JP7510699B2 - Drone drug spraying flight control method and information processing terminal - Google Patents

Description

The present invention relates to a drone pesticide spraying flight control method and an information processing terminal.

JP 2019-64544 A (Patent Document 1) is a background technology in this technical field. This publication states that "The aerial spraying device 11 (unmanned aerial vehicle system 10) includes one or more drones (unmanned aerial vehicles) 14 and a ground station 12 that is wired to at least one of the one or more drones 14. The drone 14 includes a drone-side cable 86 that is connected to the station 12 or another drone 14, and a drone-side cable mechanism unit 108 that retracts or reels in the drone-side cable 86" (see abstract).

JP 2019-64544 A

The above-mentioned Patent Document 1 describes a drone that sprays a spraying agent. However, the configuration of this Patent Document 1 allows power supply and fuel to be replenished from a station, and does not manage the amount of agent or energy required for a spraying flight. In addition, the spraying agent can only be sprayed to fields within a certain distance from the station, and the schedule of spraying flights to multiple fields is not managed.
Therefore, the present invention provides a mechanism for easily managing pesticide spraying schedules by breaking down the conditions to be considered for spraying flights and performing route search processing based on these conditions to generate a spraying flight schedule.

In order to solve the above problems, for example, the configurations described in the claims are adopted.
The present application includes multiple means for solving the above-mentioned problems, and one example is an information processing device that controls the spraying flight of a drone that sprays pesticides, comprising a memory unit that stores multiple pieces of field information, an output unit that outputs multiple pieces of field information, an input unit that accepts selection from multiple fields, and a control unit that controls the spraying flight of the drone that sprays pesticides, wherein the control unit calculates the spraying flight time for each of the multiple fields selected via the input unit and the travel time for traveling between each of the fields, generates a pesticide spraying schedule based on the calculated spraying flight time, the travel time, and constraint conditions, and the output unit outputs the generated pesticide spraying schedule.

According to the present invention, the conditions to be considered for a spraying flight are broken down and a route search process is performed based on these conditions to generate a schedule for the spraying flight, thereby making it easier to manage the pesticide spraying schedule.
Problems, configurations and effects other than those described above will become apparent from the following description of the embodiments.

1 is an example of a drone floor plan. 1 is an example of a front view of a drone. 1 is an example of a right side view of a drone. 1 is an example of a rear view of a drone. 1 is an example of a perspective view of a drone. 1 is an example of a block diagram showing the control functions of a drone. An example of a connection configuration diagram of the entire drone management system 700. 8 is an example of a farm field information display screen 800 displayed on a mobile terminal 701. 9 is an example of a drone operation screen 900 displayed on a mobile terminal 701. 7 is an example of a hardware configuration of a mobile terminal 701. 7 is an example of a hardware configuration of a management server 702. 7 is an example of a hardware configuration of a management terminal 703. 13 is an example of farm field management information 1300. 14 is an example of device management information 1400. 15 is an example of user management information 1500. 16 is an example of medicine management information 1600. 17 is an example of energy management information 1700. 18 is an example of flight route management information 1800. 19 is an example of schedule management information 1900. 2 illustrates an example of a screen display process flow 2000. 2 is an example of a flight path output process flow 2100. 22 illustrates an example of a process flow 2200 for outputting scattering-related information. 13 is a display example of the spraying information display area 820 of the farm field information display screen 800. is an example of the display of spray flight progress information 912 on the drone operation screen 900. 1 is an example of a schematic diagram showing the relationship between the amount of sprayed pesticide payload and the available flight time. 1 is an example of a schematic diagram showing the relationship between the amount of sprayed pesticide loaded and the amount of battery drain. 27 is an example of a display screen 2700 showing a schedule for spraying a chemical for multiple fields. 28 is an example of a display screen 2800 of a drug dispersion schedule for multiple days. This is an example of a screen (changing) 2900 for changing a drug dispersion schedule. This is an example of a screen (after change) 3000 for changing the drug dispersion schedule. 31 illustrates an example of a schedule information display process flow 3100. 32 illustrates an example of a schedule management information output process flow 3200. 3 shows an example of a dispersion flight time calculation process flow 3300. 3 illustrates an example of a travel time calculation process flow 3400. An example of a process flow 3500 for generating a route search model using AI. This is an example of a schedule information output process flow 3600 using AI. 37 is an example of a display screen 3700 displaying information regarding an upcoming spray flight. 38 is another example of a display screen 3800 displaying information regarding an upcoming dispersal flight. The following is an example of a dispersion flight information display process flow 3900. 1 is an example of a schematic diagram showing the relationship between the amount of sprayed pesticide and the notification time.

Hereinafter, the embodiments will be described with reference to the drawings.
A drone is an example of an agricultural machine. In this specification, a drone refers to any flying object having multiple rotors, regardless of the power source (electricity, prime mover, etc.) or the control method (wireless or wired, autonomous or manually controlled, etc.).

FIG. 1 is an example of a plan view of a drone.
FIG. 2 is an example of a front view of a drone.
FIG. 3 is an example of a right side view of a drone.
FIG. 4 is an example of a rear view of a drone.
FIG. 5 is an example of a perspective view of a drone.

The rotors 101-1a, 101-1b, 101-2a, 101-2b, 101-3a, 101-3b, 101-4a, and 101-4b (also called rotors) are means for flying the drone 100, and eight of them (four sets of two-stage rotors) are provided, taking into consideration the balance between flight stability, aircraft size, and power consumption. Each rotor 101 is arranged on all four sides of the main body 110 of the drone 100 by arms extending from the main body 110. That is, the rotors 101-1a and 101-1b are arranged at the left rear of the direction of travel, the rotors 101-2a and 101-2b are arranged at the left front, the rotors 101-3a and 101-3b are arranged at the right rear, and the rotors 101-4a and 101-4b are arranged at the right front. Note that the direction of travel of the drone 100 is downward on the paper in FIG. 1. Rod-like legs 107-1, 107-2, 107-3, and 107-4 extend downward from the rotation axis of the rotor 101.

Motors 102-1a, 102-1b, 102-2a, 102-2b, 102-3a, 102-3b, 102-4a, and 102-4b are means (typically electric motors, but may be engines, etc.) for rotating rotors 101-1a, 101-1b, 101-2a, 101-2b, 101-3a, 101-3b, 101-4a, and 101-4b, and one is provided for each rotor. Motor 102 is an example of a propulsion device. The upper and lower rotors (e.g., 101-1a and 101-1b) in one set and their corresponding motors (e.g., 102-1a and 102-1b) have axes that are on the same line and rotate in opposite directions to each other for the stability of the drone's flight, etc.

As shown in Figures 2 and 3, the radial members supporting the propeller guard, which is installed to prevent the rotor from interfering with foreign objects, are not horizontal but have a tower-like structure. This is to encourage the members to buckle toward the outside of the rotor blades in the event of a collision, preventing them from interfering with the rotor.

Chemical nozzles 103-1, 103-2, 103-3, and 103-4 are means for spraying chemicals downward, and four of them are provided. In this specification, chemicals refer to liquids, powders, or fine particles that are sprayed on a field, such as pesticides, herbicides, liquid fertilizers, insecticides, seeds, and water.

The chemical tank 104 is a tank for storing the chemical to be sprayed, and is located close to and lower than the center of gravity of the drone 100 from the viewpoint of weight balance. Chemical hoses 105-1, 105-2, 105-3, and 105-4 connect the chemical tank 104 to each chemical nozzle 103-1, 103-2, 103-3, and 103-4. The chemical hoses are made of a hard material, and may also serve to support the chemical nozzles. The pump 106 is a means for ejecting the chemical from the nozzles.

FIG. 6 is an example of a block diagram showing the control functions of a drone.
The flight controller 501 is a component that controls the entire drone, and may be an embedded computer including a CPU, memory, related software, etc. Based on input information received from the controller 401 and input information obtained from various sensors described below, the flight controller 501 controls the rotation speed of the motors 102-1a, 102-1b, 102-2a, 102-2b, 102-3a, 102-3b, 104-a, and 104-b via control means such as an ESC (Electronic Speed Control), thereby controlling the flight of the drone 100. The actual rotation speeds of the motors 102-1a, 102-1b, 102-2a, 102-2b, 102-3a, 102-3b, 104-a, and 104-b are fed back to the flight controller 501, and it is configured to be able to monitor whether normal rotation is being performed. Alternatively, an optical sensor or the like may be provided on the rotor 101 so that the rotation of the rotor 101 is fed back to the flight controller 501.

The software used by the flight controller 501 can be rewritten through a storage medium or through a communication means such as Wi-Fi or USB for function expansion/change, problem correction, etc. In this case, protection is provided by encryption, checksum, electronic signature, virus check software, etc. to prevent rewriting by unauthorized software. In addition, some of the calculation processes used by the flight controller 501 for control may be executed by another computer located on the operation device 401, the farming cloud 405, or elsewhere. Because the flight controller 501 is important, some or all of its components may be duplicated.

The flight controller 501 communicates with the mobile terminal 701 via the Wi-Fi slave function 503 and further via the base station 710, and can receive necessary commands from the mobile terminal 701 and transmit necessary information to the mobile terminal 701. In this case, the communication may be encrypted to prevent fraudulent acts such as interception, spoofing, and device hijacking. In addition to the communication function via Wi-Fi, the base station 404 also has the function of an RTK-GPS base station. By combining the signal from the RTK base station and the signal from the GPS positioning satellite, the flight controller 501 can measure the absolute position of the drone 100 with an accuracy of about a few centimeters. Since the flight controller 501 is highly important, it may be duplicated or multiplexed, and in order to respond to a failure of a specific GPS satellite, each redundant flight controller 501 may be controlled to use a different satellite. In addition, communication between the flight controller 501, the base station 710, and the mobile terminal 701 may use a mobile network such as LTE instead of Wi-Fi.

The six-axis gyro sensor 505 measures the acceleration of the drone body in three mutually perpendicular directions. Furthermore, the speed is calculated by integrating the acceleration. The six-axis gyro sensor 505 measures the change in the attitude angle of the drone body in the above-mentioned three directions, i.e., the angular velocity. The geomagnetic sensor 506 measures the direction of the drone body by measuring the geomagnetism. The air pressure sensor 507 measures the air pressure and can also indirectly measure the altitude of the drone. The laser sensor 508 measures the distance between the drone body and the ground surface by using the reflection of laser light, and may be an IR (infrared) laser.

