Computer programs, information processing methods, and agricultural machinery

Abstract

We provide computer programs and other tools that can solve a variety of problems related to agricultural machinery. [Solution] The computer program obtains questions from the user regarding agricultural machinery, The computer is instructed to perform a process that generates a solution to the acquired question and outputs the generated solution.

Description

Technical Field

[0001] The present invention relates to a computer program, an information processing method, and an agricultural machine.

Background Art

[0002] Conventionally, techniques have been proposed for solving problems encountered during work performed using agricultural machines. For example, Patent Document 1 discloses a control device for agricultural machinery that includes a discriminating means for discriminating the type of communication system of a traveling vehicle according to the combination of the data reception speed and the value of an ID field, and can eliminate problems that occur when traveling vehicles of different manufacturers and models are used.

Prior Art Literature

Patent Literature

[0003]

Patent Literature 1

Summary of the Invention

Problem to be Solved by the Invention

[0004] However, the control device for agricultural machinery described in Patent Document 1 is a technique that focuses on communication problems between a traveling vehicle and a working machine, and has the problem that other problems are not taken into consideration. Various problems can occur in work using agricultural machinery. Therefore, a technique that can solve various problems related to agricultural machinery is desired.

[0005] An object of the present disclosure is to provide a computer program and the like that can solve various problems related to agricultural machinery.

Means for Solving the Problem

[0006] A computer program according to one aspect of the present disclosure causes a computer to execute processing of acquiring a question about an agricultural machine from a user, generating a solution to the acquired question, and outputting the generated solution.

[0007] An information processing method according to one aspect of this disclosure involves a computer performing the following processes: obtaining a question from a user regarding agricultural machinery, generating a solution to the obtained question, and outputting the generated solution.

[0008] An agricultural machine according to one aspect of this disclosure includes a control unit that performs a process of obtaining a question from a user regarding the agricultural machine, generating a solution to the obtained question, and outputting the generated solution. [Effects of the Invention]

[0009] This disclosure can solve a variety of problems related to agricultural machinery. [Brief explanation of the drawing]

[0010] [Figure 1] This is an overview diagram of the agricultural work support system. [Figure 2] This is a block diagram showing an example configuration of an agricultural work support system. [Figure 3] This is a schematic diagram showing an example of a screen illustrating a solution. [Figure 4] This flowchart shows an example of the solution generation process. [Figure 5] This flowchart shows an example of a processing procedure performed by the tractor of the second embodiment. [Figure 6] This flowchart shows an example of a processing procedure performed by the tractor of the third embodiment. [Figure 7] This flowchart shows an example of a processing procedure performed by the tractor of the fourth embodiment. [Modes for carrying out the invention]

[0011] This disclosure will be described in detail with reference to drawings illustrating embodiments thereof.

[0012] (First Embodiment) Figure 1 is an overview diagram of the agricultural work support system 100. The agricultural work support system 100 is a system that supports agricultural work performed by an operator using a tractor 1. The agricultural work support system 100 is equipped with a tractor 1 as its main device. The tractor 1 is connected to the management server 2 and the terminal device 3 in a communication manner. The number of tractors 1 and terminal devices 3 may be two or more.

[0013] Tractor 1 is an example of agricultural machinery. Agricultural machinery is a machine used for agricultural purposes and performs farming tasks such as tilling, sowing, pest control, fertilizing, planting crops, and harvesting on the ground in a field. The agricultural machinery to which this system is applied is not limited to tractor 1, and may also include, for example, harvesters, rice transplanters, riding cultivators, vegetable transplanters, lawnmowers, seeders, fertilizer spreaders, etc.

[0014] Tractor 1 can function independently as a work vehicle, or, as shown in Figure 1, by connecting implements 4 via a coupling device, the entire work vehicle and implement can function as a single agricultural machine. Tractor 1 can handle multiple types of agricultural work depending on the implement 4 being towed. The implement 4 shown in Figure 1 is a tilling device, but implement 4 is not limited to tilling devices. For example, any implement such as a seeder, spreader, transplanter, mower, rake, baler, harvester, spreader, or harrow can be connected to the work vehicle and used.

[0015] The tractor 1 may have an automatic driving function. In this case, the tractor 1 automatically travels within the field according to a predetermined route using any positioning technology, and automatically performs work using the implement 4.

[0016] The management server 2 is an information processing device capable of various types of information processing and information transmission / reception, for example, it can be a server computer, a personal computer, a quantum computer, or the like. The management server 2 can transmit and receive data to and from the tractor 1 via a network N such as the Internet or a carrier network that implements wireless communication according to a predetermined mobile communication standard. The management server 2 collects and manages history information related to work performed by the tractor 1. The history information accumulated in the management server 2 can be provided to an operator via the tractor 1 or the terminal device 3.

