Agricultural support system

Abstract

We provide an agricultural support system that can collect information on plant growth. [Solution] According to one aspect of the present invention, an agricultural support system is provided, comprising a processor, the processor being configured to perform the following steps by reading a program, the map display control step of displaying a polygon map including polygons indicating plant habitats and communication information associated with the polygons, wherein the communication information is information indicating consultation regarding plant growth in the habitat indicated by the associated polygons.

Description

Technical Field

[0001] The present invention relates to an agricultural support system.

Background Art

[0002] As disclosed in the following documents, an apparatus for predicting disorders (pests and physiological disorders) occurring in plants (crops) using a learning model is known.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Although the above apparatus can obtain a prediction of the occurrence of disorders, it cannot acquire information regarding countermeasures against the disorders.

[0005] [[ID=(38]] In view of the above circumstances, the present invention aims to provide an agricultural support system capable of collecting information regarding the growth of plants.

Means for Solving the Problems

[0006] According to one aspect of the present invention, there is provided an agricultural support system including a processor configured to execute the following steps by reading a program. In a map display control step, a polygon map including a polygon indicating a growth area of plants and communication information associated with the polygon is displayed, and the communication information is information indicating consultations regarding the growth of plants in the growth area indicated by the associated polygon.

[0007] According to such an aspect, a user can relatively easily collect information regarding the growth of plants. [Brief explanation of the drawing]

[0008] [Figure 1] This is a diagram illustrating the configuration of agricultural support system 1. [Figure 2] This is a block diagram showing the hardware configuration of the information processing device 2. [Figure 3] This is a block diagram showing the hardware configuration of user terminal 3 and respondent terminal 4 (primary respondent terminal 4A). [Figure 4] This block diagram shows the functions realized by the information processing device 2 (processor 23). [Figure 5] This diagram shows an example of the organizational structure to which the respondent belongs. [Figure 6] This figure shows an example of a forecast value display screen FD that is displayed on user terminal 3 or respondent terminal 4. [Figure 7] This figure shows an example of the first map display screen MD1 displayed on user terminal 3 or respondent terminal 4. [Figure 8] This figure shows an example of the second map display screen MD2 displayed on user terminal 3 or respondent terminal 4. [Figure 9] This is an activity diagram showing the flow of information processing (consultation response processing) performed by agricultural support system 1. [Figure 10] This is an activity diagram showing the flow of information processing (forecast value display processing) performed by agricultural support system 1. [Figure 11] This is an activity diagram showing the flow of information processing (fault prediction processing) performed by agricultural support system 1. [Modes for carrying out the invention]

[0009] Embodiments of the present invention will be described below with reference to the drawings. The various features shown in the embodiments below can be combined with each other.

[0010] Incidentally, the program for implementing the software appearing in one embodiment may be provided as a non-transitory computer-readable medium, or it may be provided as a downloadable medium from an external server, or it may be provided so that the program is launched on an external computer and its functions are realized on a client terminal (so-called cloud computing).

[0011] Furthermore, in various information processing according to one embodiment, an input and an output corresponding to the input can be realized. Here, as long as an output is obtained as a result of the input, the form of the information referenced in such information processing (hereinafter referred to as "reference information") is not limited. The reference information may be, for example, rule-based information such as a database, a lookup table, or a predetermined function (including a decision formula such as a regression equation constructed by a statistical method), or a pre-trained model that has learned the correlation between input and output in advance, or a large-scale language model that can output a desired result by inputting a prompt.

[0012] Furthermore, in one embodiment, "part" may include, for example, hardware resources implemented by a circuit in a broad sense, and the information processing of software that can be specifically realized by these hardware resources. Also, in one embodiment, various types of information are handled, and this information can be represented, for example, by the physical values ​​of signal values ​​representing voltage and current, the high or low values ​​of signal values ​​as a set of binary bits composed of 0s or 1s, or by quantum superposition (so-called qubits), and communication and calculations can be performed on a circuit in a broad sense.

[0013] Furthermore, a circuit in a broad sense is a circuit realized by appropriately combining at least a circuit, circuitry, a processor, a memory, etc. The processor may be a general-purpose processor or a dedicated circuit. That is, it includes an application specific integrated circuit (ASIC), a programmable logic device (for example, a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)), etc.

