devices 3 may be located remotely where short-range communication with the sensor 5 is not possible. Further, each of the plurality of client devices 3 receives information for supporting childcare of the infant 61 from the server device 2, and notifies the childcare worker 62 of the information. Thereby, information for supporting childcare of one infant 61 can be notified to a plurality of childcare workers 62.

Below, in order to make the explanation easier to understand, a case will be mainly illustrated in which one client device 3 is associated with one infant 61.

FIG. 2 is a block diagram showing an example of the system configuration of the server device 2. As shown in FIG. The server device 2 includes, for example, a central processing unit (CPU) 21, a random access memory (RAM) 22, a storage device 23, and a communication section 24.

The CPU 21 is a processor that controls the operations of various components within the server device 2 .

RAM22 is volatile memory. The RAM 22 is, for example, a dynamic random access memory (DRAM). The storage area of the RAM 22 is allocated as a storage area for, for example, the operating system (OS) 221, application programs (for example, the childcare support server program 222), and data used for processing by the CPU 21.

The storage device 23 is, for example, a solid state drive (SSD) or a hard disk drive (HDD). The storage device 23 stores programs and data for controlling the operation of the server device 2 . The storage device 23 stores, for example, a plurality of personal databases 231, a personal characteristic table 232, a childcare database 233, and group information 234.

The plurality of personal databases 231 correspond to the plurality of infants 61, respectively. Each of the plurality of personal databases 231 is a database for managing data (that is, personal data) regarding one corresponding infant 61. One personal database 231 includes, for example, excretion data and environmental data of one corresponding infant 61. In addition to these, the personal database 231 may include any information inputted by the childcare worker 62. For example, the personal database 231 may include feedback data indicating the result of the child care worker 62 determining whether or not the information received from the server device 2 was appropriate.

The personal characteristics table 232 is a table for managing information regarding the attributes of each of the plurality of infants 61.

The childcare database 233 is a database for managing data (that is, big data) regarding the plurality of infants 61. The childcare database 233 includes, for example, analysis results using the plurality of personal databases 231 and childcare knowledge information obtained through surveys and research.

Group information 234 is information for managing multiple groups into which infants 61 can be classified. The plurality of groups are obtained by classifying the plurality of infants 61 using at least one attribute. In the classification, a group to which each of the plurality of infants 61 belongs is determined based on at least one attribute. For example, a clustering method such as the k-means method is used for classification. At least one infant 61 belongs to each of the plurality of groups. Each of the plurality of infants 61 belongs to one of the plurality of groups. The plurality of infants 61 belonging to one group have at least one of the following in common: age in months, age, date of birth, sex, place of birth, place of residence, weight, and height, for example.

The communication unit 24 is a device configured to perform wired or wireless communication between the server device 2 and the outside. The communication unit 24 executes communication with the client device 3, for example. The communication section 24 includes a transmitting section and a receiving section. The transmitter transmits a signal. The receiving section receives the signal.

Next, a program executed by the CPU 21 will be explained.
The CPU 21 executes various programs loaded into the RAM 22 from the storage device 23. The programs executed by the CPU 21 include an OS 221 and a childcare support server program 222.

The OS 221 is a program for controlling basic operations of various components within the server device 2. The CPU 21 running the OS 221 controls, for example, input/output, file management, memory management, and communication.

The childcare support server program 222 is a server program for supporting childcare for at least one infant 61. More specifically, the childcare support server program 222 has a function for notifying changes in the physical condition of the infant 61, a function for foretelling the next excretion by the infant 61, and a function for supporting an appropriate environment for the infant 61. function, and a function for notifying the degree of growth of the infant 61. An example of the functional configuration of the childcare support server program 222 will be described later with reference to FIG. Below, the childcare support server program 222 is also simply referred to as the server program 222.

FIG. 3 is a block diagram showing an example of the system configuration of the client device 3. As shown in FIG. The client device 3 includes, for example, a CPU 31, a RAM 32, a storage device 33, a touch screen display 34, a first communication section 35, a second communication section 36, a vibration section 37, and a speaker 38.

The CPU 31 is a processor that controls the operations of various components within the client device 3.

RAM 32 is volatile memory. The RAM 32 is, for example, a DRAM. The storage area of the RAM 32 is allocated, for example, as a cache area for data used for processing by the OS 321, an application program (for example, the childcare support client program 322), and the CPU 31.

The storage device 33 is, for example, an SSD or an HDD. The storage device 33 stores programs and data for controlling the operation of the client device 3.

Touch screen display 34 is an input/output device. The touch screen display 34 includes, for example, a liquid crystal display (LCD) and a touch panel. The touch screen display 34 displays, for example, an image based on a display signal generated by the CPU 31 on an LCD screen.

A touch panel is placed on the top surface of the LCD. A touch panel is a capacitive pointing device for performing input on an LCD screen. The touch panel detects the touch position on the screen that a finger touches and the movement of the touch position. The touch panel can send signals indicating the detected touch position and the movement of the touch position to each part (for example, the CPU 31) in the client device 3.

The first communication unit 35 is a device configured to perform wired or wireless communication between the client device 3 and the outside. The first communication unit 35 executes communication with the server device 2, for example. The first communication section 35 includes a transmitting section and a receiving section.

The second communication unit 36 is a device configured to perform wired or wireless communication between the client device 3 and the outside. The second communication unit 36 executes communication with each of the excretion sensor 51 and the environment sensor 52, for example. The second communication section 36 includes a transmitting section and a receiving section.

The vibrating section 37 is an output device having a vibrating mechanism. The vibration mechanism is realized, for example, as a motor with an eccentric weight attached to a rotating shaft. The vibration unit 37 vibrates the client device 3 based on a signal generated by the CPU 31, for example. The signal generated by the CPU 31 may be a signal in which at least one of vibration magnitude, vibration time, and vibration pattern is specified.

Speaker 38 is an output device. The speaker 38 outputs audio based on the audio signal generated by the CPU 31, for example.

Next, a program executed by the CPU 31 will be explained.
The CPU 31 executes various programs loaded into the RAM 32 from the storage device 33. The programs executed by the CPU 31 include an OS 321 and a childcare support client program 322.

The OS 321 is a program for controlling the basic operations of various components within the client device 3. The CPU 31 running the OS 321 controls, for example, input/output, file management, memory management, and communication.

The childcare support client program 322 is a client program for supporting childcare for at least one infant 61. More specifically, the childcare support client program 322 has a function for transmitting data regarding the condition and environment of the infant 61 to the server device 2 in cooperation with the sensor 5, and a function for transmitting data regarding the condition and environment of the infant 61 provided from the server device 2. The child care provider 62 may have a function of notifying the child care worker 62 of information to support child care. Further, the childcare support client program 322 may have a function for transmitting feedback data to the server device 2. An example of the functional configuration of the childcare support client program 322 will be described later with reference to FIG. Hereinafter, the childcare support client program 322 will also be simply referred to as the client program 322.

Next, a prediction model for predicting the excretion pattern by the target infant 61 will be explained. Here, the excretion pattern may be a pattern showing both urination and defecation, a urination pattern showing only urination, or a defecation pattern showing only defecation. Further, although the present invention will be described as a prediction model that predicts excretion patterns, a prediction model that makes arbitrary predictions may be configured in the same manner.