Sonar 509 measures the distance between the drone body and the ground surface by using the reflection of sound waves such as ultrasonic waves. These sensors may be selected according to the cost target and performance requirements of the drone. In addition, a gyro sensor (angular velocity sensor) for measuring the inclination of the drone body, a wind sensor for measuring wind force, etc. may be added. In addition, these sensors may be duplicated or multiplexed. If there are multiple sensors for the same purpose, the flight controller 501 may use only one of them, and if a failure occurs, it may switch to an alternative sensor. Alternatively, multiple sensors may be used simultaneously, and if the measurement results of each sensor do not match, it may be considered that a failure has occurred.

The flow rate sensor 510 measures the flow rate of the chemical, and is provided at multiple locations on the path from the chemical tank 104 to the chemical nozzle 103. The liquid shortage sensor 511 is a sensor that detects when the amount of chemical falls below a predetermined amount. The multispectral camera 512 is a means for photographing the field 403 and acquiring data for image analysis. The obstacle detection camera 513 is a camera for detecting obstacles, and is a separate device from the multispectral camera 512 because its image characteristics and lens orientation differ from those of the multispectral camera 512.

Switch 514 is a means for the user of drone 100 to make various settings. Obstacle contact sensor 515 is a sensor for detecting when drone 100, particularly its rotor or propeller guard, comes into contact with an intruder such as an electric wire, building, human body, tree, bird, or other drone. Note that obstacle contact sensor 515 may be substituted with 6-axis gyro sensor 505. Cover sensor 516 is a sensor for detecting when the operation panel or internal maintenance cover of drone 100 is open.

The drug injection port sensor 517 is a sensor that detects that the injection port of the drug tank 104 is open. These sensors may be selected according to the cost target and performance requirements of the drone, and may be duplicated or multiplexed. In addition, a sensor may be provided at the base station 710, the mobile terminal 701, or other location outside the drone 100, and the read information may be transmitted to the drone 100. For example, a wind sensor may be provided at the base station 404, and information regarding wind force and direction may be transmitted to the drone 100 via Wi-Fi communication.

The flight controller 501 transmits a control signal to the pump 106 to adjust the amount of drug ejection or stop drug ejection. The current status of the pump 106 (e.g., rotation speed, etc.) is fed back to the flight controller 501.

The LED 107 is a display means for informing the drone operator of the drone's status. A display means such as a liquid crystal display may be used instead of or in addition to the LED. The buzzer 518 is an output means for informing the drone's status (particularly an error state) by an audio signal. The Wi-Fi slave function 519 is an optional component for communicating with an external computer, etc., for example, for software transfer, etc., separately from the mobile terminal 701. Instead of or in addition to the Wi-Fi slave function, other wireless communication means such as infrared communication, Bluetooth (registered trademark), ZigBee (registered trademark), NFC, or wired communication means such as a USB connection may be used. In addition, the communication between the flight controller 501, the mobile terminal 701, and the base station 710 may be possible by a mobile communication system such as 3G, 4G, and LTE, instead of the Wi-Fi slave function.

The speaker 520 is an output means for informing the user of the drone's status (particularly an error state) by recorded voice or synthetic voice, etc. Depending on the weather conditions, the visual display of the drone 100 in flight may be difficult to see, and in such cases, audio transmission of the situation is effective. The warning light 521 is a display means such as a strobe light for informing the user of the drone's status (particularly an error state). These input/output means may be selected according to the drone's cost targets and performance requirements, and may be duplicated or multiplexed.

FIG. 7 is an example of a connection configuration diagram of the entire drone management system 700.
The drone management system 700 includes a drone 100, a mobile terminal 701, a management terminal 703, and a base station 710, each of which is connected to a management server 702 via a network. Note that the network may be wired or wireless, and each terminal can transmit and receive information via the network.
The drone 100 and the mobile terminal 701 can communicate via a base station 710 in a farm field 720, and the drone 100 performs a flight to spray pesticide.

The network may be a network that communicates according to one communication standard, or a network that combines networks of multiple communication standards. For example, the drone 100 and the mobile terminal 701 may each be network-connected via Wi-Fi provided by a base station 710, or the drone 100 and the mobile terminal 701 may each be network-connected via a mobile communication network such as LTE. Alternatively, the drone 100 may be connected via Wi-Fi provided by the base station 710, and the base station 710 and the mobile terminal 701 may be connected via a mobile communication network.

The mobile terminal 701 transmits commands to the drone 100 by operation of the user, and also displays information received from the drone 100 (e.g., location, amount of drug, remaining battery level, camera footage, etc.). For example, it is realized by a portable information device such as a tablet terminal or a smartphone. The drone 100 performs autonomous flight according to instructions from the management server 702, but the mobile terminal 701 can be used to manually operate the drone during basic operations such as takeoff and return, and in emergencies. The mobile terminal 701 is connected to a base station 710, and can communicate with the management terminal 703 via the base station 710 or directly.

The management server 702 is, for example, a server deployed on the cloud, and calculates the spraying flight route of the drone 100 based on the field management information 1300, and controls the autonomous flight of the drone 100. In addition, the management server 702 can collect information acquired from the camera and various sensors mounted on the drone 100, and perform various analyses such as the condition of the field and the crops.
The management terminal 703 is a terminal that operates the management server 702 and performs various settings of the management server 702. The management terminal 703 is also capable of controlling the drone 100 and the mobile terminal 701.

The base station 710 is a device installed in the field 720 that provides a base station function for Wi-Fi communication and the like, and also functions as an RTK-GPS base station, making it possible to provide the exact position of the drone 100 (the base station function for Wi-Fi communication and the RTK-GPS base station may be independent devices). The base station 710 can also communicate with the management server 702 using mobile communication networks such as 3G, 4G, and LTE.

Each terminal and management server 702 of the drone management system 700 may be, for example, a mobile terminal such as a smartphone, tablet, mobile phone, or personal digital assistant (PDA), or a wearable terminal such as glasses, wristwatch, or clothing. They may also be stationary or mobile computers, or servers located on the cloud or network. In terms of function, they may be a VR (Virtual Reality) terminal, an AR terminal, or an MR (Mixed Reality) terminal. Or they may be a combination of multiple terminals. For example, a combination of one smartphone and one wearable terminal may function logically as one terminal. They may also be other information processing terminals.

Each terminal and management server 702 of the drone management system 700 includes a processor (control unit) that executes an operating system, applications, programs, etc., a main storage device such as a RAM (Random Access Memory), an auxiliary storage device such as an IC card, a hard disk drive, an SSD (Solid State Drive), or a flash memory, a communication control unit such as a network card, a wireless communication module, or a mobile communication module, input devices such as a touch panel, a keyboard, a mouse, voice input, or input based on motion detection by capturing images from a camera unit, and an output device such as a monitor or display. The output device may be a device or terminal that transmits information to be output to an external monitor, display, printer, or device.

The main memory stores various programs, applications, etc. (modules), and the processor executes these programs and applications to realize each functional element of the overall system. Each of these modules may be implemented in hardware, for example by integration. Each module may be an independent program or application, or may be implemented as a subprogram or function within a single integrated program or application.

In this specification, each module is described as an entity (subject) that performs processing, but in reality, the processing is carried out by a processor that processes various programs, applications, etc. (modules).
Various databases (DB) are stored in the auxiliary storage device. A "database" is a functional element (storage unit) that stores a data set so that it can handle any data operation (e.g., extraction, addition, deletion, overwriting, etc.) from a processor or an external computer. The method of implementing the database is not limited, and may be, for example, a database management system, spreadsheet software, or a text file such as XML or JSON.
The mobile terminal 701 may be called an information processing device, and the management server 702 may be called an information processing device.

FIG. 8 shows an example of a farm field information display screen 800 displayed on the mobile terminal 701.
The screen display module 1011 of the mobile terminal 701 acquires the map information 1200 and the field management information 1300 stored in the mobile terminal 701, generates the field information display screen 800, and outputs it to the output device 1005 such as a screen.
The screen display module 1011 may be configured to acquire the map information 1200 and the farm field management information 1300 stored in the management server 702 via a network, and generate the farm field information display screen 800 .

A map 801 is displayed on the back of the field information display screen 800, and anchors 805 are displayed for fields 802, 803, and 804 whose field information is stored in the field management information 1300, indicating that information has been registered.
The field is a rice field, a farm field, etc. that is the target of pesticide spraying by the drone 100. In reality, the topography of the field is complex, and there are cases where a topographical map cannot be obtained in advance, or where the topographical map and the actual situation are inconsistent. Usually, the field is adjacent to houses, hospitals, schools, other crop fields, roads, railways, etc. In addition, there may be intruders such as buildings and electric wires in the field. The field is one example of an area that is the target of pesticide spraying.

When the screen display module 1011 receives a selection of a field 802 from the user via the input device 1004, such as by tapping the screen, it obtains information corresponding to the field 802 from the field management information 1300 and displays it in the field information display area 810. The screen display module 1011 also highlights the selected field 802 to indicate that it has been selected, for example by changing the periphery of the selected field 802 to a thick, light-colored line.

The field information display area 810 displays information acquired from the field management information 1300, such as the field name 811, address 812, area 813, and cultivated crop name 814.
Information related to spraying of the pesticide is displayed in the spray information display area 820. The pesticide to be sprayed varies depending on the name of the cultivated crop 814 and the spraying time, and information on the pesticide to be sprayed in the near future is obtained from the pesticide management information 1600 and displayed.
The spraying information display area 820 displays information related to the spraying of pesticides acquired or calculated by the spraying-related information management module 1114 of the management server 702, such as the name of the pesticide, the amount to be sprayed, the dilution amount, and the amount of energy required for the spraying flight in the field.
Status 830 displays information such as "surveyed" or "flight path exists" as the current status of the selected field 802.
Latest flight date and time 840 displays information on the date and time of the latest dispersion flight.
The flight status display section 850 displays the current status of the drone's spraying flight.

Compass 861 indicates the direction that map 801 is displaying.
When the display entire field button 862 is selected, the screen display module 1011 changes the scale of the display so that the selected field fills the entire screen.
When the current location movement button 863 is selected, the screen display module 1011 changes the display so that the current location acquired by the GPS of the mobile terminal 701 is at the center of the screen.
When the schedule display button 870 is selected, the screen display module 1011 displays the drug dispersion schedule for that day.