[0017] The terminal device 3 is a portable computer having a communication function and a display function, for example, it can be a smartphone, a tablet terminal, or the like. The terminal device 3 is used by an operator who performs work using the tractor 1. The operator is an example of a user of the present system.

[0018] Figure 2 is a block diagram showing a configuration example of the agricultural work support system 100. The tractor 1 includes a control unit 11, a storage unit 12, a communication unit 13, an output unit 14, an operation unit 15, a voice input unit 16, a sensor unit 17, a drive unit 18, and the like.

[0019] The control unit 11 includes arithmetic processing devices such as a CPU (Central Processing Unit), an MPU (Micro-Processing Unit), and a GPU (Graphics Processing Unit). The control unit 11 uses built-in memory such as ROM (Read Only Memory) or RAM (Random Access Memory), a clock, a counter, and the like to control each component and execute processing.

[0020] The control unit 11 in this embodiment performs processing related to providing solutions to questions and also functions as an ECU (Electronic Control Unit), performing control related to the movement of the tractor 1, control related to the work of the tractor 1, etc. Through its function as an ECU, the control unit 11 controls, for example, the speed of the tractor 1, the steering of the tractor 1, the rotation speed of the PTO (Power Take-Off) that transmits power from the engine to the implement 4, the raising and lowering of the coupling device, hydraulics, etc.

[0021] The memory unit 12 includes a non-volatile storage device such as a hard disk, flash memory, or SSD (Solid State Drive). The memory unit 12 stores various computer programs and data referenced by the control unit 11. The memory unit 12 stores a program 1P that causes the computer to execute processing related to providing solutions to questions, and a language processing model 121 necessary for the execution of this program 1P. The language processing model 121 is a learning model generated by machine learning. The language processing model 121 is intended to be used as a program module that constitutes part of artificial intelligence software.

[0022] A computer program (computer program product) including program 1P may be provided on a non-temporary recording medium 1A on which the computer program is recorded in a readable format. The storage unit 12 stores the computer program read from the recording medium 1A by a reading device (not shown). The recording medium 1A is, for example, a magnetic disk, an optical disk, or a semiconductor memory. Alternatively, the computer program may be downloaded from an external server connected to a communication network and stored in the storage unit 12. Program 1P may be a single computer program or composed of multiple computer programs, and may be executed on a single computer or on multiple computers interconnected by a communication network.

[0023] The communication unit 13 includes a first communication unit 131, a second communication unit 132, and a third communication unit 133. The first communication unit 131 includes a communication module that performs communication using a communication protocol such as CAN (Control Area Network) or Ethernet (Ethernet / registered trademark). The control unit 11 communicates with various in-vehicle equipment and implements 4 through the first communication unit 131. The control unit 11 receives signals from the implements 4 through the first communication unit 131 and can perform control related to the movement and work of the tractor 1 according to the received signals.

[0024] The second communication unit 132 is equipped with a communication module that performs communication using communication protocols such as 4G, 5G, LTE (Long Term Evolution), and WiFi (registered trademark). The control unit 11 transmits and receives various information between the management server 2 and a base station or access point (not shown) via the network N through the second communication unit 132.

[0025] The third communication unit 133 includes a communication module for short-range wireless communication, such as Bluetooth®, BLT (Bluetooth Low Energy), or WiFi. The control unit 11 transmits and receives various information to and from the terminal device 3 through the third communication unit 133. The third communication unit may also include a communication module for wired communication, such as the USB (Universal Serial Bus®) standard.

[0026] Furthermore, the communication methods of the first communication unit 131, the second communication unit 132, and the third communication unit 133 are not limited to the examples described above, and any appropriate communication method that enables communication between the tractor 1 and the implement 4, the on-board equipment, the management server 2, and the terminal device 3 can be used.

[0027] The output unit 14 includes, for example, a display device such as a liquid crystal panel, an organic EL (Electro Luminescence) display, or a projector, as well as an output device such as an LED (Light Emitting Diode) lamp, a speaker, or a buzzer. The output unit 14 outputs various types of information to be notified to the operator in accordance with instructions from the control unit 11. If the output unit 14 is a display device, it is preferable that the display device be located around the driver's seat and in a position visible to the operator while driving.

[0028] The control unit 15 includes, for example, pedals such as an accelerator and brake, a steering wheel, levers, switches, a touch panel device with a built-in display, etc. The control unit 15 receives various operations, including operations related to the driving of the tractor 1, and sends control signals to the control unit 11 according to the content of the received operations.

[0029] The voice input unit 16 is an interface that receives voice messages representing the worker's questions. The voice input unit 16 includes, for example, a microphone. The microphone converts the worker's sound waves into voice data and sends the converted voice data to the control unit 11.