[0014] 1. Hardware Configuration In this section, the hardware configuration will be described.

[0015] <Agricultural Support System 1> FIG. 1 is a configuration diagram showing the agricultural support system 1. The agricultural support system 1 provides services for a plurality of users, such as responding to consultations regarding the growth of plants (mainly agricultural crops), forecasting the occurrence of disasters, diagnosing disasters, etc.

[0016] The agricultural support system 1 includes an information processing device 2, a user terminal 3, and a responder terminal 4 (primary responder terminal 4A and secondary responder terminal 4B). The information processing device 2, the user terminal 3, and the responder terminal 4 are configured to be communicable through a telecommunication line.

[0017] In one embodiment of the agricultural support system 1, the agricultural support system 1 consists of one or more devices or components. For example, if the agricultural support system 1 consists only of the information processing device 2, the agricultural support system 1 can be the information processing device 2. Hereinafter, these components will be described.

[0018] <Information Processing Device 2> Figure 2 is a block diagram showing the hardware configuration of the information processing device 2. The information processing device 2 comprises a communication bus 20, a communication unit 21, a storage unit 22, and a processor 23. The communication unit 21, the storage unit 22, and the processor 23 are electrically connected within the information processing device 2 via the communication bus 20.

[0019] <Communications Department 21> The communication unit 21 preferably uses wired communication methods such as USB, IEEE1394, Thunderbolt®, and wired LAN network communication, but may also include wireless LAN network communication, mobile communication such as LTE / 5G, and Bluetooth® communication as needed. In other words, it is more preferable to implement it as a collection of these multiple communication methods. That is, the information processing device 2 may communicate various information from the outside via the communication unit 21 and the network.

[0020] <Storage section 22> The storage unit 22 stores various types of information as defined above. This can be implemented, for example, as a storage device such as a solid-state drive (SSD) that stores various programs related to the information processing device 2 executed by the processor 23, or as memory such as random access memory (RAM) that stores temporarily necessary information (arguments, arrays, etc.) related to program calculations. The storage unit 22 stores various programs, variables, etc. related to the information processing device 2 executed by the processor 23.

[0021] <Processor 23> The processor 23 performs processing and control of the overall operation related to the information processing device 2. The processor 23 is, for example, a Central Processing Unit (CPU). The processor 23 realizes various functions related to the information processing device 2 by reading predetermined programs stored in the memory unit 22. That is, information processing by software stored in the memory unit 22 can be concretely realized by the processor 23, which is an example of hardware, and executed as each functional unit included in the processor 23. These will be described in more detail in the next section. Note that the processor 23 is not limited to being a single unit; the information processing device 2 may have multiple processors 23 for each function. Furthermore, the information processing device 2 may have a configuration that combines these.

[0022] The information processing device 2 may be on-premise or in a cloud-based configuration. In the case of a cloud-based information processing device 2, for example, the above-mentioned functions and processing may be provided in the form of SaaS (Software as a Service) or cloud computing.

[0023] <User Terminal 3> Figure 3 is a block diagram showing the hardware configuration of the user terminal 3 and the respondent terminal 4 (primary respondent terminal 4A). As shown in Figure 3A, the user terminal 3 comprises a communication bus 30, a communication unit 31, a storage unit 32, a processor 33, an output unit 34, and an input unit 35. The communication unit 31, storage unit 32, processor 33, output unit 34, and input unit 35 are electrically connected within the user terminal 3 via the communication bus 30. The explanation of the communication unit 31, storage unit 32, and processor 33 is the same as the explanation of each part in the information processing device 2 and is therefore omitted.

[0024] <Output section 34> The output unit 34 displays a graphical user interface (GUI) screen that can be operated by the user. The output unit 34 may be included in the casing of the user terminal 3 or it may be an external component. Specifically, the output unit 34 can be implemented as a display device such as a CRT display, liquid crystal display, organic EL display, or plasma display. It is preferable that these display devices be used according to the type of user terminal 3.