FIG. 9 is an example of a drone operation screen 900 displayed on the mobile terminal 701.
The drone battery display 901 displays the current remaining battery power of the drone.
Drone position 902 displays the current position information of drone 100.
The spraying flight progress information 912 displays progress information of the current spraying flight, such as the progress of the flight route of the spraying flight, the remaining amount of sprayed chemical, the remaining battery charge, and the like.
The flight status display field 921 displays the current status of the drone 100's spraying flight.
The message display section 922 displays messages indicating the content of communication with the drone 100, the flight status, etc.

The altitude change buttons 923 and 924 are buttons for changing the flight altitude of the drone 100. Pressing the minus button decreases the altitude, and pressing the plus button increases the altitude.
The emergency stop button 925 is a button for emergency stopping the drone 100 in flight, and in addition to pausing the drone 100 to hover on the spot, it can also display options for returning to the starting point of flight and for emergency stopping the motor on the spot.
In the example of the drone operation screen 900, a field 930 to be sprayed with a pesticide is displayed on a map, along with a flight path 931 of the spraying flight over the field 930. The drone 100 flies in sequence through the specified flight coordinates in accordance with flight path management information 1800 stored in the mobile terminal 701 or the management server 702.

When an operation that requires operation of the drone 100, such as the altitude change buttons 923, 924 or the emergency stop button 925, is received, the drone operation module 1012 can transmit information such as commands corresponding to these operations to the drone 100, thereby operating the drone 100.
The next spraying schedule display button 940 is a button for displaying the schedule of the spraying flight next to the currently executed spraying flight. When this button is pressed, information about the next spraying flight obtained from the schedule management information 1900 is displayed.

FIG. 10 shows an example of the hardware configuration of the mobile terminal 701 .
The mobile terminal 701 is, for example, a tablet, a smartphone, a head-mounted display, or the like.
The main memory device 1001 stores programs and applications such as a screen display module 1011, a drone operation module 1012, and a schedule management module 1013, and each functional element of the mobile terminal 701 is realized by the processor 1003 executing these programs and applications.
The screen display module 1011 displays the farm field information display screen 800 and the drone operation screen 900 on an output device 1005 such as a display panel.

When the drone operation module 1012 receives user operation of the altitude change buttons 923, 924, the emergency stop button 925, etc., it transmits information such as commands corresponding to these operations to the drone 100 and controls the drone's flight.
The schedule management module 1013 manages the schedule of each spraying flight when spraying flights are carried out consecutively over multiple fields.
The auxiliary memory device 1002 stores various information such as map information 1200, field management information 1300, equipment management information 1400, user management information 1500, drug management information 1600, energy management information 1700, flight path management information 1800, and schedule management information 1900.

FIG. 11 shows an example of the hardware configuration of the management server 702 .
The management server 702 is configured, for example, by a server placed on a cloud.
The main memory device 1101 stores a screen output module 1111, a flight management module 1112, a user/equipment management module 1113, a spraying-related information management module 1114, a flight path management module 1115, and a schedule management module 1116, and each functional element of the management server 702 is realized by the processor 1103 executing these programs and applications.
The screen output module 1111 extracts and generates information for displaying the farm field information display screen 800 and the drone operation screen 900, and transmits it to the mobile terminal 701. The screen information itself may be generated and displayed on the mobile terminal 701, etc.
The flight management module 1112 manages the spraying flight of the drone 100 based on information such as the field management information 1300 and flight path management information 1800.

The user/equipment management module 1113 registers and manages information regarding users who use the drone 100 in the user management information 1500.
The spraying-related information management module 1114 manages the amount of pesticide sprayed, the amount of pesticide, the dilution amount, the amount of water required for dilution, and the amount of energy such as the number of batteries required for a spraying flight.
The flight path management module 1115 calculates the flight path of the drone 100's spraying flight based on the field management information 1300.
The schedule management module 1116 generates and manages schedules for multiple fields and spraying flights spanning multiple days. The generated chemical spraying schedules are stored in the schedule management information 1900.

The auxiliary memory device 1102 stores various types of information such as map information 1200, field management information 1300, equipment management information 1400, user management information 1500, drug management information 1600, energy management information 1700, flight path management information 1800, and schedule management information 1900.
Although the same information is stored in the mobile terminal 701 and the management server 702, the respective pieces of information may be synchronized, or the information may simply be copied from one of them. Also, a configuration may be adopted in which some or all of the information is stored on the management server 702, and the mobile terminal 701 downloads information from the management server 702 as necessary.

FIG. 12 shows an example of the hardware configuration of the management terminal 703 .
The management terminal 703 is, for example, a desktop PC, a notebook PC, a tablet, or other terminal.
The main memory device 1201 stores programs and applications such as a drone setting module 1211 and a management server setting module 1212, and each functional element of the management terminal 703 is realized by the processor 1203 executing these programs and applications.
The drone setting module 1211 performs various operations and settings such as spraying flight settings and initial settings for the drone 100.
The management server setting module 1212 performs various settings such as the initial settings of the management server 702 .
The auxiliary memory device 1202 stores various information such as drone setting information 1221 and management server setting information 1222.

FIG. 13 is an example of the farm field management information 1300.
The field management information 1300 stores various information related to the field on which the pesticide is to be sprayed, such as the field ID, the field name, the field position, the field perimeter coordinates, the field area, the cultivated crop, etc. The field management information 1300 is sometimes simply referred to as field information.
The field ID is identification information that uniquely identifies a field.
The field position 1311 indicates the position coordinates of the field, and has information on the latitude and longitude of the center of the field, for example.
For example, if the field is a square, the coordinates are the position coordinates of the four corners. The sample value GC007 indicates a link to information in which consecutive position coordinates are stored, separated by commas, for example.
The field area 1313 is the total area of the field corresponding to the field ID.
The cultivated crop 1314 stores information for identifying the crop cultivated in the field.

FIG. 14 is an example of device management information 1400.
The equipment management information 1400 stores information for managing the drone 100, and stores information such as the equipment ID, equipment name, model number, specifications, user, energy, and possible flight time.
The device ID is identification information that uniquely identifies the drone 100.
The user is information about the user currently using the drone 100, and the user ID of the user management information 1500 is stored.
Energy 1411 is information regarding the energy that can be carried by drone 100, and stores the energy ID of energy management information 1700.
The remaining flight time 1412 indicates the remaining flight time based on the energy that can be loaded onto the drone 100. For example, information such as the fact that a set of two batteries allows flight for 15 minutes is stored.

FIG. 15 is an example of user management information 1500.
User management information 1500 stores information about the user operating drone 100, including user ID, user display ID, name, email address, date of birth, gender, and other information.
The user ID is identification information that uniquely identifies a user.
The user display ID is user information displayed on the mobile terminal 701, etc., and is, for example, a nickname registered by the user.

FIG. 16 is an example of medicine management information 1600.
The drug management information 1600 stores information on the drug to be sprayed, such as the drug ID, drug name, product number, specifications, dilution rate, and amount to be sprayed.
The medicine ID is identification information that uniquely identifies a medicine.
The agent name 1602 indicates the name of a liquid, powder or fine particle product to be sprayed on a field, such as a pesticide, herbicide, liquid fertilizer, insecticide, or seed.

The specifications 1603 store information such as the method of using the pesticide, the dilution method, the target crop, and the spraying method, and the pesticide dilution and spraying process is carried out according to the contents described in the specifications 1603.
The dilution ratio 1604 stores the ratio at which the medicine is diluted, such as the ratio of medicine to water, or the amounts of medicine and water used for dilution.
The amount of the diluted agent to be sprayed is stored as the spray amount 1605. For example, it is shown that 10 L of the agent to be sprayed per 1 hectare.

FIG. 17 is an example of energy management information 1700.
Energy management information 1700 stores information regarding energy, such as batteries, required for drone 100 flight, and stores information such as energy ID, energy name, model number, type, specifications, etc.
The energy ID is identification information that uniquely identifies the energy.
The type indicates the type of energy, and for example, battery, gasoline, jet fuel, etc. are stored.

FIG. 18 is an example of flight route management information 1800.
Flight route management information 1800 stores information indicating the flight route of drone 100, and stores a route ID, a target ID, route coordinates, total route distance, etc.
The route ID is identification information that uniquely identifies a flight route.
The target ID is information that identifies the field for which the flight route is calculated, the movement route between fields, etc. For example, farm003 indicates that the target is a field, and route002 indicates that the target is a movement route outside the field.
The route coordinates 1811 are links to information indicating the route coordinates of a flight, and the route coordinates of a flight are expressed, for example, as a combination of a plurality of consecutive position coordinates. Possible position coordinates include a combination of latitude and longitude, or a combination of latitude, longitude, and altitude.
The total route distance 1812 indicates the total route distance if the entire flight path is flown from the start of the flight to the schedule.

FIG. 19 is an example of schedule management information 1900.
The schedule management information 1900 is information that specifies a schedule when a spraying flight is performed over multiple fields, and stores information such as the schedule ID, schedule name, date and time, start location, and schedule.
Schedule 1901 stores information specifying fields for which spraying flights are to be performed, travel routes between fields, etc. For example, in the example of sample values, the schedule includes flying over two fields specified by farm006 and farm005, flying along the travel route indicated by route001, flying over a field specified by farm003, passing through other events (e.g., lunch time) specified by other001, and then flying over a field specified by farm002.

The spraying-related information 1902 stores the total chemical spray amount, dilution amount, energy amount, etc. for the entire schedule that are calculated and output by the schedule management information output processing flow 3200 in Figure 32. Note that the spraying-related information 1902 may store the chemical spray amount, dilution amount, energy amount, etc. for each field that are calculated and output by the spraying-related information output processing flow 2200 in Figure 22.
In addition, the spraying-related information includes information such as the amount of pesticide sprayed, dilution amount, and energy amount required for a pesticide spraying flight.
The method of defining the schedule is just one example, and other schedule management methods may be used.

FIG. 20 shows an example of a screen display process flow 2000.
When the screen display module 1011 of the mobile terminal 701 receives a screen display instruction from the user, it acquires the map information 1200 from the storage device 1002 (step 2010).
The screen display module 1011 acquires field management information 1300 relating to the field that is the target of the spraying flight from the storage device 1002 (step 2020).
The screen display module 1011 retrieves flight path management information 1800 regarding the flight path of the spraying flight from the storage device 1002 (step 2030).
The display module 1011 acquires the drug and energy information required for the spray flight (step 2040).

The screen display module 1011 generates and displays the farm field information display screen 800 based on the acquired information (step 2050).
When the screen display module 1011 receives drone operation instructions from the user (Yes in step 2060), it displays the drone operation screen 900 (step 2070).
The map information 1200 and the farm field management information 1300 may be obtained from the storage device 1102 of the management server 702 via a network, instead of from the storage device 1002 of the mobile terminal 701 .