[0030] The sensor unit 17 includes sensors that detect information related to the basic operation of the tractor 1, such as vehicle speed, transmission, engine speed, PTO speed, hydraulic pressure, and the mounting status of the implement 4. In addition, it includes a camera that images the area around the tractor 1, a position sensor that detects the position of the tractor 1 (e.g., GPS (Global Positioning System) receiver, ultrasonic sensor, radar sensor, LIDAR (Laser Imaging Detection and Ranging)), an odometer that detects the distance traveled by the tractor 1, a spray amount meter that detects the amount of spraying (e.g., fertilizer spraying amount, pesticide spraying amount, seeding amount, etc.), a harvest amount sensor that detects the harvest yield, and a taste sensor that detects the taste of the produce. The control unit 11 receives detection data detected by the sensor unit 17 as needed. The control unit 11 uses the received detection data to generate solutions and control the tractor 1, etc. Some or all of the detection data from the sensor unit 17 may be transmitted to the management server 2 and stored in the management server 2 as history information.

[0031] The drive unit 18 is equipped with various devices necessary for the movement of the tractor 1 and the driving of the tractor 1 and the implement 4, including power sources such as an engine and motor, a transmission, a clutch axle, brakes, front wheels, rear wheels, a PTO, and a coupling device. The drive of the drive unit 18 is controlled by the control unit 11.

[0032] The implement 4 includes a control unit, a communication unit, a drive unit, sensors, etc., which are not shown in the illustration. The drive unit of the implement 4 includes devices such as a hydraulic system, an electric motor, or a pump, depending on the application of the implement 4. The control unit of the implement 4 causes the drive unit to perform various operations in response to control signals transmitted from the tractor 1 via the communication unit. The control unit of the implement 4 also transmits signals to the tractor 1 according to the status of the implement 4.

[0033] The management server 2 comprises a control unit 21, a storage unit 22, and a communication unit 23. The management server 2 may be configured with multiple computers for distributed processing, or it may be implemented by multiple virtual machines located within a single server, or it may be implemented using a cloud server.

[0034] The control unit 21 includes one or more processors, such as CPUs and GPUs. The control unit 21 uses built-in memory such as ROM or RAM, a clock, counters, etc., to control each component and execute processing.

[0035] The storage unit 22 includes, for example, non-volatile memory such as a hard disk, flash memory, or SSD. The storage unit 12 may be an external storage device connected to the management server 2. The storage unit 22 stores various computer programs and data referenced by the control unit 21.

[0036] The communication unit 23 includes a communication module that enables communication via the network N. The control unit 11 sends and receives data to and from the tractor 1 via the communication unit 23.

[0037] The terminal device 3 includes a control unit 31, a storage unit 32, a communication unit 33, a display unit 34, and an operation unit 35, etc.

[0038] The control unit 31 is an arithmetic circuit equipped with a CPU, ROM, RAM, etc. The CPU or GPU in the control unit 31 executes various computer programs stored in the ROM and memory unit 32, and controls the operation of the hardware components described above.

[0039] The storage unit 32 includes non-volatile storage devices such as flash memory and hard disk drives. The storage unit 32 stores various computer programs and data that the control unit 31 references.

[0040] The communication unit 33 includes a communication module that enables communication with the third communication unit 133 of the tractor 1. The control unit 31 sends and receives various information with the tractor 1 through the communication unit 33. The communication unit 33 may also include a communication module that enables communication via the network N.

[0041] The display unit 34 includes a display device such as a liquid crystal display or an organic EL display, and displays information to be notified to the worker according to instructions from the control unit 31.

[0042] The operation unit 35 includes, for example, a keyboard, a touch panel device with a built-in display, a speaker, and a microphone, and receives operation input from the operator and sends control signals to the control unit 31 according to the operation content.

[0043] The agricultural work support system 100 receives questions from workers regarding agricultural work using the tractor 1 and provides solutions to the received questions, thereby supporting the smooth execution of work. In this embodiment, the tractor 1 generates solutions to the questions using a language processing model 121.

[0044] The language processing model 121 generates solutions to problems related to the use of tractor 1 in response to questions that describe such problems. Examples of language processing models that can be used for 121 include BERT (Bidirectional Encoder Representations from Transformers), Transformer, GPT (Generative Pre-trained Transformer)-3, and GPT-4. The above model is a general-purpose natural language processing model constructed by unsupervised pre-training with a large set of texts.

[0045] The language processing model 121 has an input layer that accepts a question, an intermediate layer (hidden layer) that extracts features of the question, and an output layer that outputs a solution. In the Transformer model, the intermediate layer includes an Attention layer that can extract the position of words within the entire sentence. Since natural language processing models are well-known technologies, further detailed explanations are omitted.

[0046] Alternatively, instead of storing the language processing model 121 in the storage unit 12 of the tractor 1, the tractor 1 may access and read the language processing model 121 stored in the management server 2, terminal device 3, or an external language processing server.