[0025] <Input section 35> The input unit 35 receives operation input from the user. The operation input is transmitted to the processor 33 via the communication bus 30 as a command signal. The processor 33 can perform predetermined controls or calculations based on the transmitted command signal as needed. The input unit 35 may be included in the casing of the user terminal 3 or it may be external. For example, the input unit 35 may be implemented as a touch panel in conjunction with the output unit 34. When the input unit 35 is implemented as a touch panel, the user can input tap operations, swipe operations, etc. to the input unit 35. Instead of a touch panel, the input unit 35 can be a switch button, mouse, trackpad, QWERTY keyboard, etc.

[0026] <Respondent's device 4> As shown in Figure 3B, the primary respondent terminal 4A comprises a communication bus 40, a communication unit 41, a storage unit 42, a processor 43, an output unit 44, and an input unit 45. The communication unit 41, storage unit 42, processor 43, output unit 44, and input unit 45 are electrically connected within the primary respondent terminal 4A via the communication bus 40. The descriptions of the communication unit 41, storage unit 42, processor 43, output unit 44, and input unit 45 are the same as those for the user terminal 3 and are therefore omitted. The hardware configuration of the secondary respondent terminal 4B is the same as that of the primary respondent terminal 4A.

[0027] 2. Functional Configuration This section describes the functional configuration of this embodiment. Information processing by software stored in the memory unit 22 is specifically realized by the processor 23, which is an example of hardware, and can be executed as each functional unit included in the processor 23.

[0028] Figure 4 is a block diagram showing the functions realized by the information processing device 2 (processor 23). Specifically, the information processing device 2 (processor 23) includes a registration unit 231, a consultation reception unit 232, a response reception unit 233, a forecast unit 234, a forecast value display control unit 235, a map display control unit 236, an image acquisition unit 237, a fault prediction unit 238, a point management unit 239, and an artificial intelligence unit 240.

[0029] <Registration Section 231> The registration unit 231 registers users who will use the user terminal 3. Users are, for example, farmers or employees of organizations (farms or companies) that manage farms. The registration unit 231 registers user data, including the user's personal information (name, address, contact information, affiliated organization, etc.), as well as the user ID, the type of plant (crop) being cultivated, and the managed growing area (address of the field), in a user database stored, for example, in the storage unit 22. For users with multiple growing areas, the registration unit 231 registers the addresses of all of those growing areas. Furthermore, if a user is a farmer or an employee of a company, one growing area may be shared by multiple users in the user data.

[0030] The registration unit 231 also registers respondents who use the respondent terminal 4. Respondents are agricultural advisors and include, for example, employees of agricultural cooperatives (e.g., JA: Japan Agricultural Co-operatives), local government agricultural officials, and employees of material companies such as pesticide manufacturers. The registration unit 231 registers respondent data, including the respondent's personal information (name, affiliated organization, contact information, etc.) and respondent ID, into a respondent database stored, for example, in the storage unit 22.

[0031] <Consultation Desk 232> The consultation reception unit 232 is configured to receive consultations from the user terminal 3 regarding the growth of plants in a designated growing area. Specifically, the consultation reception unit 232 accepts input (upload) from the user terminal 3 of matters that the user wants to consult with a respondent (instructor) for each growing area managed by the user. The consultation reception unit 232 links the consultation content received from the user terminal 3 with the user and the growing area and registers it in a consultation database stored, for example, in the storage unit 22.

[0032] The consultation department 232 accepts consultations that include, for example, the determination (diagnosis) of plant disorders (diseases, pests, and physiological disorders), and measures against disorders or pests. The consultation information entered by the user into the user terminal 3 includes, for example, images of the plant in question, text describing the type of plant, its condition, symptoms, numerical values, symbols, etc.

[0033] For example, the user selects a respondent (primary respondent) from the list of respondent candidates (instructors) presented on the user terminal 3 and inputs the consultation request. The candidate respondents are extracted by the consultation reception unit 232 from the respondents registered in the respondent database according to the location of the animal being consulted (the location registered by the user). Alternatively, the consultation reception unit 232 may automatically select a respondent according to the location without accepting a response selection from the user terminal 3.

[0034] Furthermore, the consultation reception unit 232 may accept consultations directed not to the respondent (instructor), but to another user (for example, an employee, manager, or owner of the same farm). In this case, the user terminal 3 will select a different user as the person to consult. By enabling consultations directed to other users in this way, it becomes possible to visualize the occurrence of problems within the farm, accumulate a history of problems, strengthen farm monitoring, and provide employee training.