FIG. 4 is a conceptual diagram showing the prediction model 75 used in the childcare support system 1. The server device 2 generates a prediction model 75 through learning 71 using at least one of the personal database 231A of one or more other infants 61 belonging to the same group as the target infant 61 and the personal database 231B of the target infant 61. do. The learning 71 is, for example, modeling using a neural network. The prediction model 75 is, for example, a mathematical model or a physical model.

Note that the generated prediction model 75 is a prediction model corresponding to the target infant 61. The server device 2 can generate a plurality of prediction models corresponding to the plurality of infants 61, respectively.

The server device 2 uses the prediction model 75 with the excretion data regarding the most recent excretion of the target infant 61 as input, and thereby determines whether or not to issue a warning notice regarding the physical condition change of the target infant 61.

Furthermore, the server device 2 may use the prediction model 75 to give advance notice of the next excretion. For example, the time when the next excretion is predicted may be calculated and included in the excretion notice. The time at which the next excretion by the target infant 61 is predicted is also referred to as the excretion prediction time. The predicted excretion time may be the expected time, or may be the time (for example, n minutes) from the current time to the time when the target infant 61 is predicted to excrete.

More specifically, the server device 2 uses, for example, a standard prediction model by learning 71 using the personal database 231A of one or more other infants 61 belonging to the same group as the target infant 61 as prior learning data. 75 is generated. The server device 2 uses the standard prediction model 75 with the excretion data regarding the most recent excretion of the target infant 61 as input, and thereby determines whether or not to issue a warning notice regarding a change in the physical condition of the target infant 61. Note that the server device 2 sequentially stores the excretion data and environmental data of the target infant 61 in the personal database 231B of the target infant 61.

Next, the server device 2 generates a modified prediction model 75 through learning 71 (ie, retraining) that further uses the personal database 231B of the target infant 61 as learning data for updating. The server device 2 uses the corrected prediction model 75 with the excretion data regarding the most recent excretion of the subject infant 61 as input, and thereby determines whether or not to issue a warning notice regarding a change in the physical condition of the subject infant 61.

For example, the server device 2 generates a modified prediction model 75 in response to the addition of excretion data to the personal database 231B of the target infant 61. That is, the server device 2 repeatedly performs learning 71 using the personal database 231B of the target infant 61 as learning data for updating. Thereby, the server device 2 can improve the prediction model 75 into a model that is more suitable for the characteristics of the target infant 61. Further, the prediction model 75 may be modified based on feedback data added to the personal database 231B of the target infant 61. Therefore, it is possible to improve the accuracy of prediction as to whether or not to issue a warning notice regarding a change in the physical condition of the target infant 61. Moreover, the prediction accuracy regarding the excretion notice of the target infant 61 can be improved. Note that if the excretion data of the target infant 61 is stored in the personal database 231B of the target infant 61 before generating the standard prediction model 75, the server device 2 stores the personal database 231B of the target infant 61 in advance. It may also be used as learning data.

Next, a configuration example of a database and a table used in the childcare support system 1 will be explained.
(Personal database)
FIG. 5 shows an example of the configuration of the personal database 231. The personal database 231 is a database for managing excretion data of the infant 61 and environmental data. Personal database 231 may include multiple entries each corresponding to multiple times. Each of the plurality of entries includes a time field, a type field, a temperature field, a humidity field, a volume field, an illuminance field, and an oxygen concentration field.

In an entry corresponding to a certain time, the time field indicates that time. The time is expressed, for example, as a date and time.

The type field may indicate urination or defecation by infant 61 detected at the corresponding time. If urination by the infant 61 is detected at the corresponding time, "urination" is set in the type field, for example. If defecation by the infant 61 is detected at the corresponding time, "defecation" is set in the type field, for example. If neither urination nor defecation by the infant 61 is detected at the corresponding time, for example, no value is set in the type field.

The temperature field indicates the temperature of the location where the infant 61 is detected at the corresponding time. Temperature is expressed, for example, in degrees Celsius.

The humidity field indicates the humidity at the location where the infant 61 is detected at the corresponding time. Humidity may be relative humidity or absolute humidity. Humidity is, for example, relative humidity expressed as a percentage.

The volume field indicates the volume of the location where the infant 61 is detected at the corresponding time. The volume is expressed, for example, in decibels.

The illuminance field indicates the illuminance of the place where the infant 61 is detected at the corresponding time. Illuminance is expressed, for example, in lux.

The oxygen concentration field indicates the oxygen concentration at the location where the infant 61 is detected at the corresponding time. The oxygen concentration is expressed, for example, as a percentage. The same applies to the concentration of gases other than oxygen (oxygen, carbon dioxide, nitrogen, VOC, nitrogen oxides, etc.).

In the example shown in FIG. 5, for the time "2021/3/1 00:00:01", the temperature is "10 degrees Celsius", the humidity is "50%", the volume is "20 dB", the illuminance is "0 lux", and the oxygen concentration is "21". .9%” and no detected urination or defecation. For the time “2021/3/1 00:00:02”, temperature “10°C”, humidity “50%”, volume “20dB”, illuminance “0lux”, oxygen concentration “21.9%”, and urination is associated with the detection of In addition, for the time "2021/3/1 15:10:31", the temperature is "20 degrees Celsius", the humidity is "60%", the volume is "50 dB", the illuminance is "300 lux", the oxygen concentration is "21.8%", and detected defecation.

In the following description of the personal database 231, the value shown in the time field is also simply referred to as time. The same applies to the values shown in each other field of the personal database 231 and the values shown in each field of other databases and tables.

(Personal characteristics table)
FIG. 6 shows an example of the configuration of the personal characteristics table 232. The personal characteristics table 232 is a table for managing information regarding the attributes and characteristics of each of the plurality of infants 61. The personal characteristics table 232 may include a plurality of entries corresponding to each of the plurality of infants 61. Each of the plurality of entries includes, for example, an infant ID field, a date of birth field, a gender field, a place of birth field, a place of residence field, a weight field, a height field, and a group ID field.

In the entry corresponding to a certain infant 61, the infant ID field indicates identification information (infant ID) given to the infant 61. With one infant ID, one corresponding infant 61 can be specified.

The date of birth field indicates the date of birth of the corresponding infant 61.
The gender field indicates the gender of the corresponding infant 61.
The place of birth field indicates the place of birth of the corresponding infant 61.

The residence field indicates the residence of the corresponding infant 61. When the place of residence of the corresponding infant 61 is changed, the place (address, postal code, etc.) set in the place of birth field is changed.

The weight field indicates the weight of the corresponding infant 61. When the weight of the corresponding infant 61 increases or decreases, the value set in the weight field is updated.

The height field indicates the height of the corresponding infant 61. When the height of the corresponding infant 61 increases, the value set in the height field is updated.

The group ID field indicates identification information (group ID) given to the group to which the corresponding infant 61 belongs. With one group ID, one corresponding group can be specified.

Note that each entry may further include a month/age field. The age/age field indicates the age or age of the corresponding infant 61. The age in months or age is calculated based on the date of birth of the infant 61, for example.