[0047] Tractor 1 may fine-tune a pre-trained language processing model 121 using training data that associates questions related to problems specific to Tractor 1 with solutions to those questions. Through fine-tuning, the language processing model 121 can accurately generate solutions appropriate to the type of Tractor 1. Fine-tuning may be performed on the management server 2.

[0048] The configuration of the language processing model 121 is not limited to the example described above. The language processing model 121 only needs to be capable of generating solutions to questions. The language processing model 121 may also use other learning algorithms, such as RNN (Recurrent Neural Network) or LSTM (Long Short-Term Memory).

[0049] The language processing model 121 is not limited to machine learning models, but may also derive solutions using rule-based methods. The tractor 1 may, for example, pre-store a database (not shown) in the storage unit 12 that associates one or more keywords with solutions, and read out solutions corresponding to keywords extracted from the query by referring to this database.

[0050] Tractor 1 accepts questions from the operator regarding Tractor 1. These questions include, for example, questions about problems encountered during farm work using Tractor 1, questions about its current condition, and questions to obtain advice for better operation. Specifically, questions may include: "How do I use the tilling attachment?", "How do I install the tilling attachment?", "Is the height of the tilling attachment correct?", "Am I driving it properly?", and "Automatic driving isn't working."

[0051] Tractor 1 inputs information indicating the acquired question into the language processing model 121. The question is input into the language processing model 121 as a token generated by, for example, converting the speech data related to the utterance (question) into text, and then analyzing the text using morphological analysis or the like. Alternatively, Tractor 1 may display an input screen including a question input field on the output unit 14 and accept question input from the operator using this input screen.

[0052] The language processing model 121 generates sentences that represent solutions to the question. The generated solutions include specific means, methods, etc., for resolving the content of the question.

[0053] The language processing model 121 acquires data (information) from the control unit 31 related to the operator's question about tractor 1. For example, in response to the question, "Automatic driving is not possible," the language processing model 121 uses the characters "automatic driving" included in the question as a key to acquire data related to automatic driving. When the language processing model 121 acquires data related to automatic driving, it uses the information "Automatic driving is not possible" to determine whether the pre-set conditions for automatic driving are met. For example, if sufficient data for automatic driving cannot be obtained from the GPS, it identifies that the GPS reception sensitivity is insufficient and outputs "It's because the GPS is not receiving a signal" as a solution. Furthermore, in response to the question "Is the height of the tiller okay?", the language processing model 121 uses the characters "tiller height" included in the question as a key to obtain data related to "tiller height". Once the language processing model 121 obtains data related to the tiller height, it uses the information "Is the height of the tiller okay?" to determine whether the height of the tiller is appropriate or not. If the height of the tiller is higher than a pre-set threshold range, it calculates the height at which the tiller height will be within the threshold range, and based on the calculation result, outputs "It would be better to lower the height of the tiller by 1m" as a solution. Furthermore, in response to the question "Am I driving well?", the language processing model 121 uses the word "driving" included in the question as a key to acquire data related to "driving". When the language processing model 121 acquires data related to driving, it uses the information from "Am I driving well?" to determine whether the current driving is appropriate or not. If the vehicle speed is faster than a preset threshold range, it outputs "Drive a little slower" as a solution.

[0054] As described above, the language processing model 121 acquires data from the control unit 31 related to the operator's question about the tractor 1. The data related to the question may include detection data from the sensor unit 17. The language processing model 121 compares the desired state of the tractor 1 corresponding to the question with the current data (information) of the tractor 1, and if there is a discrepancy, outputs a solution that can resolve the discrepancy. The desired state of the tractor 1 refers to the conditions under which the desired driving or work is performed, such as when the conditions for automatic driving are met in the case of automatic driving, when the conditions for the height of the tilling device are met in the case of tilling height, or when the conditions for driving are met in the case of driving.

[0055] The language processing model 121 may generate a single solution to a single question from the operator, or it may generate multiple solutions in a step-by-step manner. For example, in response to a question such as "The vehicle cannot drive autonomously," the language processing model 121 may output the following solutions in step-by-step order: first solution "Because the GPS signal is not being received," second solution "Move to a place where the GPS signal can be received," and third solution "Wait in that location for 15 minutes." The operator can then address the problem by following the presented solutions in step-by-step order.

[0056] The generated solution is output through the output unit 14 of the tractor 1. The tractor 1 generates a screen containing text showing the solution, for example, and displays the generated screen on a display device. The tractor 1 may pre-store an illustration database (not shown) that associates expected solutions with illustrations, and generate a screen containing an illustration corresponding to the acquired solution. The illustration database may store one or more keywords that may be included in the solution, associating them with illustrations. The tractor 1 may generate an illustration representing the solution using an image generation model that takes text information as input and generates an image corresponding to that text information. The solution is not limited to being output from a display device; for example, it may be output from a speaker as audio data, or it may be output by lighting up an LED lamp.