The flight path management information 1800 of the scattering flight is stored in the flight path management information 1800 of the storage device 1102 of the management server 702, which is information on the flight path calculated by the flight path management module 1115 of the management server 702. This information may be synchronized and stored in the storage device 1002 of the mobile terminal 701. The flight path may be calculated on the mobile terminal 701 side and stored in the storage device 1002 of the mobile terminal 701. The calculation of the flight path will be described in FIG. 21.
The drug and energy information required for the spraying flight is calculated and output by the spraying-related information management module 1114 of the management server 702, and the mobile terminal 701 acquires the drug and energy information via the network. Alternatively, the mobile terminal 701 may calculate the drug and energy information and display it on the mobile terminal 701. The calculation of the drug and energy information will be described with reference to FIG. 22.

FIG. 21 is an example of a flight path output process flow 2100.
This may be executed by the management server 702 or the mobile terminal 701. When the management server 702 executes this, first, the flight path management module 1115 of the management server 702 acquires the field management information 1300 from the storage device 1102 (step 2110). Specifically, the flight path management module 1115 acquires information on the field perimeter coordinates 1312 of the field that is the target of the spraying flight from the field management information 1300.

The flight path management module 1115 calculates the shape of the field from the surrounding coordinate information, and calculates the path of the spraying flight based on the calculated shape of the field (step 2120).
For example, as shown in flight path 931 of a spraying flight over a field 930 on the drone operation screen 900 in Figure 9, a route is calculated for the drone to travel back and forth, first circling the periphery of the field and then filling in the middle.
The flight path management module 1115 outputs information about the calculated flight path and stores it in the flight path management information 1800 (step 2130). For example, the flight path management information 1800 includes route coordinates 1811, which store multiple position coordinates consisting of combinations of latitude, longitude, and altitude. The spraying flight of the drone 100 is controlled according to the flight path consisting of the combination of latitude, longitude, and altitude. The flight path management module 1115 may also store a total route distance 1812 and the like in addition to the route coordinates.

In addition, when the flight path management module 1115 of the management server 702 receives a request to obtain a flight path from the mobile terminal 701 or the management terminal 703, it transmits flight path management information 1800 regarding the calculated flight path to the mobile terminal 701 or the management terminal 703.
In addition, when the mobile terminal 701 performs the flight path output processing flow 2100, a similar process is executed by a flight path management module (not shown) of the mobile terminal 701, and the flight path management information 1800 is stored in the memory device 1002 of the mobile terminal 701.

FIG. 22 shows an example of a process flow 2200 for outputting scattering-related information.
This process may be executed by the management server 702 or the mobile terminal 701. When the management server 702 executes this process, the spraying-related information management module 1114 of the management server 702 first acquires the field management information 1300 from the storage device 1102 (step 2210). For example, the spraying-related information management module 1114 acquires information on the area 1313 of the field that is the target of the spraying flight from the field management information 1300.
The spray-related information management module 1114 acquires the chemical management information 1600 of the chemical to be sprayed in the field from the storage device 1102 (step 2220). For example, the chemical name 1601, product number 1602, specifications 1603, dilution rate 1604, spray amount 1605, etc. of the chemical management information 1600 are acquired.

The spraying-related information management module 1114 calculates the amount of pesticide to be actually sprayed during the spraying flight based on the acquired field information (step 2230).
For example, the amount of diluted pesticide required for spraying is calculated from the field area 1313 obtained from the field management information 1300 and the amount of diluted pesticide (sprayed pesticide) per unit area 1605 obtained from the pesticide management information 1600.
For example, the amount of diluted pesticide sprayed may be calculated based on the amount of diluted pesticide sprayed per unit time by drone 100 and the flight time of the spraying flight.
In addition, the amount of diluted pesticide sprayed may be calculated based on the amount of diluted pesticide sprayed per unit distance of the drone 100 and the total route distance 1812 of the spraying flight.

Next, the spray-related information management module 1114 calculates the dilution amount of the drug to be sprayed (step 2240).
The dilution amount is the amount by which the drug is diluted, for example, the amount of water mixed with the drug to dilute the amount of drug corresponding to the amount of drug sprayed calculated in step 2230. Alternatively, it may be a dilution rate indicating the ratio of drug to water, or the total amount of the drug after mixing with water (in this case, it is better to also display the dilution rate).
In addition, the spraying-related information management module 1114 can generate information regarding the dilution amount based on at least one of the crop variety present in the selected field, the corresponding type of pesticide, and the spraying time of the corresponding pesticide.
The crop variety is stored in the cultivated crop 1314 of the farm field management information 1300 , and the type of pesticide required for this cultivated crop 1314 and the timing of application are stored in the specifications 1603 of the pesticide management information 1600 .

Next, the spraying-related information management module 1114 calculates the amount of energy required for the spraying flight (step 2250).
For example, the spraying-related information management module 1114 acquires device management information 1400 of the drone 100 performing a spraying flight, and acquires information 1411 of the energy to be used and the flight time available with this energy 1412. The energy information 1411 is associated with energy management information 1700, and for example, if the corresponding energy of the drone 100 is a battery, information regarding this battery is stored in the energy management information 1700.

For example, if the energy source is a battery, the dispersion-related information management module 1114 calculates the number of batteries required to completely spray the diluted drug dosage.
In this case, the battery capacity and number of batteries required for spraying are calculated based on the amount of diluted drug sprayed for the spraying flight calculated in step 2230 and the value of the battery capacity required per amount of drug sprayed stored in device management information 1400. For example, the battery capacity is equivalent to 2.7 batteries, and the number of batteries is rounded up to 3 batteries as it takes an integer value.

In addition, the battery capacity and number of batteries required for spraying may be calculated based on the value of the battery capacity required per weight and the total weight of the drone 100 carrying the diluted pesticide to be sprayed.
In addition, the battery capacity and number of batteries required for spraying may be calculated based on the value of the battery capacity required per flight hour and the flight time of the spraying flight.
In addition, the battery capacity and number of batteries required for spraying may be calculated based on the value of the battery capacity required per flight distance and the flight distance of the spraying flight.
Even if the energy source of the drone 100 is not a battery, such as jet fuel, the battery capacity and number of batteries required for spraying can be calculated based on the amount of pesticide sprayed, weight, flight time, and flight distance, and the amount of pesticide sprayed, weight, flight time, and flight distance of the spraying flight.

The spraying-related information management module 1114 outputs the calculated amount of chemical sprayed, the dilution amount, and the amount of energy as spraying-related information and transmits it to the mobile terminal 701 or the management terminal 703 (step 2260). Alternatively, this spraying-related information is stored in the storage device 1102 of the management server 702 together with field information corresponding to the field management information 1300, for example. Alternatively, it is recorded as spraying-related information 1902 in the schedule management information 1900.

FIG. 23 is a display example of the spraying information display area 820 on the farm field information display screen 800.
The screen display module 1011 of the mobile terminal 701 obtains spray-related information such as the amount of pesticide to be sprayed, dilution amount, and energy amount for the field specified by the user from the management server 702 and displays it as the spray information display area 820.
23A is a display example 2300 in which the dispersion information display area 820 is displayed in text.
The name of the drug to be sprayed in the field during the spraying flight is displayed in the drug name 2301, which is obtained from the drug management information 1600. Note that the drug may not only be determined in advance, but may also be selected or input by the user in the field or in advance. In this case, the package of the drug to be sprayed may be photographed by the camera unit 1006 of the mobile terminal 701, and the drug name may be obtained by analyzing the photographed image.

The spray amount 2302, dilution amount 2303, and energy amount 2304 display the amount of pesticide sprayed, dilution amount, and energy amount output by the spray-related information output processing flow 2200 in Figure 22. In the case of a battery, the energy amount 2304 may display, for example, 2.7 units of the battery capacity required for the spray flight, or may display the integer value rounded up to 3.
23B is a display example 2350 in which a portion of the dispersion information display area 820 is displayed graphically.
The amount of dilution 2353 and the amount of energy 2354 are displayed graphically.

Figure 24 is an example of the display of spray flight progress information 912 on the drone operation screen 900.
The spraying flight progress information 912 displays progress information of the current spraying flight, such as the progress of the flight route of the spraying flight, the remaining amount of sprayed chemical, the remaining battery charge, and the like.
23A is a display example 2300 showing the maximum payload and the current progress.
The progress of the spraying flight is displayed in the status bar as route progress 2410, remaining amount of drug 2420, and remaining battery amount 2430.

In the route progress 2410, the total value of the route required for the spraying flight, obtained from the route total distance 1812 of the flight route management information 1800, is displayed in 2411. Of these, the current route progress 2412, which indicates the progress of the pesticide spraying, is displayed. In the example of the drone operation screen 900, the flight route 931 of the spraying flight over the field 930 is displayed, and the color of the line of the sprayed area changes depending on the progress of the spraying flight. These displays allow the user to simultaneously visually grasp where the drone 100 is currently flying on the route of the spraying flight and how much the route progress 2410 is in relation to the total route distance, making it easier to understand the management of pesticide spraying.

The remaining amount of drug 2420 shows the current remaining amount of drug 2422, which indicates the progress of drug spraying, out of the amount of diluted drug 2421 that can be loaded onto the drone 100 in one go.
In addition, 2421 may be the amount of pesticide sprayed required for one spraying flight output by the spraying-related information output processing flow 2200 in Figure 22.
Furthermore, if it is necessary to spray more pesticide than the maximum load capacity of the drone 100, the total amount of pesticide required for spraying may be set to 2421. In this case, it is necessary to load additional pesticide on the way.

The remaining battery capacity 2430 is a current remaining battery capacity 2432 out of the maximum capacity 2431 of the battery that can be mounted on the drone 100, and is displayed in a status bar.
In addition, 2431 may be the amount of energy required for one spraying flight output by the spraying-related information output processing flow 2200 in Figure 22.
Furthermore, if more batteries than the maximum load capacity of the drone 100 are required, the total battery capacity (number of batteries) required for spraying may be set to 2431. In this case, it is necessary to replace the batteries midway.

(B) is an example display 2350 showing the maximum payload, the amount required for one spraying flight, and the current progress.
The progress of the spraying flight is displayed in the status bar as route progress 2460, remaining drug amount 2470, and remaining battery amount 2480.
The route progress 2460 displays a maximum possible flight distance 2461 in one attempt and a total value 2462 of the route required for the spraying flight obtained from the total route distance 1812 of the flight route management information 1800. Of these, a current route progress 2463 indicating the progress of the drug spraying is displayed.