In the example shown in FIG. 6, for an infant 61 whose infant ID is "1", the date of birth is "2020/7/16", the gender is "female", the place of birth is "A", the place of residence is "A", and the weight is " 7.8", height "68.5", and group ID "G1". For infant 61 with infant ID “2”, date of birth “2020/10/21”, gender “male”, place of birth “B”, place of residence “B”, weight “6.5”, height “ 62.0” and group ID “G1” are associated. In addition, for infant 61 with infant ID “3”, date of birth “2021/1/15”, gender “male”, place of birth “A”, place of residence “C”, weight “4.5”, Height "55.0" and group ID "G2" are associated.

(Childcare database)
FIG. 7 shows an example of the structure of the childcare database 233. The childcare database 233 is a database for managing data regarding the plurality of infants 61. More specifically, the childcare database 233 manages, for example, statistical values obtained by analyzing the plurality of personal databases 231 for each group to which the infant 61 belongs. Furthermore, the childcare database 233 may manage data based on childcare knowledge obtained through surveys and research.

Childcare database 233 may include multiple entries corresponding to multiple groups. Each of the plurality of entries includes a group ID field, a urination frequency field, a urination interval field, a defecation frequency field, a defecation interval field, an average temperature field, an average humidity field, an average volume field, an average illuminance field, and an average density field. In addition, fields corresponding to the amount of urine, the amount of defecation, the frequency of urination, the frequency of defecation, the amount of food, or the amount of perspiration may be included.

In an entry corresponding to a certain group, the group ID field indicates identification information (group ID) given to that group.

The urination frequency field is a statistical value regarding the urination frequency of one or more infants 61 belonging to the corresponding group. The urination frequency is the number of micturitions per unit time. The unit time is, for example, one day. Further, the statistical value is, for example, any statistical numerical value such as an average value, a deviation value, a median value, a maximum value, and a minimum value.

The urination interval field is a statistical value regarding the urination interval of one or more infants 61 belonging to the corresponding group. The micturition interval is the time interval between at least two micturitions.

The defecation frequency field is a statistical value regarding the defecation frequency of one or more infants 61 belonging to the corresponding group. Other points are similar to the urination frequency field.

The defecation interval field is a statistical value regarding the defecation interval of one or more infants 61 belonging to the corresponding group. Other points are similar to the micturition interval field.

The average temperature field is the average value of the temperature per unit time of the location where one or more infants 61 belonging to the corresponding group are present. The unit time may be, for example, one day, or may be a fixed period of time divided by time of day or the like to represent daytime, nighttime, or the like. Also, other statistical values may be used in addition to or instead of the average value.

The average humidity field is the average value of humidity per unit time at a location where one or more infants 61 belonging to the corresponding group are present. Other points are similar to the average temperature field.

The average sound volume field is the average value of sound volume per unit time at a location where one or more infants 61 belonging to the corresponding group are present. Other points are similar to the average temperature field.

The average illuminance field is the average value of the sound volume per unit time at a place where one or more infants 61 belonging to the corresponding group are present. Other points are similar to the average temperature field.

The average concentration field is the average value of oxygen concentration (gas concentration) per unit time at a location where one or more infants 61 belonging to the corresponding group are present. Other points are similar to the average temperature field.

(Functional configuration of client device 3)
Next, the configuration of the client device 3 will be explained.
FIG. 8 is a block diagram showing an example of the functional configuration of the client device 3. As shown in FIG. The client device 3 includes, for example, a first reception processing section 501, a transmission processing section 502, a second reception processing section 503, and a notification processing section 504. The first reception processing unit 501, the transmission processing unit 502, the second reception processing unit 503, and the notification processing unit 504 are functional configurations that are provided in the CPU 31 by executing the client program 322, for example.

The first reception processing unit 501 and the transmission processing unit 502 have a configuration (hereinafter referred to as sensor data transmission ). Further, the second reception processing unit 503 and the notification processing unit 504 are configured to notify the child care worker 62 of the information received from the server device 2 (hereinafter referred to as a configuration for information notification). The configuration for sensor data transmission and the configuration for information notification will be described below.

(Configuration for sensor data transmission)
The first reception processing unit 501 receives signals from each of the excretion sensor 51 and the environment sensor 52 via the second communication unit 36. The first reception processing unit 501 uses the received signal to generate data regarding the excretion and environment of the target infant 61. The first reception processing unit 501 then sends the generated data to the transmission processing unit 502.

More specifically, the first reception processing unit 501 uses the signal received from the excretion sensor 51 to generate excretion data. If the signal received from the excretion sensor 51 does not include information on the time when excretion was detected, the first reception processing unit 501 may generate excretion data that includes the time when excretion was detected.

The first reception processing unit 501 generates environmental data using the signal received from the environmental sensor 52. If the signal received from the environmental sensor 52 does not include information on the time at which the detected value (temperature, etc.) was detected, the first reception processing unit 501 receives the detected value and the time at which the detected value was detected. You may also generate environmental data including:

The first reception processing unit 501 then sends the excretion data or environmental data to the transmission processing unit 502. The first reception processing section 501 may send a combination of excretion data and environmental data to the transmission processing section 502.

The transmission processing unit 502 transmits the data received from the first reception processing unit 501 to the server device 2 via the first communication unit 35. Further, the transmission processing unit 502 may transmit information (feedback data, etc.) input by the child care worker 62 to the server device 2 via an input device such as a touch panel.

(Configuration for information notification)
The second reception processing unit 503 receives information used for notification to the childcare worker 62 from the server device 2 via the first communication unit 35 . The information used to notify the childcare worker 62 is, for example, information for notifying changes in the physical condition of the infant 61, information for foretelling the next excretion by the infant 61, and information for supporting an appropriate environment for the infant 61. This is information for notifying the child 61's growth level. The second reception processing unit 503 sends the received information to the notification processing unit 504. Hereinafter, this information will also be referred to as information for notifying changes in the physical condition of the target infant 61 or physical condition change information. Information for foretelling the next excretion by the target infant 61 is also referred to as advance notice information. Information for supporting an appropriate environment for the infant 61 is also referred to as appropriate environment support information. Information for notifying the growth degree of the target infant 61 is also referred to as growth degree information.

The notification processing unit 504 uses the information received from the second reception processing unit 503 to notify the childcare worker 62. At least one of the touch screen display 34, the vibration unit 37, and the speaker 38 is used for the notification.

For example, the notification processing unit 504 uses the physical condition change information received from the second reception processing unit 503 to notify the child care worker 62 of a change in the physical condition of the target infant 61. Specifically, the notification processing unit 504 generates, for example, a display signal for displaying an image (hereinafter referred to as a caution notification image) that notifies the user of a change in physical condition based on the physical condition change information. The notification processing unit 504 sends the generated display signal to the touch screen display 34. The touch screen display 34 displays the caution notification image on the screen based on the received display signal. By looking at the displayed caution notification image, the child care worker 62 can recognize that the child care worker 62 has been notified of a change in the physical condition of the target infant 61.