[0057] Figure 3 is a schematic diagram showing an example of a screen 40 that displays solutions. Screen 40 includes multiple solution display units 401 and 402, each corresponding to a set of solutions to a given question. The solution display units 401 and 402 are arranged according to predetermined rules based on the step-by-step order of the solutions. In the example shown in Figure 3, the solution display units 401 and 402 are arranged from top to bottom of the screen in order of increasing step-by-step. Solution display unit 401 displays a document and illustration indicating the first solution, "Move forward 5 meters." Solution display unit 402 displays a document and illustration indicating the second solution, "Lower the tilling device." The solution display units 401 and 402 may also include selectable input buttons 403 and 404. Input buttons 403 and 404 will be described later.

[0058] When tractor 1 obtains a solution output from language processing model 121, it refers to the above-mentioned illustration database, reads the illustration corresponding to the solution, and displays it on solution display units 401 and 402 along with the text. The illustration of the solution regarding the operating method may be an image that clearly shows the operating part and the operating method, as shown in Figure 3.

[0059] The operating parts corresponding to the operating method are not limited to those shown in images; any information that visually identifies the operating parts is acceptable. For example, if the solution is "lower the tiller," tractor 1 extracts the keywords "tiller" and "lower" from the solution to identify the operating part (e.g., the operating lever) corresponding to the operation of lowering the tiller. Tractor 1 then notifies the operator of the identified operating part, for example, by illuminating an LED lamp installed near the identified operating part.

[0060] Tractor 1 may output solutions by combining multiple output modes. For example, Tractor 1 may display a screen showing the solution on a display and output the solution by voice. This allows the operator to recognize the solution more easily and reliably.

[0061] In addition, the language processing model 121 may not be able to output a solution that satisfies the predetermined requirements. For example, the solution generated by the language processing model 121 may include content that does not solve the problem, such as "I don't know." In cases where a solution that satisfies the predetermined requirements cannot be output, the tractor 1 may output contact information for contacting an operator. The contact information may include, for example, the operator's phone number, an icon for calling or chatting with the operator, a QR code (registered trademark) for calling or chatting with the operator, etc.

[0062] The above describes an example in which tractor 1 receives questions and provides solutions. However, tractor 1 may also be configured to receive questions or output solutions to terminal device 3 via terminal device 3. Tractor 1 may also be configured to appropriately change the output destination of solutions according to the operator's selection.

[0063] The tractor 1 and the operator's terminal device 3 may be paired in advance. Prior to using the machine, the tractor 1 performs a pairing process to perform mutual authentication between the tractor 1 and the operator's terminal device 3, which is the legitimate user of the tractor 1, and stores the authentication information of the correct terminal device 3. For example, when unlocking the door, the tractor 1 performs an authentication process on surrounding terminal devices 3 and determines whether they are correct terminal devices 3 that have been paired. If it is determined that the terminal device 3 is paired, the tractor 1 establishes mutual communication using a predetermined communication standard. If it is determined that the terminal device 3 is not paired, the tractor 1 may perform a warning process against unauthorized use. The tractor 1 may perform a warning process such as outputting an alert sound, sending a notification to the management server 2, or starting to take pictures of the surroundings with the camera. The warning process may include a process that prohibits the provision of the above-mentioned solutions. This prevents unauthorized use of the tractor 1.

[0064] Figure 4 is a flowchart showing an example of the solution generation process. The processes in each flowchart below may be executed by the control unit 11 according to the program 1P stored in the memory unit 12 of the tractor 1, or they may be implemented by a dedicated hardware circuit (e.g., FPGA or ASIC) provided in the control unit 11, or they may be implemented by a combination of the above.

[0065] The control unit 11 of the tractor 1 checks whether pairing with the terminal device 3 held by the operator has been completed (step S11). The control unit 11 performs an authentication process using appropriate authentication information of the terminal device 3 that has been stored in advance, for example, by a predetermined wireless communication standard, and determines whether pairing has been completed.

[0066] If it is determined that pairing has not been performed (S11: NO), the control unit 11 performs a predetermined warning process (step S12). If it is determined that pairing has not been performed, the control unit 11 may prohibit the processing from step S13 onward, that is, it may not accept the query. If it is determined that pairing has been performed (S11: YES), the control unit 11 proceeds to step S13.

[0067] The control unit 11 acquires information indicating a question from the worker (step S13). The worker can input a question at any time. The control unit 11 may accept the question as voice data through the voice input unit 16, or as text through the operation unit 35. The control unit 11 may also acquire information indicating a question by receiving the question received by the terminal device 3 via communication.