The drug progress 2470 displays the maximum payload 2471 of diluted drug that can be loaded onto the drone 100 at one time, and the drug spray amount 2472 required for one spraying flight output by the spraying-related information output process flow 2200 in Fig. 22. Of these, the current remaining amount of drug 2473, which indicates the progress of the drug spraying, is displayed.
The remaining battery capacity 2480 displays the maximum capacity 2481 of the battery that can be mounted on the drone 100 and the amount of energy (battery capacity) 2482 required for one spraying flight output by the spraying-related information output processing flow 2200 in Figure 22. Of these, the current remaining battery capacity 2483, which indicates the progress of the pesticide spraying, is displayed.

FIG. 25 is an example of a schematic diagram showing the relationship between the amount of sprayed pesticide payload and the available flight time.
For example, the drone 100 can carry up to 10 L of the chemical A, and the flight time when the maximum load is 15 minutes. On the other hand, if the amount of chemical to be sprayed is reduced, the weight becomes lighter, the battery consumption is reduced, and the flight time is extended. When the chemical is not loaded, the flight time is 20 minutes.
In this case, there is no linear relationship between battery consumption and the amount of drug carried, and a reduction in the load and weight tends to result in a longer flight time.
Furthermore, since the specific gravity differs for each drug, the relational equation differs for each drug.

FIG. 26 is an example of a schematic diagram showing the relationship between the amount of sprayed pesticide loaded and the amount of battery power lost.
25 into the battery consumption rate, in the case of drug A, when the maximum load of 15 L is applied, one battery (one set) is consumed in 15 minutes, resulting in a battery consumption of 1/15 battery per minute = approximately 6.7% per minute. On the other hand, when nothing is loaded, one battery is consumed in 20 minutes, resulting in a battery consumption of 1/20 battery per minute = 5% per minute.

In reality, the aggressor will continue to spray during the flight, and the amount of aggressor will gradually decrease over time. In this case, the amount of battery power consumed can be calculated by integrating the amount of battery power consumed at each time.
Similarly, the flight time can be calculated by performing calculations using the flight time corresponding to the amount of drug at each time.

In the spraying-related information output processing flow 2200 of Figure 22, when the spraying-related information management module 1114 of the management server 702 calculates 2250 the battery capacity required for spraying, it can calculate the battery capacity required for spraying using the amount of drug sprayed required for spraying found in step 2230 and the relationship between the amount of drug sprayed and the amount of battery depletion in Figure 26. In this case, by further using the relational equation for each drug, it is possible to calculate the battery capacity more accurately.
In this way, by calculating the battery capacity taking into account the reduction in the amount of sprayed pesticide loaded onto the drone 100, it is possible to determine the battery usage more accurately, and to more accurately grasp the timing and frequency of battery replacement.
It should be noted that similar calculations can be performed for other types of energy such as fuels other than batteries.

The configuration of Example 1 above can also be applied to a spraying flight in which multiple fields are selected.
FIG. 27 is an example of a display screen 2700 showing a pesticide spray schedule for multiple fields.
When the schedule display button 870 is selected from the field information display screen of FIG. 8, the screen display module 1011 displays a spraying schedule bar 2710 in an animation that appears to slide in from the right edge of the screen.
In the spraying schedule bar 2710, fields 802, 803, and 804 are selected as spraying targets, and spraying schedules 2730, 2740, and 2750 for these fields are displayed.
Additionally, above the spray schedule bar 2710, a total information display area 2720 is displayed as the entire spray schedule for the day.

The schedule management module 1116 of the management server 702 calculates a pesticide spraying schedule for the selected fields.
For each field 802, 803, 804, flight path management information 1800 and spraying-related information calculated by the flight path management module 1115 and the spraying-related information management module 1114 are obtained, and the amount of pesticide and energy required for the spraying flight is displayed in the spraying schedules 2730, 2740, 2750.

An example of the display screen 2700 for the pesticide spray schedule is the display when field 802 is selected. The screen display module 1011 changes the color of the field 802 to indicate that it has been selected, and displays information about the field 802 in the field information display area 810. The screen display module 1011 also highlights the spray schedule 2730 corresponding to the field 802 in the spray schedule bar 2710 by changing its color.

The schedule management module 1116 also acquires area information for each of the selected multiple fields from the field management information 1300, and the spraying-related information management module 1114 calculates the required amount of chemical spray and the amount of energy for the total spraying area obtained by adding up the area information. The calculated values are displayed in the total information display area 2720 as the overall spraying schedule for the day.
As in Example 1, the amount of pesticide sprayed and the amount of energy required for the entire spraying schedule for the day may be calculated based on the total flight distance, total flight time, etc.
In addition, rather than first totaling the area of the fields, etc. and then calculating the required amount of pesticide spraying and amount of energy, the total amount of pesticide spraying and amount of energy may be calculated by adding up the amounts of pesticide spraying and energy for each individual field calculated in the spraying schedule for each field.

In addition, the spraying-related information management module 1114 of the management server 702 calculates and outputs the total amount of pesticide sprayed, dilution amount, and energy amount based on the total of the field management information 1300 for all selected fields.
Based on the output information, the screen display module 1011 displays the total amount of drug sprayed, dilution amount, and energy amount in the total information display area 2720.

As a GUI (graphical user interface) output to the display unit, for example, the screen display module 1011 accepts input of multiple fields and the work days for each field, and the spraying related information management module 1114 calculates the number of batteries, amount of chemicals, and amount of water required for each field work based on the field area of each field, and displays the total amount of resources (number of batteries, amount of chemicals, amount of water) required for each day. It is also possible to notify these required resources before the work day, so that the required resources can be known in advance.
In addition, the screen display module 1011 can accept input of the work order for each field, calculate the travel time between each field based on the distance between each field calculated from the field position 1311 of each field, and display the travel time between each field.
The system also has a function for inputting the completion of work for each field to be worked on, and the work completion information can be displayed on the work schedule screen.

In addition, the drawing process of the pesticide spraying schedule in Example 2, and the drawing process of information on each field and the required pesticide spray amount and energy amount may be performed on the management server 702 side or on the mobile terminal 701 side.
In addition, the calculation of the amount of pesticide sprayed and the amount of energy for each field and the total amount of these fields may be performed on the management server 702 side or on the mobile terminal 701 side.

The present embodiment relates to a drone pesticide spray flight control method and information processing device, and in particular to a method for automatically generating a schedule for a pesticide spray flight by a schedule management information output process.
During pest control seasons when pesticides and other chemicals are sprayed to prevent and eliminate agricultural pests and diseases, it is necessary to spray chemicals over a large number of fields over several days, making it necessary to create an efficient work schedule.

However, because the fields are scattered and the size and distance between each field varies, it was difficult to create a spraying schedule that would be efficient overall.In addition, there are time constraints such as the prohibition of drone flights at night and the need to avoid lunch time, as well as functional constraints such as the flight time that can be flown with one set of batteries and the amount of spraying pesticide that can be sprayed in one spraying flight, making it difficult to create an optimal schedule while taking these constraints into account.
Therefore, in this embodiment, a mechanism is provided that breaks down the conditions to be considered for a spraying flight, generates a spraying flight schedule by performing a route search process based on these conditions, and makes it easy to manage pesticide spraying schedules.

The present application includes multiple means for solving the above-mentioned problems, and one example is an information processing device that controls the spraying flight of a drone that sprays pesticides, comprising a memory unit that stores multiple pieces of field information, an output unit that outputs multiple pieces of field information, an input unit that accepts selection from multiple fields, and a control unit that controls the spraying flight of the drone that sprays pesticides, wherein the control unit calculates, for the multiple fields selected via the input unit, the spraying flight time for performing a spraying flight to each field and the travel time for traveling between each field, generates a pesticide spraying schedule based on the calculated spraying flight time, the travel time, and constraint conditions, and the output unit outputs the generated pesticide spraying schedule.

According to the present invention, the conditions to be considered for a spraying flight are broken down and a route search process is performed based on these conditions to generate a schedule for the spraying flight, thereby facilitating management of the pesticide spraying schedule.

FIG. 28 is an example of a display screen 2800 of a drug dispersion schedule for multiple days.
In Figure 27, a one-day dispensing schedule bar 2710 is displayed in an animation that slides in from the right edge of the screen, but if this dispensing schedule bar 2710 is swiped further to the left, a drug dispensing schedule bar 2810 for the most recent several days is displayed.
The dates of the most recent multiple days are displayed in a date area 2820 at the top of the multiple-day drug dispensing schedule bar 2810. By further swiping the multiple-day drug dispensing schedule bar 2810 to the left or right, the drug dispensing schedule for the date before or after the currently displayed date can be displayed.

For example, a pesticide spraying schedule 2830 for each field is displayed on the multi-day pesticide spraying schedule bar 2810. In addition, a movement schedule 2841 showing the time for moving between fields by truck or the like, and a movement flight schedule 2842 showing the movement of the drone 100 while flying are displayed.
Since the size of the display area of the mobile terminal 701 etc. is limited, it may not be possible to display all of the schedule. The continuation display 2843 indicates that other schedule information exists outside the area displayed on the screen for the same day.

The pesticide spraying schedule 2830 for each field displays the pesticide application amount, dilution amount, and energy amount as spray-related information required for that spraying flight.
Additionally, the spray-related information 2821 for the entire schedule for the day displays the amount of pesticide sprayed, dilution amount, and energy amount required for the entire schedule for the day.
The schedule display is just an example, and other schedule displays may be used.

Figures 29 and 30 are figures that explain the change in display when the spray schedule is changed from the multi-day drug spray schedule bar 2810.
FIG. 29 is an example of a screen (changing) 2900 for changing a drug dispersion schedule.
Assume that spraying flight 2850 for field D2 in FIG. 28 is moved to vacant area 2910 in the schedule in FIG.

The screen display module 1011 accepts a schedule change instruction from a user. For example, if the mobile terminal 701 is a tablet or smartphone, the screen display module 1011 recognizes the change instruction by detecting a long press on the drug dispersion schedule 2950 to be moved. Also, if the mobile terminal 701 is a notebook PC or desktop PC, the screen display module 1011 recognizes the change instruction by detecting that the drug dispersion schedule 2950 to be moved has been dragged with a mouse or the like.