Further, the notification processing unit 504 may send a signal requesting vibration to the vibration unit 37 based on the caution notification information. The vibrator 37 vibrates the client device 3 based on the received signal. By vibrating the client device 3, the child care worker 62 can be prompted to check the caution notification image displayed on the screen. This vibration may have a specific vibration pattern. The child care worker 62 can recognize that the client device 3 vibrates in a specific vibration pattern, and thus has been notified of a change in the physical condition of the target infant 61.

Further, the notification processing unit 504 may send an audio signal to the speaker 38 to notify the user of a change in physical condition based on the caution notification information. The speaker 38 outputs audio based on the received audio signal. This sound may be the sound of a specific message being uttered, or may be an alert sound. The child care worker 62 can recognize from the voice that the child care worker 62 has been notified of a change in the physical condition of the target infant 61. Alternatively, the child care worker 62 can be prompted by voice to confirm the caution notification image displayed on the screen.

Similarly, when the notification processing unit 504 receives advance notice information from the second reception processing unit 503, it notifies the caregiver 62 of the next excretion by the target infant 61. Further, when the notification processing unit 504 receives the appropriate environment support information from the second reception processing unit 503, it similarly notifies the child care worker 62 of information for supporting the appropriate environment for the target infant 61. Further, when the notification processing unit 504 receives the growth degree information from the second reception processing unit 503, it similarly notifies the child care worker 62 of information regarding the growth degree of the target infant 61.

With the above configuration, the client device 3 can transmit data regarding the excretion and environment of the target infant 61 to the server device 2 using the signals received from the sensor 5. The client device 3 can notify the childcare worker 62 of the information received from the server device 2. Further, the client device 3 can transmit feedback data regarding the notified information to the server device 2. For any information sent to the client device 3, the server device may use the feedback data in any way to generate information more appropriate for the target infant 61. For example, the feedback data may be used to modify any criteria or may be used as learning data to generate or update a predictive model.

(Functional configuration of server device 2)
Next, the functional configuration of the server device 2 will be explained.
FIG. 9 is a block diagram showing an example of the functional configuration of the server device 2. As shown in FIG. The server device 2 includes, for example, a storage processing section 401, a group determination section 402, a learning section 403, a determination section 404, a generation section 405, and a transmission processing section 406. The storage processing unit 401, the group determination unit 402, the learning unit 403, the determination unit 404, the generation unit 405, and the transmission processing unit 406 are functional configurations that are provided in the CPU 21 by executing the server program 222, for example.

The storage processing unit 401 receives data (sensor data) regarding the excretion of the infant 61 and the environment from the client device 3 via the communication unit 24 . The received data includes at least one of excretion data and environmental data. The storage processing unit 401 updates the personal database 231 corresponding to the infant 61 using the received data.

Specifically, when the storage processing unit 401 receives excretion data and environmental data corresponding to a certain time from the client device 3 associated with a certain infant 61, the storage processing unit 401 stores information about the time and the environment data indicated in the excretion data. Generate an entry that includes urination or defecation and the environment indicated in the environmental data. Then, the storage processing unit 401 adds the generated entry to the personal database 231 corresponding to the infant 61.

The group determining unit 402 determines the group to which the target infant 61 belongs, using the group information 234 and the personal characteristics table 232. Specifically, the group determining unit 402 identifies the entry corresponding to the target infant 61 in the individual characteristics table 232. Then, the group determining unit 402 determines one group to which the target infant 61 belongs, using at least one attribute shown in the specified entry and the group information 234. Group determining section 402 sends a group ID indicating the determined group to learning section 403 and generating section 405.

The learning unit 403 generates a prediction model 75 for predicting the excretion pattern of the target infant 61. The learning unit 403 uses the group ID received from the group determining unit 402 to determine the personal database 231A of one or more other infants 61 belonging to the group specified by the group ID and the personal database 231B of the target infant 61. A prediction model 75 is generated using at least one of them. Each of the personal databases 231A and 231B includes at least one of excretion data and environmental data.

The determination unit 404 uses the prediction model 75 sent out by the learning unit 403 to determine whether or not to issue a warning notice regarding a change in the physical condition of the target infant 61. For example, the determination unit 404 receives excretion data indicating the current condition of the target infant 61 and uses the prediction model 75 to determine the physical condition of the target infant 61 and determines whether or not a warning should be given. The determination unit 404 may use the excretion prediction model 75 to calculate the time at which the next excretion by the target infant 61 is predicted (excretion prediction time) and give an excretion advance notice.

When the determining unit 404 determines that a warning notice regarding a change in the physical condition of the target infant 61 should be issued, the determining unit 404 sends the determination result to the generating unit 405 . Further, the determination unit 404 may send an excretion notice including the predicted excretion time to the generation unit 405.

The generation unit 405 generates information to be provided to the childcare worker 62. Specifically, the generation unit 405 generates caution notification information for notifying the target infant 61 of a change in physical condition based on the determination result by the determining unit 404 that a caution notification of the physical condition change of the target infant 61 should be issued. generate. Further, the generation unit 405 generates advance notice information for giving advance notice of excretion. The generation unit 405 then sends the generated caution notification information or preview information to the transmission processing unit 406.

When the determining unit 404 determines that a warning notice regarding a change in the physical condition of the target infant 61 should be issued, the determination unit 404 determines whether or not there is inappropriate environmental data in the environmental data of the target infant 61 for the most recent predetermined period. The determination unit 404 sends the determination result to the generation unit 405 when there is inappropriate environmental data. The generation unit 405 generates appropriate environmental support information including environmental data determined to be inappropriate and appropriate environmental data corresponding to the environmental data. The generation unit 405 then sends the generated appropriate environment support information to the transmission processing unit 406.

Further, the determining unit 404 may determine the degree of growth of the target infant 61. For example, the determination unit 404 determines the growth level of the target infant 61 from the excretion-related data accumulated in the personal database 231B of the target infant 61, based on the growth level determination criteria generated from the excretion-related data accumulated in the childcare database 233. Determine. The excretion-related data is, for example, a daily excretion pattern. The determining unit 404 sends a determination result indicating the degree of growth to the generating unit 405. The generation unit 405 generates growth degree information including a determination result indicating the growth degree. The generation unit 405 then sends the generated growth degree information to the transmission processing unit 406.

The transmission processing unit 406 transmits the information sent by the generation unit 405 to the client device 3 via the communication unit 24. The transmitted information is, for example, caution notification information, advance notice information, appropriate environmental support information, or growth degree information.

A specific example of the operation of the learning section 403 and the determining section 404 will be described with reference to FIGS. 10 and 11. Here, a case will be exemplified in which a urination pattern model 751 corresponding to one infant (target infant) 61 is learned and it is determined whether or not a change in the physical condition of the infant 61 should be notified.

FIG. 10 is a diagram showing an example of a determination operation based on the learned urination pattern model 751.
The learning unit 403 learns the standard urination pattern model 751 using the personal database 231A of one or more other infants 61 belonging to the same group as the target infant 61 as prior learning data. The learning unit 403 sends the learned standard urination pattern model 751 to the determining unit 404.

For example, the determination unit 404 determines whether or not to issue a warning notice of a change in the physical condition of the target infant 61 by using the standard urination pattern model 751 with input of urination data regarding the most recent urination of the target infant 61. The determination unit 404 may use the urination pattern model 751 to predict the next urination by the target infant 61 (for example, the predicted time of the next urination, etc.).