[0068] The control unit 11 inputs the acquired question to the language processing model 121 (step S14) and obtains the solution output from the language processing model 121 (step S15). The language processing model 121 acquires data related to the question according to the keywords contained in the question and compares the acquired data with the appropriate conditions corresponding to the question. If the acquired data and the appropriate conditions corresponding to the question are inconsistent, the language processing model 121 outputs a solution that matches or approximates the acquired data to the appropriate conditions corresponding to the question. The language processing model 121 may output one solution or may output multiple solutions in stages.

[0069] The control unit 11 outputs the acquired solutions (step S16). The control unit 11 generates a screen that displays the acquired solutions in step order, for example, and displays the generated screen on the output unit 14. The operator can recognize the solutions, including the order of implementation, through the screen.

[0070] The control unit 11 determines whether or not to terminate the acceptance of inquiries (step S17). If it determines not to terminate because it has not detected a predetermined termination operation (e.g., locking the door, disconnecting communication with terminal device 3, etc.) (S17: NO), the control unit 11 returns to step S13 and continues to accept inquiries. If it determines to terminate because it has detected a predetermined termination operation (S17: YES), the control unit 11 terminates the series of processes.

[0071] According to this embodiment, it is possible to receive a variety of questions regarding work using agricultural machinery and provide solutions to the received questions. By providing specific solutions, it is possible to prevent situations where, for example, when a problem occurs during work, only an error message is displayed and no solution is shown, leading to the work being terminated without knowing how to proceed, thereby improving user convenience. Because it is possible to generate solutions to a variety of questions, even when a variety of questions are anticipated, such as with agricultural machinery that performs various types of work with various work implements 4 attached, it is possible to generate appropriate solutions.

[0072] By using a language processing model, solutions to questions can be generated easily and accurately. By outputting multiple solutions in a step-by-step manner, appropriate solutions can be provided even when problem solving requires multiple steps. By clearly outputting solutions using screens, audio, etc., even workers unfamiliar with agricultural machinery can easily and accurately implement the solutions. Since tractor 1 generates and outputs solutions, solutions can be presented quickly regardless of the communication environment.

[0073] (Second Embodiment) In the second embodiment, a configuration is described in which the tractor 1 automatically controls each component according to the generated solution. In the following embodiments, the differences from the first embodiment will be mainly described, and components common to the first embodiment will be denoted by the same reference numerals and their detailed descriptions will be omitted.

[0074] In the second embodiment, the tractor 1 automatically controls the travel system or work system of the tractor 1 or the implement 4 according to the generated solution. For example, if the solution includes at least one of control information relating to the control of the tractor 1 and control information relating to the implement 4, the tractor 1 directly or indirectly controls the operation of the tractor 1 or the implement 4 by outputting a control instruction corresponding to the solution. The control information includes, for example, information regarding the direction of travel of the tractor 1, the distance traveled, the speed of travel, the rotation speed of the PTO, the height of the coupling device, and the drive of the drive unit of the implement 4.

[0075] Control instructions for executing control information can be automatically generated by the language processing model 121. The language processing model 121 of the second embodiment takes a query as input and generates a solution that includes control instructions for controlling the tractor 1 or the implement 4. When the tractor 1 receives a control instruction generated by the language processing model 121, it outputs the acquired control instruction to the drive unit 18 or the implement 4. As a result, for example, the direction of travel of the tractor 1, the distance traveled, the speed of travel, the rotation speed of the PTO, the height of the coupling device, the drive of the implement 4, etc., are automatically controlled by the tractor 1. Note that the control instructions are not limited to those generated using the language processing model 121; for example, the control unit 11 of the tractor 1 may generate them by specifying the content of the operation, the operating part, the amount of operation, etc., indicated by the solution based on the solution.

[0076] As a condition for executing control according to the solution, tractor 1 may accept execution permission from the operator. Tractor 1 accepts execution permission from the operator using, for example, the screen 40 shown in Figure 3. As shown in Figure 3, the solution display sections 401 and 402 of screen 40 include an input button 403 labeled "Execute Permission" to be specified when permission is granted, and an input button 404 labeled "Disallow" to be specified when permission is denied. By the operator specifying an input button 403, tractor 1 accepts execution permission for the solution corresponding to the specified input button 403. If multiple solutions are generated, the system may be configured to accept execution permission or disallowance for each solution. The method of accepting execution permission is not limited to the example described above.

[0077] Figure 5 is a flowchart showing an example of a processing procedure performed by the tractor 1 of the second embodiment.

[0078] After outputting the solution, the control unit 11 of tractor 1 determines whether or not it has obtained permission to execute from the operator (step S21). For example, if it determines that permission to execute has not been obtained because the input button 403 is not selected on screen 40 (S21: NO), the control unit 11 terminates the process.