[0035] <Response Reception Department 233> The response receiving unit 233 is configured to forward the consultation received by the consultation receiving unit 232 to the respondent (primary respondent or secondary respondent) registered in the respondent database and to receive responses from the respondent. The response receiving unit 233 links the received response content to the respondent and the consultation content and registers it in the consultation database. As a result, the response content is stored linked not only to the respondent and the consultation content, but also to the user who made the consultation (consultant) and their place of origin.

[0036] The response receiving unit 233 transmits to the respondent terminal 4 (primary respondent terminal 4A or secondary respondent terminal 4B) the image for consultation uploaded from the user terminal 3, diagnostic information held by the information processing device 2 (for example, the predicted value of the occurrence of the malfunction described later, the status of the malfunction inferred from the image), etc.

[0037] The response to the consultation includes information such as the diagnosis of the problem and countermeasures (type of pesticide to use, timing, etc.). The respondent inputs this information on the respondent terminal 4. The response receiving unit 233 transmits the information received from the respondent terminal 4 to the user terminal 3 as a response to the consultation.

[0038] The response receiving unit 233 forwards the consultation to the primary respondent terminal 4A, which is selected from among the respondents assigned according to the location of the habitat that is the subject of the consultation received by the consultation receiving unit 232, and also receives the response to the consultation from the primary respondent terminal 4A. This allows for a quick resolution of the consultation, as the response to the consultation is considered by a primary respondent who has been pre-assigned to the habitat that is the subject of the consultation.

[0039] Primary respondents may be assigned, for example, based on the relationship between the area covered by the primary organization to which the primary respondent belongs (e.g., a branch of a JA) and the location of the habitat of the subject of the consultation, or they may be assigned based on the relationship between the area covered by each individual respondent and the location of the habitat.

[0040] The response receiving unit 233, when it receives a retransmission instruction from the primary respondent terminal 4A, or when it fails to receive a response from the primary respondent terminal 4A within a predetermined period, should transfer the consultation to a secondary respondent terminal 4B, which is selected from among the respondents belonging to a second organization that has a cooperative relationship with the first organization to which the primary respondent belongs, and should also receive the response from the secondary respondent terminal 4B. The second organization is a superior organization to the first organization, or an organization that has established a cooperative relationship with the first organization. This allows for backup by a secondary respondent when the primary respondent is unable to answer the consultation. Therefore, in addition to the effect of quickly resolving consultations, it is possible to ensure that appropriate answers are provided to the user's consultations.

[0041] The period before transferring the consultation to the secondary respondent can be set arbitrarily, for example, one week. In addition, the response receiving unit 233 may first notify the primary respondent terminal 4A that no response has been entered after a predetermined first period has elapsed since transferring the consultation to the primary respondent terminal 4A, and then transfer the consultation to the secondary respondent terminal 4B after a predetermined second period has elapsed since the notification.

[0042] The response receiving unit 233 may adjust the display format of the consultation on the primary respondent terminal 4A (or secondary respondent terminal 4B) according to the status of the disorder estimated by the disorder estimation unit 238, described later, using the plant images included in the consultation. This makes it possible to present consultations that should be given priority to the primary respondent, thereby facilitating the rapid resolution of urgent consultations.

[0043] For example, the response receiving unit 233 assigns a priority to each consultation according to the predicted occurrence of the problem, and displays the consultations on the primary respondent terminal 4A or secondary respondent terminal 4B in order of priority. The response receiving unit 233 may also attach a label or icon indicating the high priority to high-priority consultations, or highlight them by changing the font, coloring, etc. The priority is a numerical value representing the degree of risk of the problem. The priority may be calculated, for example, when the occurrence of the problem is predicted by the problem prediction unit 238 described later, or it may be calculated using the predicted type or degree of the problem and a table in which the risk level is defined in advance.

[0044] The habitat area covered by each respondent, and the organizational structure of the organization to which the respondent belongs (including inter-organizational relationships), are recorded, for example, in the respondent database.

[0045] The primary respondent's answers are only viewable by other respondents belonging to the first organization or the second organization, among those registered in the respondent database. Therefore, even if a respondent is registered in the respondent database, if their organization is not the same as the primary respondent's first organization, and they do not belong to the second organization, the map display control unit 236 will restrict their viewing of the primary respondent's answers (i.e., their answers will not be displayed on the terminal). This protects the user's personal information.