With the above configuration, the learning unit 403 and the determining unit 404 can learn the standard urination pattern model 751 corresponding to the target infant 61 and determine whether or not to notify the target infant 61 of a change in physical condition.

FIG. 11 is a diagram showing an example of a determination operation based on the modified urination pattern model 751.
After learning the standard urination pattern model 751, the learning unit 403 further uses the personal database 231B of the target infant 61 as learning data for updating to learn a modified urination pattern model 751. The learning unit 403 uses, for example, the personal database 231A of one or more other infants 61 belonging to the same group as the target infant 61 and the personal database 231B of the target infant 61 to generate the modified urination pattern model 751. learn. The learning unit 403 sends the corrected urination pattern model 751 to the determining unit 404.

Further, the urination pattern model 751 may be modified based on environmental data, sweat amount, or meal amount (lactation amount, etc.) stored in the personal database 231B. By correcting the urination pattern model 751 with any combination of data stored in the personal database 231B, it is possible to improve the accuracy of predicting the urination pattern of the target infant 61.

For example, the determination unit 404 determines whether or not to issue a warning notice of a change in the physical condition of the target infant 61 by using the modified urination pattern model 751 with input of urination data related to the most recent urination of the target infant 61. .

Further, the learning unit 403 may further modify the modified urination pattern model 751, for example, in response to the addition of urination data or feedback data to the personal database 231B of the target infant 61. By repeatedly modifying the urination pattern model 751 using the personal database 231B of the target infant 61, the urination pattern model 751 becomes a predictive model that is more suitable for the characteristics of the target infant 61. Therefore, it is possible to improve the accuracy of prediction as to whether or not to issue a warning notice regarding a change in the physical condition of the target infant 61. Moreover, the prediction accuracy regarding the urination notice of the target infant 61 can be improved.

FIG. 12 is a schematic diagram showing an example of the urination pattern model 751. In FIG. 12, the horizontal axis indicates time. The urination pattern model 751 is a model that indicates the urination time and urination interval of the target infant 61 in one day.

The starting point, time t0, is, for example, when the target infant 61 wakes up, but it may also be the time when the subject infant 61 urinates for the first time. Note that the waking up of the target infant 61 may be detected using a sensor or the like, or may be determined in any manner.

Times t11, t12, t13, and t14 are times when the target infant 61 is predicted to urinate. Times t11 to t14 are the predicted times of the first to fourth urinations of the subject infant 61 in one day, respectively. The intervals TB1, TB2, TB3, and TB4 are the time intervals between the first to fourth urinations of the subject infant 61 in one day.

The deviations σT1, σT2, σT3, and σT4 are deviations from the predicted times of the first to fourth urinations of the target infant 61 in one day, and indicate the allowable range of urination time shifts due to disturbances for the target infant 61. The disturbance may be caused by the environment, amount of meals, meal time, amount of sweat, etc. of the target infant 61.

Next, with reference to FIGS. 12 and 13, a method for determining urination notice and physical condition change will be described.
FIG. 13 is a schematic diagram showing an example of the daily urination pattern of the target infant 61 to which the urination pattern model 751 is applied. In FIG. 13, the horizontal axis indicates time. The time t0 is the starting point similarly to FIG. 12. Times t21, t22, t23, and t24 indicate times when the target infant 61 urinated.

The predicted time when the target infant 61 urinates for the third time is estimated as follows.
Referring to the urination pattern model 751 in FIG. 12, there is a time interval TB2 between the second urination time t12 and the third urination time t13. Furthermore, deviations σT1 and σT2 due to disturbance are assumed at the first urination times t11 and t12, respectively. Therefore, if the elapsed time since the target infant 61 urinated for the second time is T, then when the following equation holds true, the target infant 61 may urinate at any time. At this time, a urination warning may be issued.

T≧TB2−σ(T1+T2) …Formula (1)
As shown in FIG. 13, it is assumed that the target infant 61 urinates for the third time at time t23, and there is a time interval T2 between the second urination time t22 and the third urination time t23. It is determined using the urination pattern model 751 whether this time interval T2 causes any problem in the physical condition of the target infant 61. When the following formula holds true, it is determined that there is a possibility that the target infant 61 has changed in physical condition. At this time, a warning notice regarding changes in the physical condition of the target infant 61 may be issued.

T2≧2×(TB2−σ(T1+T2)) …Formula (2)
That is, if the time interval T2 takes twice as long as the predicted time interval TB2, taking into account the deviation σ (T1 + T2) due to disturbance, it is determined that it is necessary to pay attention to changes in the physical condition of the target infant 61. ing.

Similarly to the urination pattern model 751, the above-mentioned determination formula may be updated sequentially by machine learning using a neural network or the like. For example, "2 times" in the above equation may be updated to "1.5 times" or "2.5 times" as a parameter to be learned. Furthermore, a new formula that is completely different from the above formula may be derived by machine learning. Furthermore, the change is not limited to machine learning, and may be artificially changed based on childcare knowledge (knowledge base) obtained through surveys and research, or feedback data from the childcare worker 62.

Next, with reference to FIGS. 14 to 17, the procedure of processing executed in the server device 2 will be described.
(Model generation process)
FIG. 14 is a flowchart illustrating an example of a procedure of model generation processing executed by the CPU 21 of the server device 2. As shown in FIG. The model generation process is a process for generating a urination pattern model of the target infant 61. For example, when an entry corresponding to the target infant 61 is added to the personal characteristics table 232, the CPU 21 executes the model generation process. Alternatively, the CPU 21 may start executing the model generation process when urination data and environmental data for a specific period are stored (accumulated) in the personal database 231 corresponding to the target infant 61.

First, the CPU 21 identifies an entry corresponding to the target infant 61 in the personal characteristics table 232 (step S11). The identified entry includes information indicating at least one attribute regarding the target infant 61. The CPU 21 uses the specified entry and the group information 234 to determine the group to which the target infant 61 belongs (step S12). More specifically, the CPU 21 determines to which of the plurality of groups indicated by the group information 234 the target infant 61 belongs. Then, the CPU 21 generates the urination pattern model 751 of the target infant 61 by learning using the personal database 231 of other infants belonging to the determined group (step S13). The generated urination pattern model 751 is a standard urination pattern model corresponding to the group to which the target infant 61 belongs. Note that the CPU 21 may generate a standard urination pattern model for each group in advance, for example, before the target infant 61 is registered in the server device 2. Further, the CPU 21 may further use the personal database 231 of the target infant 61 for learning to generate the urination pattern model 751. Alternatively, the CPU 21 may generate the urination pattern model 751 through learning using only the personal database 231 of the target infant 61.

Next, the CPU 21 determines whether a unit time has elapsed since the current urination pattern model 751 was generated (step S14). The unit time is, for example, one day, several days, one week, one month, etc. If a unit time has elapsed since the current urination pattern model 751 was generated (YES in step S14), the CPU 21 acquires urination data and environmental data for that unit time from the personal database 231 of the target infant 61. (Step S15). Then, the CPU 21 generates the corrected urination pattern model 751 using the acquired urination data for the unit time and the environmental data (step S16). That is, the CPU 21 modifies the current urination pattern model 751 using the urination data of the target infant 61 for a unit time and the environmental data.