[0079] For example, if the system determines that permission to execute has been obtained because the input button 403 is selected on screen 40 (S21: YES), the control unit 11 identifies a control instruction corresponding to the solution for which execution has been permitted and outputs the identified control instruction (step S22). As described above, the control instruction is output along with the solution by the language processing model 121. The control unit 11 controls the operation of the tractor 1 or implement 4 according to the generated control instruction.

[0080] According to this embodiment, the entire process from generating a solution to controlling it according to that solution can be performed in a single step, allowing for smoother problem resolution. By accepting whether or not to execute the solution, unintended control execution can be prevented, improving convenience. For multi-stage solutions, accepting whether or not to execute each solution allows for the user to arbitrarily select between manual or automatic control depending on the solution, further improving convenience.

[0081] (Third embodiment) In the third embodiment, a configuration for determining whether appropriate operations are being performed according to the solution will be described.

[0082] Figure 6 is a flowchart showing an example of a processing procedure performed by the tractor 1 of the third embodiment.

[0083] After outputting a solution, the control unit 11 of the tractor 1 determines whether the operation performed by the operator is appropriate (step S31). An appropriate operation means that the operation is performed in accordance with the generated solution. For example, the control unit 11 determines whether the current operation and the operation of the solution match or approximate by comparing the content of the operation, operating location, amount of operation, etc. indicated by the generated solution with the content of the current operation, operating location, amount of operation, etc. identified based on the detection data detected by the sensor unit 17.

[0084] If the control unit 11 determines that the operation is inappropriate because the current operation does not match or approximate the solution operation (S31: NO), it outputs a notification indicating that the operation is inappropriate through the output unit 14 (step S32). The control unit 11 outputs a message such as "The operation is incorrect." Based on the comparison result between the current operation and the solution operation, the control unit 11 may identify corrective operations that should be performed to make the operation appropriate and output a notification indicating the identified corrective operations. Examples of notifications indicating corrective operations include "Move a little more to the right" and "Slow down a little." The notification of the determination result may also be output by voice, warning sound, etc.

[0085] If the control unit 11 determines that the operation is appropriate because the current operation status matches or approximates the operation of the solution (S31: YES), it outputs a notification indicating that the operation is appropriate through the output unit 14 (step S33). The control unit 11 outputs messages such as "Keep it up" or "Has the problem been solved?". Note that if the operation is appropriate, the output of the notification may be omitted.

[0086] According to this embodiment, determining whether the operator's actions are appropriate leads to a more reliable solution to the problem. By notifying the operator of the determination result, the operator can clearly understand whether the actions are appropriate or not, and proceed with the work more smoothly.

[0087] (Fourth Embodiment) In the fourth embodiment, the details of the input information input to the language processing model 121 differ. In the fourth embodiment, in addition to the question, the input information to the language processing model 121 includes driving information of the tractor 1 and growth information of crops grown using the tractor 1.

[0088] Driving information is information about the driving status of tractor 1, and includes, for example, engine load, driving speed, driving position, driving distance, battery level, GPS reception strength, PTO rotation speed, coupling device height, hydraulic pressure, type of attached implement 4, and the current location of tractor 1. Growth information is information about crop growth, and includes, for example, crop size, color, yield, taste, fertilizer application amount, pesticide application amount, and seed application amount. Driving information and growth information can be obtained, for example, by acquiring various detection data detected by the sensor unit 17, as detection data or analysis data based on the detection data.

[0089] Driving information and growth information may be generated based on time-series detection data. For example, the management server 2 continuously receives and stores detection data transmitted from the tractor 1. Based on the history of the obtained detection data and map information of the fields managed by the operator, the management server 2 identifies which fields the tractor 1 performed what tasks on, the growth status of the crops in each field, the harvest status, etc. The management server 2 stores the historical information, including the identified information, in association with the identification information of the tractor 1 or the operator. When generating a solution, the tractor 1 may receive the above-mentioned historical information from the management server 2 as driving information and growth information. Driving information and growth information may also be obtained by accepting input from the operator.

[0090] Tractor 1 inputs acquired driving information and growth information, along with questions from the operator, into a language processing model 121, and obtains solutions output from the language processing model 121. For example, the language processing model 121 generates solutions such as "There is no need to spray pesticides" or "Let's spread fertilizer today" in response to a question from tractor 1 on a specific field, "What work should I do today?", and the corresponding driving information and growth information for tractor 1. Note that the input information to the language processing model 121 may consist of either driving information or growth information, or it may not include any questions. The language processing model 121 may be fine-tuned using training data that includes the aforementioned driving information and growth information.

[0091] Figure 7 is a flowchart showing an example of a processing procedure performed by the tractor 1 of the fourth embodiment.