FIG. 30 is an example of a screen (after change) 3000 for changing the drug dispersion schedule.
When the schedule is changed, the schedule is recalculated and the schedule management information 1900 is updated.
For example, the time of the drug dispensing schedule 3050 to be moved was 15 minutes longer than the free space 2910 in the schedule, but it was moved to the free space 2910, and in return, the start time of the drug dispensing schedule 3010 that follows it has been delayed by 15 minutes.

In addition, since the amount of pesticide to be sprayed, the dilution amount, and the amount of energy required for the entire schedule for the day are also changed, the spray-related information 3021 and 3022 for the entire schedule for the day are recalculated and updated.
Moreover, any unnecessary travel flight schedules or travel schedules are deleted as shown at 3030.

FIG. 31 shows an example of a schedule information display process flow 3100.
The schedule management module 1116 of the management server 702 receives the selection of the field to be sprayed from the mobile terminal 701 or the management terminal 703 (step 3110).
The schedule management module 1116 receives a selection of a scheduling mode that sets priorities when generating a flight schedule from the mobile terminal 701 or the management terminal 703 (step 3120).

Scheduling modes include, for example, a "time-saving mode" which prioritizes shortening the time it takes to complete a task, a "battery-saving mode" which prioritizes reducing the number of batteries used, and a "task reduction mode" which prioritizes reducing the number of tasks such as refilling medication and replacing batteries.
For example, after the screen display module 1011 of the mobile terminal 701 accepts the selection of multiple fields, it displays a screen for selecting "time-saving mode,""battery-savingmode," or "reduced work frequency mode," and accepts the user's selection of a mode by tapping the screen.

The schedule management module 1116 executes the schedule management information output process shown in FIG. 32 based on the input information and the information stored in the storage device, and outputs the schedule management information 1900 (step 3130).
The schedule management module 1116 outputs the drug dispensing schedule to the output device 1105 based on the schedule management information 1900 (step 3140), or outputs the drug dispensing schedule to the mobile terminal 701 via the network to display a schedule display screen on the mobile terminal 701.

The schedule management module 1116 receives a schedule change instruction from the mobile terminal 701 or the management terminal 703 (step 3150).
When an instruction to change the schedule is received, the schedule management module 1116 executes the schedule management information output process again and recalculates the schedule.
The schedule management module 1116 constantly or periodically checks whether or not there is an instruction to change the schedule until an instruction to end the display is received (step 3160).

All or part of the steps in the schedule information display process flow can also be performed by the mobile terminal 701. For example, only the schedule management information output process 3130 can be performed by the management server 702, and the other processes can be performed by the mobile terminal 701.
When the mobile terminal 701 is used, the screen display module 1011 outputs and displays the information on the screen, and the schedule management module 1013 acquires and adjusts the schedule management information 1900 .

FIG. 32 shows an example of a schedule management information output process flow 3200.
The schedule management module 1116 of the management server 702 obtains field information such as the field area 1313 and the field position 1311 from the field management information 1300 in response to the information on the field to be sprayed received from the mobile terminal 701 or the management terminal 703 (step 3210).
The schedule management module 1116 acquires some of the constraint conditions from the mobile terminal 701 and the management terminal 703. For example, there are time constraints such as the time of a break that the user plans to take, the start and end times that the user expects in advance, the time for preparation work such as battery replacement and drug refilling, and other predetermined schedule and location constraints, such as the requirement to be at a specified location at 2 p.m.

The management server 702 also acquires constraint conditions that are stored in advance on the management server 702 side. For example, when a time during which the drone 100 is prohibited from flying is stipulated by local ordinance, such as at night, a constraint condition is to fit the schedule outside of the prohibited time.
The time periods other than the times when these spraying flights cannot be performed are the available work hours during which actual spraying flights can be performed, and staying within this available work hours is one of the constraints.
The schedule management module 1116 executes the process of calculating the spraying flight time for each field shown in FIG. 33 (step 3230).
The schedule management module 1116 executes the process of calculating the travel time between each of the fields shown in FIG. 34 (step 3240).

The schedule management module 1116 modifies the constraints based on the selected mode (step 3250).
For example, in "time-saving mode," the drone loads as much medicine as possible and continues flying continuously while reducing the number of replenishments. The constraints are changed to reduce the time lost during battery replacement and replenishment by performing battery replacement and replenishment as simultaneously as possible.
Also, for example, in the "battery saving mode," by replenishing the drug as frequently as possible, the drone can continue flying with a small amount of drug, which reduces the payload weight of the drone 100 and reduces the amount of battery power consumed, as shown in Figures 25 and 26, improving battery life.
In the "operation frequency reduction mode", the constraints are changed so that battery replacement and drug replenishment are performed simultaneously as much as possible, thereby reducing the amount of work lost during replacement and replenishment.

The schedule management module 1116 uses the calculated spray flight time, travel time, and constraint conditions as input, performs a route search process on them, and outputs a drug spray schedule (step 3260).
The route search process is performed, for example, by the flight route management module 1115 rearranging the input spraying flight times and travel times and executing a route search algorithm so as to satisfy the constraints. An example of the route search algorithm is an algorithm for solving the traveling salesman problem, and by solving the traveling salesman problem for the spraying flight times and travel times, a route that minimizes the time required to visit all fields can be calculated.

Other algorithms for calculating the shortest travel route between any two bases include Dijkstra's algorithm and A* search algorithm. The route search algorithm is not limited to these, and other suitable algorithms can be selected.
It is also possible to generate a route search model by AI using machine learning or deep learning, and to generate a schedule by inputting conditions into the route search model. This will be described later with reference to Figs. 35 and 36.

An example of a constraint condition that must be satisfied in the route search process is available work time, and as mentioned above, a pesticide spraying schedule is generated that allocates spraying flight time and travel time so that they fall within available work time excluding rest times and no-fly times.
In addition, a pesticide spraying schedule is generated to satisfy the constraint conditions changed in step 3250. For example, in the "time-saving mode", a schedule is generated to load as much pesticide as possible, reduce the number of replenishments, and continue continuous flights. For example, in the "battery-saving mode", a pesticide spraying schedule is generated to replenish the pesticide as frequently as possible, so that the flight can be continued with a small amount of pesticide. For example, in the "work frequency reduction mode", a pesticide spraying schedule is generated to replace the battery and replenish the pesticide simultaneously as much as possible, minimizing work loss during replacement and replenishment.

Another example of a constraint is the available flight time when all the batteries held by the user are used, and a pesticide spraying schedule is generated that allocates spraying flight time and travel time so that they fit within this available flight time.
Another example of a constraint is the amount of pesticide that the drone 100 can carry at one time, and a pesticide spraying schedule is generated that arranges the spraying flight time and travel time so that the amount of pesticide that the drone 100 can carry at one time is not exceeded.
Another example of a constraint is the number of batteries used, and a drug dispersion schedule is generated to minimize the number of batteries used.

Another example of a constraint is the time required to complete a task, and a pesticide dispersion schedule is generated to minimize the time required to complete the task.
Other examples of constraints may include at least one of the following, or a combination of: available work time, available flight time using the battery, amount of medicine that the drone can carry at one time, number of batteries used, and time required to complete the work.
In addition, the order of fields to be sprayed can be specified in advance as a constraint.
As described above, there are multiple constraints that need to be satisfied, but it is not necessary to satisfy all of them. For example, the schedule management module 1116 changes the set of constraints that need to be satisfied based on the mode selected by the user, and calculates schedule information by a route search process so as to satisfy the changed constraints.

Next, the schedule management module 1116 calculates the total drug dispensing amount, dilution amount, and energy amount for the entire schedule (step 3270), and writes and outputs the calculated schedule information together with the schedule management information 1900 (step 3280). Alternatively, the schedule management module 1116 outputs the calculated schedule information to the mobile terminal 701 or the management terminal 703 via the network.

FIG. 33 shows an example of a dispersion flight time calculation process flow 3300.
The schedule management information 1900 of the management server 702 acquires field information such as the field area 1313 and the field perimeter coordinates 1312 from the field management information 1300 (step 3310).
The schedule management module 1116 acquires the flight paths for each field calculated by the flight path management module 1115 based on the acquired field information (step 3320).
The schedule management module 1116 calculates the spraying flight time for each field by dividing the total route distance of the flight path by the flight speed (step 3330) and outputs the calculated flight time (step 3340).

Although the spraying flight time was obtained from the total route distance and flight speed, the spraying flight time may also be calculated from the field area and the sprayable area per unit time.
In addition, if the spraying flight speed changes depending on the weight of the pesticide being loaded, i.e., if the flight speed decreases when the total weight is heavy and increases when the total weight is light, the spraying flight time can be calculated using the flight speed calculated based on the relationship of the flight speed to the weight of the pesticide being sprayed (or the total weight of the drone 100).

In this case, the schedule management module 1116 obtains the name of the pesticide 1601 and the dilution rate 1604 from the pesticide management information 1600 to be sprayed in each field, and calculates the weight of the pesticide to be sprayed.
Alternatively, the weight of the sprayed pesticide may be calculated by calculating the dilution amount of the pesticide to be sprayed. The dilution amount can be calculated based on at least one of the variety of the crop present in the field, the type of the corresponding pesticide, and the spraying time of the corresponding pesticide.
The crop variety is stored in the cultivated crop 1314 of the farm field management information 1300 , and the type of pesticide required for this cultivated crop 1314 and the timing of application are stored in the specifications 1603 of the pesticide management information 1600 .

The flight speed can also be changed depending on the dilution rate of the drug. For drugs for which the dilution rate can be changed, for example, a flight in which a drug with a concentration of 5% is sprayed at a speed of 100 m/min may be replaced with a flight in which a drug with a concentration of 10% is sprayed at a speed of 200 m/min. That is, for a sprayed drug with a higher concentration, the spray density is reduced by spraying at a faster speed, and the amount of sprayed drug per unit area is approximately the same.
In this case, the spray flight time can be determined using the flight speed calculated based on the relationship between the drug name, drug dilution rate, and flight speed.

FIG. 34 shows an example of a travel time calculation process flow 3400.
The schedule management module 1116 acquires the field position 1311 from the field management information 1300 (step 3410).
The schedule management module 1116 calculates the distance between each of the fields based on the position coordinates of the acquired field position 1311 (step 3420). Note that the field position 1311 is, for example, information on the latitude and longitude of the center of the field, but the distance between each of the fields may be calculated using information on the field perimeter coordinates 1312.