If the unit time has not elapsed since the current urination pattern model 751 was generated (NO in step S14), the process by the CPU 21 returns to the procedure in step S14. In other words, the CPU 21 returns to step S14 because sufficient data for modifying the current urination pattern model 751 is not yet stored in the personal database 231 of the target infant 61.

Through the above model generation process, the CPU 21 can generate the urination pattern model 751 of the target infant 61. In addition, the CPU 21 can modify the generated urination pattern model 751 when urination data and environmental data of the target infant 61 are further obtained. The modified urination pattern model 751 becomes a predictive model that is more suitable for the characteristics of the target infant 61.

Note that this model generation process can also be applied to the generation of the defecation pattern model of the target infant 61 by replacing urination data with defecation data, and the defecation pattern model may be generated using the urination data and defecation data.

(Caution notification processing)
FIG. 15 is a flowchart illustrating an example of the procedure of the caution notification process executed by the CPU 21 of the server device 2. As shown in FIG. The caution notification process is a process for notifying the caregiver 62 of changes in the physical condition of the target infant 61. For example, the CPU 21 executes the caution notification process every day.

The urination pattern model 751 corresponding to the target infant 61 is used in the attention notification process. At the beginning of the day, the CPU 21 determines whether the target infant 61 has woken up (step S11). The CPU 21 may determine whether the target infant 61 has woken up based on the environmental sensor 52 or may determine based on information input to the client device 3 from the childcare worker 62. For example, if the volume or illuminance measured by the environmental sensor 52 exceeds a preset threshold, it may be determined that the target infant 61 has woken up. The CPU 21 repeats this procedure until it determines that the target infant 61 has woken up (NO in step S21). When the CPU 21 determines that the target infant 61 has woken up, the CPU 21 moves to the next procedure (YES in step S21).

The CPU 21 predicts the next urination time from the previous urination data based on the urination pattern model 751 (step S22). When predicting the first urination time of the day after the target infant 61 wakes up, since there is no previous urination data, the first urination time is predicted from the wake-up time based on the urination pattern model 751. For example, the predicted urination time can be calculated using the above equation (1). Here, the last urination data of the previous day may be used as the previous urination data to predict the first urination time. Note that, after predicting the next urination time, the CPU 21 may notify the childcare worker 62 of the urination time via the client device 3 in advance of urination. The urination notice may be sent when the calculated predicted urination time approaches.

Based on the urination pattern model 751, the CPU 21 determines that the target infant 61 may be experiencing a change in physical condition when the target infant 61 does not urinate, and calculates a notification time for issuing a caution notification (step S23). Specifically, the CPU 21 calculates the predicted urination time calculated in step S22 by considering the deviations σT1 to σT4 of the urination pattern model 751 shown in FIG. 12. For example, in the above equation (2), the time interval T2 on the left side when the equation holds is calculated. Alternatively, the notification time may be a time when the actual micturition intervals T1 to T3 exceed a predetermined ratio based on the micturition intervals TB1 to TB3 predicted by the micturition pattern model 751. Here, the predetermined ratio is a numerical value at which it is determined that there is a possibility that a change in the physical condition of the target infant 61 has occurred.

After calculating the notification time, the CPU 21 determines whether the target infant 61 has urinated (step S24). Although the CPU 21 determines whether or not the child has urinated based on the urination data, the child care worker 62 may notify the server device via the client device 3 that the child has urinated. The CPU 21 determines whether or not the user has urinated until the notification time (NO in step S24, NO in step S26).

When determining that the target infant 61 has urinated, the CPU 21 determines whether the urination time is appropriate for the target infant 61 (step S25). Here, the CPU 21 determines whether the urination time of the target infant 61 is too early compared to the urination pattern model 751. Specifically, in consideration of the predicted urination time calculated in step S22 and the deviations σT1 to σT1 derived from the urination pattern model 751, it is determined whether the urination time is too early. In addition, as in the case where the urination time is too late, the determination may be made based on the ratio of the actual urination intervals T1 to T3 based on the urination intervals TB1 to TB3 predicted by the urination pattern model 751. If the CPU 21 determines that the urination time is appropriate (that is, there is no change in the physical condition of the subject infant 61), it predicts the next urination time again (NO in step S25, step S22).

If it is determined that the target infant 61 urinates too early (NO in step S25), or if the notification time has been reached without the target infant 61 urinating being confirmed (YES in step S26), the CPU 21 controls the client device 3. A notice of change in physical condition is sent to (step S27). That is, if the CPU 21 determines that there is a possibility that the physical condition of the target infant 61 has changed, it transmits a notice of the change in physical condition to the client device 3 .

(Appropriate environmental notification processing)
FIG. 16 is a flowchart illustrating an example of the procedure of the appropriate environment notification process executed by the CPU 21 of the server device 2. As shown in FIG. The appropriate environment notification process is a process for supporting the child care worker 62 in order to make the environment of the target infant 61 appropriate when a caution notice of a change in the physical condition of the target infant 61 is issued. The CPU 21 executes this process, for example, when it is determined by the caution notification process shown in FIG. 15 that a caution notification is to be sent to the client device 3.

As with the urination pattern model 751, an appropriate environment model may be generated by machine learning or the like, or criteria such as acceptable ranges may be determined in advance for each item of environmental data based on childcare knowledge, etc. good. Here, it is assumed that an appropriate environment model has been generated by learning using the personal database 231 of the infants 61 of the group to which the target infant 61 belongs. Here, the infants 61 in the personal database 231 used for learning may include the target infant 61, only the target infant 61, or may not include the target infant 61.

When the CPU 21 detects a change in physical condition, it starts the appropriate environment notification processing procedure (YES in step S31). A change in physical condition is detected, for example, when it is determined to send a warning notification of a change in physical condition through the warning notification process shown in FIG. 15 . The CPU 21 is on standby while not detecting a change in physical condition (NO in step S31).

When detecting a change in physical condition, the CPU 21 extracts environmental data for the most recent (or time determined based on the time of excretion) predetermined period from the personal database 231 of the subject infant 61 (step S32). The predetermined period is, for example, within one week, within three days, within 24 hours, within 12 hours, or within three hours.

The CPU 21 inputs the extracted environmental data for a predetermined period into the appropriate environment model, and determines the suitability of the environment for the target infant 61 for a predetermined period (step S33).

If there is environmental data that is determined to be inappropriate, the CPU 21 transmits the environmental data that is determined to be appropriate together with the inappropriate environmental data to the client device 3 (step S34).

Inappropriate environmental data is environmental data that indicates numerical values that may have an adverse effect on the target infant 61 in terms of temperature, humidity, sound volume, illuminance, or gas concentration. Specifically, the environmental data that is not appropriate is a temperature of 30° C., a humidity of 90%, or the like. On the other hand, environmental data that is considered appropriate is a temperature of 23° C. to 25° C. or a humidity of 55% to 65%. These criteria may be changed depending on the season or time zone. For example, the appropriate value of the volume or illuminance during the day may be higher than the appropriate value during the night. Further, the determination criteria may be changed depending on whether or not the target infant 61 is sleeping. Note that whether or not the target infant 61 is sleeping may be determined using a sensor or the like, or may be determined in any other manner.