[0092] The control unit 11 of the tractor 1 acquires information indicating a question from the operator (step S41). Before acquiring the question, the control unit 11 may perform a pairing process in the same manner as in the first embodiment. The control unit 11 acquires driving information and growth information (step S42). The control unit 11 may receive driving information and growth information corresponding to the identification information of the tractor 1 or operator from the management server 2 by transmitting a request for driving information and growth information, along with the identification information of the tractor 1 or operator, to the management server 2.

[0093] The control unit 11 inputs the acquired question, driving information, and growth information into the language processing model 121 (step S43), and obtains the solution output from the language processing model 121 (step S44). Thereafter, the control unit 11 performs the same processing as in steps S16 to S17 of the first embodiment.

[0094] According to this embodiment, solutions can be generated by taking into account driving information and growth information. By using more information about the tractor 1 as input elements, the accuracy of the solutions generated by the language processing model 121 can be improved. Solutions tailored to the usage conditions of the tractor 1 can be provided, as well as solutions to a wider variety of questions. For example, in response to a question such as "Why is the crop growing poorly?", information such as the recommended type of fertilizer and the amount of fertilizer to apply can be presented.

[0095] In the embodiments described above, examples were shown in which the tractor 1 executes each process in the flowchart, but the entity that executes each process is not limited. Some or all of the processes in the flowchart may be executed by the management server 2 or the terminal device 3.

[0096] The embodiments disclosed herein should be considered in all respects to be illustrative and not restrictive. The technical features described in each embodiment can be combined with each other, and the scope of the present invention is intended to include all modifications within the claims and equivalents thereof. The sequences shown in each embodiment are not limiting, and within the bounds of consistency, the order of each processing step may be changed, and multiple processes may be executed in parallel. The processing entity for each process is not limiting, and within the bounds of consistency, the processing of each device may be executed by other devices.

[0097] The matters described in each embodiment can be combined with each other. Furthermore, the independent and dependent claims described in the claims can be combined with each other in any combination, regardless of the form of reference. In addition, the claims use a form in which claims referencing two or more other claims (multi-claim form), but are not limited to this. A form in which multi-claims referencing at least one multi-claim (multi-multi-claim) may also be used. [Explanation of Symbols]

[0098] 100 Agricultural work support systems 1. Tractor (agricultural machinery) 11 Control Unit 12 Storage section 13 Communications Department 14 Output section 15 Control section 16. Voice input section 17. Sensor Unit 18 Drive unit 121 Language Processing Models 1P Program 1A Recording medium 2 Management Server 3 Terminal devices 4. Work equipment

Claims

1. We obtain user inquiries regarding agricultural machinery. Generate a solution to the aforementioned question obtained, Output the generated solution. A computer program that instructs a computer to perform a process.

2. The solution is generated by inputting the received question into a language processing model that has been trained to output a solution to a question when a question about agricultural machinery is input. The computer program according to claim 1.

3. We acquire operating information for agricultural machinery. The solution is generated by inputting the acquired operating information and the received question into a language processing model that has been trained to output solutions to questions and operating information when questions and operating information regarding agricultural machinery are input. The computer program according to claim 2.

4. We obtain growth information of crops grown using agricultural machinery, By inputting the acquired growth information and the received question into the language processing model, which has been trained to output solutions to questions and growth information when questions and growth information regarding agricultural machinery are input, the solution is output. The computer program according to claim 2.

5. By inputting the received question into the language processing model, which has been trained to output solutions to questions related to agricultural machinery, multiple solutions are output in a stepwise manner. The computer program according to claim 2.

6. If a solution that meets the specified requirements cannot be output, contact information for contacting an operator will be output. The computer program according to claim 1 or claim 2.

7. The aforementioned solution includes control information relating to the agricultural machine, including the drive unit. When permission to execute the control information is obtained from the user, the drive unit of the agricultural machine is controlled according to the control information. The computer program according to claim 1 or claim 2.

8. The solution includes control information relating to the implement attached to the agricultural machine, When permission to execute the control information is obtained from the user, the operation of the work machine is controlled according to the control information. The computer program according to claim 1 or claim 2.

9. The aforementioned solution includes a method for operating the agricultural machinery, Outputs guidance information indicating the operating part corresponding to the aforementioned operating method. The computer program according to claim 1 or claim 2.

10. Determine whether the terminal device used by the user and the agricultural machine are already paired. If it is determined that the terminal device and the agricultural machine are not paired, a predetermined warning process will be performed. The computer program according to claim 1 or claim 2.

11. We obtain user inquiries regarding agricultural machinery. Generate a solution to the aforementioned question obtained, Output the generated solution. An information processing method in which a computer performs the processing.

12. We obtain user inquiries regarding agricultural machinery. Generate a solution to the aforementioned question obtained, Output the generated solution. An agricultural machine equipped with a control unit that performs processing.

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