The schedule management module 1116 calculates the travel time between each of the fields from the calculated distances between the fields and the travel speed (step 3430), and outputs the time (step 3440).
The travel speed may be set to a predetermined value and the travel time may be roughly estimated from the distance between each field, but a more accurate travel time may be calculated using a travel speed that is differentiated for each distance.
Possible travel speeds include, for example, flight travel, in which the drone 100 moves while flying, truck travel, in which the drone 100 is temporarily retrieved and then moved by truck, or foot travel, in which the drone 100 is moved on foot.

An appropriate means of transportation is selected depending on the distance between the fields. For example, if the drone 100 can only fly continuously for about 15 minutes, taking into account the spraying time, flying to a location that is more than 5 minutes away is a waste of battery power and is not recommended.
In addition, walking is limited to about 15 minutes, and for travel beyond that, transportation by truck is more efficient.
Possible means of transportation are determined based on such predetermined conditions. For example, flying is determined when the distance between the fields is 0 m or more and less than 300 m, walking is determined when the distance is 300 m or more and less than 1 km, and truck transportation is determined when the distance is 1 km or more. Travel time is calculated based on the distance between the fields and the travel speed of each means of transportation.

The spraying flight time output in Figure 33 and the travel time calculated in Figure 34 are used as input values for the route search process in Figure 32, and a spraying schedule for the spraying pesticide is calculated taking into account the constraints.
In the example of Figure 32, a method of calculating a schedule using a route search algorithm has been described. However, instead of such a route search algorithm, it is also possible to generate a route search model using AI such as machine learning or deep learning, and use this model to calculate a schedule.
For example, the schedule management module 1116 can use field information for a number of selected fields, the spraying flight times for each selected field, the travel time for traveling between each field, constraints, and a pesticide spraying schedule as training data, and use machine learning to generate a route search model that takes the field information, spraying flight times, travel times, and constraints as input and outputs a pesticide spraying schedule, accepts input of the field information, spraying flight times, travel times, and constraints, and uses the route search model to output a pesticide spraying schedule estimated from the input information.

FIG. 35 is an example of a process flow 3500 for generating a route search model using AI.
For example, using the field information, constraint conditions, spraying flight time, travel time, and schedule information stored in the field management information 1300 as training data, a route search model is generated in which the inputs are the field information, constraint conditions, spraying flight time, and travel time, and the output is schedule information.
Specifically, the schedule management module 1116 acquires the field area or field perimeter coordinates, and field position, which are field information stored in the field management information 1300, for each field selected as input information (step 3510).
The schedule management module 1116 acquires the above-mentioned constraint conditions as input information (step 3520).

The schedule management module 1116 obtains the calculated spraying flight time for each field as input information (step 3530).
The schedule management module 1116 acquires the travel time between each of the fields calculated as input information (step 3540).
The schedule management module 1116 obtains schedule information for each field selected as each input information (step 3550).
The schedule management module 1116 generates a route search model that takes as input field information, constraint conditions, spraying flight time, and travel time, and outputs schedule information (step 3560).

FIG. 36 shows an example of a schedule information output process flow 3600 by AI.
The schedule management module 1116 accepts input of field information (step 3610), accepts input of constraint conditions (step 3620), accepts input of the calculated spraying flight time for each field (step 3630), and accepts input of the calculated travel time between each field (step 3640).
The schedule management module 1116 uses the route search model generated in accordance with FIG. 37 to output schedule information calculated from the various types of input information received (step 3650).

The schedule management module 1116 appropriately accepts the user's evaluation of the output schedule information (step 3660). For example, the evaluation may be an evaluation of whether the output schedule is "good" or "bad," and the system may be such that the user inputs the evaluation each time a medicine is actually sprayed according to the schedule.
The schedule management module 1116 improves the accuracy of the route search model by using the input information corresponding to the schedule evaluated as "good" as teacher data, or by using a part of the input information corresponding to the schedule evaluated as "good" as highly rated teacher data and a part of the input information corresponding to the schedule evaluated as "bad" as poorly rated teacher data, thereby improving the accuracy of the route search model.

Although the teacher data used were field information, constraint conditions, spraying flight time, travel time, and schedule information, the route search model may use only some of these as teacher data rather than all of them.
Although the field area or the field perimeter coordinates, and the field position are used as the field information, it is not necessary to use all of these, but only a part of them may be used, or other information stored in the field management information 1300 may be used.
As the constraint conditions, the various constraint conditions described above can be used as training data, but not all of them, and some of them may be used.

The present embodiment relates to a method and an information processing device for controlling a drone's pesticide spraying flight, and in particular, to notifying a drone of preparation information for a pesticide spraying flight.
During pest control seasons when agricultural pesticides and other chemicals are sprayed to prevent and eliminate agricultural pests and diseases, the chemicals must be diluted for each field according to a work schedule, and a spraying flight must be carried out to apply the diluted chemicals.
Some of the chemicals to be sprayed may settle over time, so it is preferable to dilute them by mixing them with water just before spraying (a few minutes before). In this case, when spraying multiple fields in sequence, it is desirable to dilute the chemical to be sprayed in the next field during spraying in order to shorten the work time.

However, in conventional pesticide spraying using drones, the user had to directly operate the drone using an operating terminal. This required the user to concentrate on operating the drone, and they could not perform other tasks while operating the drone. As a result, the next pesticide spraying schedule was not taken into consideration while operating a drone spraying flight, and there was no need to display the next pesticide spraying schedule.

On the other hand, one feature of this embodiment is that pesticide spraying by the drone 100 is basically performed automatically in accordance with the flight path 931 of the spraying flight generated by the flight path management module 1115 of the management server 702 and the pesticide spraying schedule generated by the schedule management module 1116.
Therefore, except in an emergency or when the user wishes to specifically change the altitude of the drone 100, the user does not need to operate the drone 100, and can even prepare pesticides for the next spraying flight while spraying pesticide.
Therefore, in this embodiment, a mechanism is provided for displaying information about the next spraying flight in part of the operation screen for controlling the drone spraying flight.

The present application includes multiple means for solving the above-mentioned problems, and one example is an information processing terminal that controls the spraying flights of a drone that sprays pesticides, the information processing terminal comprising: a memory unit that stores a pesticide spraying schedule for performing multiple spraying flights on multiple fields; a display unit that displays an operation screen for operating the spraying flights of the drone; and a control unit that controls the spraying flights of the drone, the display unit displaying the operation screen related to a current spraying flight based on the pesticide spraying schedule stored in the memory unit, and displaying information regarding the next spraying flight in a portion of the operation screen related to the current spraying flight.

According to the present invention, a mechanism is provided for displaying information about the next spraying flight on a portion of the operation screen for operating a drone spraying flight. For example, by displaying the pesticide to be used on the next spraying flight and its dilution amount or battery charge, the user can efficiently prepare for the next spraying flight, such as by diluting the pesticide.

FIG. 9 is an example of a drone operation screen 900 displayed on the mobile terminal 701.
In the example of the drone operation screen 900, a field 930 to be sprayed with a pesticide is displayed on a map, along with a flight path 931 of the spraying flight over the field 930. The drone 100 flies in sequence through the specified flight coordinates in accordance with flight path management information 1800 stored in the mobile terminal 701 or the management server 702.
In addition, when an operation that requires operation of the drone 100, such as the altitude change buttons 923, 924 or the emergency stop button 925, is received, the drone operation module 1012 can transmit information such as commands corresponding to these operations to the drone 100, thereby operating the drone 100.

The next spraying schedule display button 940 is a button (operation display) for displaying the schedule of the spraying flight next to the currently executed spraying flight. When this button is pressed, information about the next spraying flight obtained from the schedule management information 1900 is displayed.
Also, as described below, when the time until the next scheduled spraying falls within a predetermined time, information regarding the next spraying flight is displayed.

FIG. 37 is an example of a display screen 3700 that displays information regarding an upcoming spray flight.
The screen display module 1011 displays an information display area 3710 regarding the next spraying flight in a portion of the operation screen related to the current spraying flight, for example, in the lower right corner of the screen.
When the right-facing triangle button 3715 is selected, the screen display module 1011 displays information about the next dispersal flight, and when the left-facing triangle button is selected, it displays information about the previous dispersal flight.
The information display area 3710 regarding the next spraying flight displays information obtained from the field management information 1300 such as the field name 3711, the address 3712, the field area 3713, the crop planted 3714, etc.

Information related to spraying of the pesticide is displayed in the spraying information display area 3720. The pesticide to be sprayed varies depending on the cultivated crop name 3714 and the spraying time, and information on the pesticide to be sprayed on the next spraying flight is obtained from the pesticide management information 1600 and displayed.
The spraying information display area 3720 displays information related to the spraying of pesticides acquired or calculated by the spraying related information management module 1114 of the management server 702, such as the name of the pesticide, the amount to be sprayed, the dilution amount, and the amount of energy required for the spraying flight in the field.
Status 3730 displays information such as "surveyed" or "flight path exists" as the current status of the selected field 930.

Compared to the drone operation screen 900 in Figure 9, the screen display module 1011 has moved the altitude change button 924, which was previously located on the right side of the screen, to the left side, and has displayed the emergency stop button 925 with a shorter width, so that the various operation buttons are not hidden by the information display area 3710 regarding the next spraying flight.
Note that the display is merely an example, and the various operation buttons may be hidden, or other display designs may be used.

FIG. 38 is another example of a display screen 3800 that displays information regarding an upcoming spray flight.
The screen display module 1011 displays an information display area 3810 regarding the next spraying flight in the lower right corner of the screen.
In this example, the screen display module 1011 displays the spraying schedule for the day obtained from the schedule management information 1900, and information 3830 regarding the next spraying flight is displayed below information 3820 regarding field A where the current spraying flight is being performed.
Current time 3850 displays the current time in the schedule.

Furthermore, since the information 3840 regarding the next dispersion flight cannot be displayed in its entirety, continuation information 3841 indicating that there is continuing information is displayed outside the margin.
The information display area 3810 regarding the next spray flight can be scrolled up and down by swiping, etc., to display information regarding past or future spray flights.
As described above, at least one of the amount of the agent to be sprayed or the amount of energy required for spraying is displayed as information about the next spraying flight. As the amount of energy, for example, the number of batteries required for spraying is displayed. The information about the next spraying flight may also include information about the start time of the next spraying flight and the field to be sprayed.

FIG. 39 is an example of the next dispersion flight information display process flow 3900.
When the screen display module 1011 of the mobile terminal 701 receives drone operation instructions from the user, it displays the drone operation screen 900 (step 3910).
The screen display module 1011 acquires the schedule 1901 from the schedule management information 1900 (step 3920).
The screen display module 1011 acquires the next schedule notification time (step 3930).