In addition, the CPU 21 may transmit any information for optimizing the environment of the target infant 61 to the client device 3. For example, information such as recommending that the room temperature of the room where the target infant 61 is present or recommending that the target infant 61 drink water may be included.

(Growth level determination process)
FIG. 17 is a conceptual diagram showing the data flow of the growth degree determination process executed by the CPU 21 of the server device 2. As shown in FIG.

The growth level determination process is a process of determining whether or not the growth level of the target infant 61 is appropriate based on the excretion data stored in the personal database 231 or the latest urination pattern model 751 generated. This is a process for determining the age of the infant 61. The growth level determination process may be executed when the childcare worker 62 requests it via the client device 3, may be executed at regular intervals, or may be executed when preset criteria are met. Good too.

The childcare database 233 stores excretion data regarding a plurality of infants 61 other than the target infant 61. The CPU 21 extracts excretion related data 233a to 233x from the childcare database 233 by age (or age) of 1 to 24 months. The excretion-related data is data representing a daily excretion pattern corresponding to the urination pattern model 751, for example. Here, the age is up to 24 months, but it may be up to any number of months (or years). The excretion-related data includes data corresponding to at least multiple excretion data, but may also include other data. For example, the excretion-related data may include information such as height, weight, or gender. Furthermore, it is not necessary to extract excretion-related data of the infant 61 that has attributes (such as gender) that are different from the target infant 61 or values that are clearly different from the target infant 61 (height or weight equivalent). Furthermore, only the excretion-related data of the infant 61 having attributes similar to the target infant 61 may be extracted.

The CPU 21 calculates the excretion standards Ra to Rx of the infant 61 by age based on the excretion related data 233a to 233x by age. For example, the excretion standards Ra to Rx are standard values or average values of the number of excretions or intervals of excretion for the infant 61 of the same age. The excretion standards Ra to Rx may be any value as long as the age of the infant 61 can be determined from the excretion pattern as shown by the urination pattern model 751.

The CPU 21 determines the growth degree determination unit 501 based on the calculated results of the calculated excretion standards Ra to Rx by age. The growth degree determination unit 501 is a calculation unit that determines the growth degree of the target infant 61 based on the excretion related data of the target infant 61.

Next, a method for determining the growth level of the target infant 61 by the growth level determination unit 501 will be explained.
The growth degree determination unit 501 estimates the age in months of the target infant 61 based on excretion-related data input from the target infant 61's personal database 231B. The growth degree determining unit 501 compares the estimated age in months with the actual age in months of the target infant 61 stored in the personal characteristics table 232 to determine the degree of growth. If the estimated age in months is behind the actual age in months, the growth degree determination unit 501 notifies the client device 3 that the growth of the target infant 61 is delayed, and determines that the estimated age in months is ahead of the actual age in months. If so, the client device 3 is notified that growth is progressing or growth is going well. At this time, the growth degree determination unit 501 may include the estimated lunar age in the information notified to the client device 3.

The growth degree determining unit 501 may use the growth curve data D1 and the childcare knowledge data D2 to determine the degree of growth, such as estimating the age in months.

The growth curve data D1 is created based on accumulated data of infants 61 close to the target infant 61, and is data showing a growth curve representing the relationship between excretion and growth. The infant 61 close to the target infant 61 may be an infant 61 belonging to the same group as the target infant 61, or may be determined by individually or comprehensively determining weight, height, place of birth, place of residence, etc.

The childcare knowledge data D2 may be data accumulated in the childcare database 233, or may be data stored for determining the degree of growth. For example, even if the estimated lunar age and the actual lunar age are significantly different, the growth level determining unit 501 may determine that the growth level is OK or going well based on the childcare knowledge data D2. can.

According to the present embodiment, by accumulating excretion data and environmental data in relation to time, and determining an excretion pattern including an excretion cycle (for example, by modeling using machine learning), changes in the physical condition of the target infant 61 can be monitored. can be grasped.

Regarding the embodiments of the present invention described above, the following additional notes are further disclosed.
<1>
a server device;
a client device that communicates with the server device;
an excretion sensor that detects the excretion of a childcare subject;
an environmental sensor that detects environmental information indicating the environment of the subject;
The client device includes:
Excretion information transmitting means for transmitting excretion information indicating that the excretion has been detected by the excretion sensor to the server device;
environmental information transmitting means for transmitting the environmental information detected by the environmental sensor to the server device;
an environmental appropriateness information receiving means for receiving environmental appropriateness information received from the server device and including a determination result of determining the appropriateness of the environment of the subject;
The server device includes:
storage means for storing the excretion information and the environmental information received from the client device in association with time;
an excretion cycle determining means for determining an excretion cycle of the subject based on the excretion information stored in the storage means;
Determining the appropriateness of the environment of the subject based on the excretion information stored in the storage means, the excretion cycle determined by the excretion cycle determining means, and the environmental information stored in the storage means. Environmental appropriateness judgment means,
an environmentally appropriate information generating means for generating the environmentally appropriate information including a determination result by the environmentally appropriate determining means;
and an environmentally appropriate information transmitting means for transmitting the environmentally appropriate information generated by the environmentally appropriate information generating means to the client device;
A childcare support system featuring:
<2>
The childcare support system according to <1>, wherein the environmental information includes at least one of temperature, humidity, sound volume, illuminance, or gas concentration.
<3>
The childcare support according to <1> or <2>, wherein the environmental appropriateness information includes at least one of information regarding an inappropriate environment for the target person, or information for making the target person's environment appropriate. system.
<4>
The server device may include physical condition change determination means for determining a change in physical condition of the subject based on the excretion information stored in the storage means and the excretion cycle determined by the excretion cycle determination means. The childcare support system according to any one of <1> to <3>.
<5>
Any one of <1> to <4>, wherein the server device includes growth degree determining means for determining the degree of growth of the subject based on the excretion cycle determined by the excretion cycle determining means. Childcare support system described in .
<6>
The childcare support system according to any one of <1> to <5>, wherein the excretion cycle determining means determines the excretion cycle based on a predictive model learned from information regarding excretion of a plurality of infants.
<7>
The childcare according to any one of <1> to <6>, wherein the environment suitability determination means determines the suitability of the target person's environment based on a predictive model learned from information regarding the environment of a plurality of infants. support system.
<8>
The childcare support system according to any one of <1> to <7>, wherein the client device includes a feedback sending unit that sends feedback data indicating an evaluation regarding the information received from the server device to the server device.
<9>
The childcare support system according to <8>, wherein the excretion cycle determining means determines the excretion cycle based on the feedback data received from the client device.
<10>
The childcare support system according to <8> or <9>, wherein the environment suitability determining means determines the suitability of the environment for the subject based on the feedback data received from the client device.
<11>
a storage means for storing excretion information detected by an excretion sensor and indicating that the childcare subject's excretion has been detected, and environmental information detected by the environmental sensor and indicating the environment of the subject in association with time;
an excretion cycle determining means for determining an excretion cycle of the subject based on the excretion information stored in the storage means;
Determining the appropriateness of the environment of the subject based on the excretion information stored in the storage means, the excretion cycle determined by the excretion cycle determining means, and the environmental information stored in the storage means. Environmental appropriateness judgment means,
A childcare support device comprising: environmental appropriateness information generation means for generating environmental appropriateness information including a determination result by the environmental appropriateness determination means.
<12>
The childcare support device according to <11>, wherein the environmental information includes at least one of temperature, humidity, sound volume, illuminance, or gas concentration.
<13>
The childcare support according to <11> or <12>, wherein the environmental appropriateness information includes at least one of information regarding an inappropriate environment of the target person, or information for making the target person's environment appropriate. Device.
<14>
<11> to <13>, comprising a physical condition change determination means for determining a physical condition change of the subject based on the excretion information stored in the storage means and the excretion cycle determined by the excretion cycle determination means. >The childcare support device according to any one of the above.
<15>
The childcare support device according to any one of <11> to <14>, comprising a growth degree determination means for determining the growth degree of the subject based on the excretion cycle determined by the excretion cycle determination means. .
<16>
The childcare support device according to any one of <11> to <15>, wherein the excretion cycle determining means determines the excretion cycle based on a predictive model learned from information regarding excretion of a plurality of infants.
<17>
The childcare according to any one of <11> to <16>, wherein the environmental appropriateness judgment means judges the appropriateness of the environment of the subject based on a predictive model learned from information regarding the environment of a plurality of infants. Support equipment.
<18>
The childcare support device according to any one of <11> to <17>, further comprising a feedback input means for inputting feedback data indicating an evaluation regarding the childcare information.
<19>
The childcare support device according to <18>, wherein the excretion cycle determining means determines the excretion cycle based on the feedback data input by the feedback input means.
<20>
The childcare support device according to <18> or <19>, wherein the environment suitability determining means determines the suitability of the environment of the subject based on the feedback data input by the feedback input means.
<21>
storing excretion information detected by an excretion sensor and indicating that excretion of a person to be cared for has been detected, and environmental information detected by an environment sensor and indicating the environment of the subject in relation to time;
determining an excretion cycle of the subject based on the stored excretion information;
determining the appropriateness of the environment of the subject based on the stored excretion information, the determined excretion cycle, and the stored environmental information;
A childcare support method comprising: generating environmental appropriateness information including a determination result of determining the appropriateness of the environment.