The next schedule notification time is assumed to be about the time required for preparation for the next spraying flight, such as diluting the pesticide required for the next spraying flight, preparing a replacement battery, etc., and is assumed to be about 5 to 10 minutes. This notification time is determined in advance for each spraying flight and is stored in the schedule management information 1900.
Alternatively, the notification time may be set for each type of chemical to be sprayed on the next spray flight. For example, a longer time may be set when diluting a highly viscous chemical, since it takes time to dilute the chemical. Alternatively, the notification time may be set based on the time required to dilute the chemical to be sprayed on the next spray flight.

Alternatively, the notification time may be set based on the dilution amount of the chemical to be sprayed on the next spraying flight. The dilution amount may be at least one of the dilution rate of the chemical, the amount of water to be mixed with the chemical, or the total amount of the chemical after mixing with water. For example, if the total amount of chemical to be diluted is large, the time required for dilution is long, and therefore the notification time is set long.
In addition, if the schedule stored in the schedule management information 1900 requires that the battery be replaced before the next spraying flight, the notification time can be set to include the time required for battery replacement.

The screen display module 1011 detects that the next spraying schedule display button 940 has been selected by the user tapping the screen or selecting with a mouse, and when it accepts an instruction to display the next schedule (step 3940 is Yes), it displays information regarding the next schedule on the drone operation screen 900 (step 3960).
Alternatively, if the time until the next schedule is equal to or less than the notification time (step 3950: Yes), information regarding the next schedule is displayed on the drone operation screen 900 (step 3960).

Thereafter, the next scattered flight information display processing flow is repeated until an instruction to end the display is received (step 3970).
Although this flow is executed by the screen display module 1011 of the mobile terminal 701, it may also be executed by the screen output module 1111 of the management server 702, which generates and outputs a display screen, which is then displayed by the mobile terminal 701 or the management terminal 703.

FIG. 40 is an example of a schematic diagram showing the relationship between the amount of sprayed pesticide and the notification time.
The spray chemical is prepared by mixing the chemical with water and stirring to dilute it, but as the amount of chemical to be sprayed increases, the amounts of chemical and water also increase, and the time required for the dilution process increases. The notification time is set taking this increased time into consideration.
When comparing drug A and drug B, for example, drug B has a higher viscosity, and even when making the same spray drug, it takes longer to dilute and mix drug B than drug A, so the notification time is set longer.

For example, when chemical C needs to mix two types of chemicals and water, the initial time required is longer even if the amount to be sprayed is smaller than that of chemical A. On the other hand, the viscosity is low, so the time required for dilution and mixing is short, resulting in a steeper slope in the graph.
In this way, the notification time can be set based on the relationship between the amount of sprayed pesticide and the notification time.
In addition, since the amount of medicine to be sprayed varies depending on, for example, the medicine name, purpose, weight, dilution amount, time required for dilution, specifications, etc., which are stored in the medicine management information 1600, it is possible to store a graph or the like showing the relationship between this medicine-related information and the notification time, and set the notification time based on the relationship between this medicine-related information and the notification time.

The present invention is not limited to the above-described embodiments, but includes various modified examples. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and are not necessarily limited to those having all of the configurations described. It is also possible to replace part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. It is also possible to add, delete, or replace part of the configuration of each embodiment with other configurations.

In addition, the above-mentioned configurations, functions, processing units, processing means, etc. may be realized in hardware, in part or in whole, for example by designing them as integrated circuits. In addition, the above-mentioned configurations, functions, etc. may be realized in software by a processor interpreting and executing a program that realizes each function. Information on the programs, tables, files, etc. that realize each function can be stored in a memory, a recording device such as a hard disk or SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD.

In addition, the control lines and information lines shown are those that are considered necessary for the explanation, and not all control lines and information lines in the product are necessarily shown. In reality, it can be considered that almost all components are connected to each other.
The above-described embodiments disclose at least the configurations described in the claims.

100... drone, 701... mobile terminal, 702... management server, 703... management terminal, 710... base station

Claims (25)

An information processing device that controls a drone's flight to spray pesticides,
A storage unit that stores a plurality of pieces of farm field information;
an output unit that outputs the plurality of pieces of farm field information;
an input unit for accepting a selection from a plurality of fields;
A control unit that controls the flight of a drone that sprays pesticides,
The control unit is
Calculating a spraying flight time for performing a spraying flight to each of the multiple fields selected via the input unit and a travel time for traveling between each of the fields;
A drug spray schedule is generated based on the calculated spray flight time, the travel time, and constraint conditions,
The amount of drug loaded by the drone is set as the constraint,
Calculating a time to flight based on the amount of the drug;
In the pesticide spray schedule, the spray flight time and the travel time are arranged so as to fall within the flight time,
The output unit is an information processing device that outputs the generated drug dispersion schedule. The control unit calculates the flight time based on a relationship between the amount of the drug reduced during the spraying flight and the amount of energy consumed by the drone.
The information processing device according to claim 1 . The process of calculating the flight time based on the drug amount includes:
The amount of energy required for the spray flight is calculated based on the amount of reduction in the amount of the drug, and the flight time is calculated based on the amount of energy.
The information processing device according to claim 2 . The process of calculating the flight time based on the drug amount includes:
Calculating the remaining amount of energy based on the remaining amount of the drug, and calculating the remaining time to flight based on the remaining amount of energy.
The information processing device according to claim 2 . The control unit further calculates the flight time based on the specific gravity of each different drug and the drug amount.
The information processing device according to claim 3 . The constraint is the number of batteries used,
The information processing device according to any one of claims 1 to 5, wherein the control unit generates the drug dispersion schedule so as to minimize the number of batteries used. The constraint is a time required to complete the task,
An information processing device according to any one of claims 1 to 6, wherein the control unit generates the pesticide spray schedule so as to minimize the time required to complete the task. the input unit accepts a selection of a second constraint condition from among a plurality of constraint conditions;
The information processing device according to claim 1 , wherein the control unit generates the drug dispersion schedule so as to satisfy the constraint condition, which is the drug amount, and the selected second constraint condition. The information processing device according to claim 8, wherein the selected second constraint condition is at least one of the available work time, the available flight time using the battery held, the amount of medicine that the drone can carry at one time, the number of batteries used, and the time until the work is completed. The control unit calculates at least one of a drug dispersion amount or an energy amount used in the drug dispersion schedule,
An information processing device according to any one of claims 1 to 9, wherein the output unit displays at least one of the calculated drug spray amount or energy amount on the drug spray schedule. The information processing device according to any one of claims 1 to 10, wherein the output unit displays in an area on the spraying schedule that indicates each of the fields that the spraying flight for each of the fields has ended. using the field information for the selected multiple fields, the spraying flight time for performing a spraying flight to each field, the travel time for traveling between each field, the constraint conditions, and the pesticide spraying schedule as training data;
the control unit generates a route search model by machine learning, the route search model receiving the field information, the flight time, the travel time, and the constraint conditions, and outputting the pesticide spray schedule;
An information processing device described in any one of claims 1 to 11, wherein the control unit accepts input of the field information, the spraying flight time, the travel time, and the constraint conditions, and uses the route search model to output the pesticide spraying schedule estimated from the input information. A control method for controlling a drone flight that sprays pesticides using an information processing device, comprising:
The information processing device includes:
A storage unit that stores a plurality of pieces of farm field information;
an output unit that outputs the plurality of pieces of farm field information;
an input unit for accepting a selection from a plurality of fields;
A control unit that controls the flight of a drone that sprays pesticides,
Calculating a spraying flight time for performing a spraying flight to each of the multiple fields selected via the input unit and a travel time for traveling between each of the fields;
A pesticide spray schedule is generated based on the calculated spray flight time, the travel time, and constraint conditions,
The amount of drug loaded by the drone is set as the constraint,
Calculating a time to flight based on the amount of the drug;
In the pesticide spray schedule, the spray flight time and the travel time are arranged so as to fall within the flight time,
A control method characterized by outputting the generated pesticide spray schedule. The control unit calculates the flight time based on a relationship between the amount of the drug reduced during the spraying flight and the amount of energy consumed by the drone.
The control method according to claim 13. The process of calculating the flight time based on the drug amount includes:
The amount of energy required for the spraying flight is calculated based on the amount of reduction in the amount of the drug, and the flight time is calculated based on the amount of energy.
The control method according to claim 14. The process of calculating the flight time based on the drug amount includes:
Calculating the remaining amount of energy based on the remaining amount of the drug, and calculating the remaining time to flight based on the remaining amount of energy.
The control method according to claim 14. The control unit further calculates the flight time based on the specific gravity of each different drug and the drug amount.
17. A control method according to claim 15 or 16. The control method according to any one of claims 13 to 17, wherein the constraint condition is the number of batteries in use, and the drug dispersion schedule is generated to minimize the number of batteries in use. The control method according to any one of claims 13 to 18, wherein the constraint condition is the time until the task is completed, and the drug spray schedule is generated so as to minimize the time until the task is completed. The control method described in claim 13, wherein the input unit accepts selection of a second constraint condition from among a plurality of constraint conditions, and generates the drug dispersion schedule so as to satisfy the constraint condition , which is the drug amount, and the selected second constraint condition. The control method described in claim 20, wherein the multiple selected second constraint conditions are at least one of the available work time, the available flight time using the batteries held, the amount of medicine that the drone can carry at one time, the number of batteries used, and the time required to complete the work. A control method according to any one of claims 13 to 21, which calculates at least one of the pesticide spray amount or energy amount used in the pesticide spray schedule, and displays at least one of the calculated pesticide spray amount or energy amount on the pesticide spray schedule. The control method according to any one of claims 13 to 22, further comprising displaying in an area on the spraying schedule indicating each of the fields that the spraying flight for each of the fields has ended. using the field information for the selected multiple fields, the spraying flight time for performing a spraying flight to each field, the travel time for traveling between each field, the constraint conditions, and the pesticide spraying schedule as training data;
A route search model is generated by machine learning, the route search model inputting the field information, the spraying flight time, the travel time, and the constraint conditions, and outputting the pesticide spraying schedule;
A control method described in any one of claims 13 to 23, which accepts input of the field information, the spraying flight time, the travel time, and the constraint conditions, and uses the route search model to output the pesticide spraying schedule estimated from the input information. A program for causing an information processing device to execute each step of the control method according to any one of claims 13 to 24.

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