1 Childcare support system 2 Server device 21 CPU
22 RAM
221 OS
222 Childcare support server program 23 Storage device 231 Personal database 231A Personal database of other infants belonging to the same group 231B Personal database of target infant 232 Individual characteristic table 233 Childcare database 234 Group information 24 Communication department 3 Client device 31 CPU
32 RAM
321 OS
322 Childcare support client program 33 Storage device 34 Touch screen display 35 First communication unit 36 Second communication unit 37 Vibration unit 38 Speaker 4 Network 5 Sensor 51 Excretion sensor 52 Environment sensor 53 Posture sensor 54 Movement sensor 61 Infant 62 Child care worker 71 Learning 75 Prediction model 751 Urination pattern model 401 Storage processing section 402 Group determination section 403 Learning section 404 Judgment section 405 Generation section 406 Transmission processing section 501 First reception processing section 502 Transmission processing section 503 Second reception processing section 504 Notification processing section 601 Growth Degree judgment part

Claims (7)

a server device;
a client device that communicates with the server device;
an excretion sensor that detects the excretion of a childcare subject;
an environmental sensor that detects environmental information indicating the environment of the subject;
The client device includes:
Excretion information transmitting means for transmitting excretion information indicating that the excretion has been detected by the excretion sensor to the server device;
environmental information transmitting means for transmitting the environmental information detected by the environmental sensor to the server device;
environment judgment information receiving means for receiving environment-related information from the server device based on a judgment result of judging the suitability of the environment of the subject;
The server device includes:
storage means for storing the excretion information and the environmental information received from the client device in association with time;
an excretion cycle determining means for determining an excretion cycle of the subject based on the excretion information stored in the storage means and the time associated with the excretion information;
If it is determined that the time associated with the excretion information stored in the storage means is not appropriate based on the predicted time predicted from the excretion cycle determined by the excretion cycle determination means, the subject is informed of the physical condition of the subject. Physical condition change detection means for detecting that a change has occurred;
When it is detected by the physical condition change detection means that a physical condition change has occurred in the subject, the time is determined based on the time included in the environmental information stored in the storage means and associated with the excretion information. environmental suitability determining means for determining the suitability of the environment for the subject for the predetermined period based on the environmental information for the predetermined period and environmental judgment criteria;
and an environment judgment information transmitting means for transmitting to the client device the environmental information indicating that the environment of the subject for the predetermined period is not suitable as determined by the environment suitability determining means. The childcare support system according to claim 1, wherein the environmental information includes at least one of temperature, humidity, sound volume, illuminance, and gas concentration. According to claim 1 or claim 2 , the server device comprises a growth degree determination means for determining the growth degree of the subject based on the excretion cycle determined by the excretion cycle determination means. Childcare support system described. a storage means for storing excretion information indicating that the excretion of the childcare subject has been detected by the excretion sensor and environmental information indicating the environment of the subject detected by the environmental sensor in relation to time;
an excretion cycle determining means for determining an excretion cycle of the subject based on the excretion information stored in the storage means and the time associated with the excretion information;
If it is determined that the time associated with the excretion information stored in the storage means is not appropriate based on the predicted time predicted from the excretion cycle determined by the excretion cycle determination means, the subject is informed of the physical condition of the subject. Physical condition change detection means for detecting that a change has occurred;
When it is detected by the physical condition change detection means that a physical condition change has occurred in the subject, the time is determined based on the time included in the environmental information stored in the storage means and associated with the excretion information. environmental suitability determining means for determining the suitability of the environment for the subject for the predetermined period based on the environmental information for the predetermined period and environmental judgment criteria;
A childcare support device comprising: environmental judgment information notifying means for notifying environmental information indicating that the environment of the subject for the predetermined period is not appropriate as judged by the environmental appropriateness judging means. 5. The childcare support device according to claim 4 , wherein the environmental information includes at least one of temperature, humidity, volume, illuminance, and gas concentration. The childcare support device according to claim 4 or 5 , further comprising growth degree determining means for determining the degree of growth of the subject based on the excretion cycle determined by the excretion cycle determining means. . storing excretion information indicating that the excretion of the childcare subject has been detected by the excretion sensor and environmental information indicating the environment of the subject detected by the environment sensor in association with time;
determining an excretion cycle of the subject based on the stored excretion information and the time associated with the excretion information;
If it is determined that the time associated with the stored excretion information is not appropriate based on the predicted time predicted from the determined excretion cycle, detecting that a physical condition change has occurred in the subject;
When it is detected that a physical condition change has occurred in the subject, the environmental information for a predetermined period determined based on the time included in the stored environmental information and associated with the excretion information, and judgment regarding the environment. determining the suitability of the environment for the subject for the predetermined period based on a criterion;
A childcare support method comprising: notifying the environment information that the environment of the subject has been determined to be inappropriate for the predetermined period of time.

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