[0046] Furthermore, under the above conditions, access may be restricted not only to the primary respondent's answer but also to the entire consultation history including that answer. In addition, access restrictions may be set so that users other than the person who asked the question or users outside the organization (farm) to which the person who asked the question belongs cannot view the consultation history. Moreover, the conditions for access restrictions (for example, whether or not to disclose the consultation history to other users) may be set by individual users.

[0047] Figure 5 shows an example of the organizational structure to which a respondent belongs. In Figure 5, "A" through "T" each represent a single respondent (leader). Also, "U" through "Z," enclosed by dashed lines, each represent a single user (e.g., a farmer) who consults with the respondent. In the example in Figure 5, the respondent belongs to a respondent organization with a hierarchical structure consisting of a first-tier organization O1, a second-tier organization O2, a third-tier organization O31, O32, O33, and a fourth-tier organization O41, O42, O43, O44, O45.

[0048] For example, if the responding organization is the JA Group, then the fourth-tier organizations O41, O42, O43, O44, and O45 are regional JAs that each have jurisdiction over a designated region IV. The third-tier organizations O31, O32, and O33 are prefectural-level (i.e., regional) agricultural cooperative federations that have jurisdiction over a wider area than region IV, and are defined as higher-level organizations than the fourth-tier organizations O41, O42, O43, O44, and O45. The second-tier organization O2 is the National Federation of Agricultural Cooperative Associations that has jurisdiction over the entire country, and is defined as higher-level organizations than the third-tier organizations O31, O32, and O33. The first-tier organization O1 is the National Federation of Agricultural Cooperative Associations, and is defined as higher-level organizations than the second-tier organization O2.

[0049] Furthermore, in the example in Figure 5, among the fourth-tier organizations O41, O42, O43, O44, and O45, a linkage (dotted line) is established between the fourth-tier organization O42 in region II and the fourth-tier organization O43 in region III. Similarly, among the third-tier organizations O31, O32, and O33, a linkage is established between the third-tier organization O31 in prefecture α and the third-tier organization O32 in prefecture β.

[0050] In Figure 5, for example, when user X enters a consultation request, among the respondents belonging to the fourth-tier organization O43 (corresponding to the "first organization" in the processing of the response reception unit 233) in region III where the habitat managed by user X (the habitat subject to the consultation) is located, respondent P, who is in charge of that habitat, is selected as the primary respondent by the response reception unit 233, and the consultation is transferred to respondent P's terminal (primary respondent terminal 4A).

[0051] If respondent P is unable to answer the consultation themselves, they input a message indicating that they cannot answer (re-transfer of consultation) into the primary respondent terminal 4A. If the response receiving unit 233 receives a re-transfer of consultation, or if no response is input from the primary respondent within a predetermined period, it selects respondent G or respondent H belonging to the third-tier organization O32 of β prefecture (corresponding to the "second organization" in the processing of the response receiving unit 233), which is a higher-level organization of the fourth-tier organization O43 of region III, or respondent M or respondent N belonging to the fourth-tier organization O42 of region II (corresponding to the "second organization" in the processing of the response receiving unit 233), which is linked to the fourth-tier organization O43 of region III, as a secondary respondent, and transfers the consultation to the terminal of the said secondary respondent (secondary respondent terminal 4B).

[0052] If the secondary respondent is also unable to provide an answer, the response receiving unit 233 may further forward the consultation to a respondent in a higher-level organization of the second organization (in the example above, the second-tier organization O2) or an organization with which cooperation with the second organization has been established (in the example above, the third-tier organization O31 of α prefecture).

[0053] Furthermore, the response reception unit 233 may accept nominations of secondary respondents from primary respondents. In this case, the primary respondent inputs the information of the respondent to be nominated as the secondary respondent from the primary respondent terminal 4A. The nominated respondent may be a respondent belonging to the second organization (a higher organization or a collaborating organization), or a respondent belonging to an organization that does not fall under either the higher organization or a collaborating organization (respondents outside the organizational structure, such as prefectural employees, in the example in Figure 5).

[0054] The response receiving unit 233 may either directly send the response received from the secondary respondent terminal 4B to the user terminal 3 as a response from the secondary respondent, or it may forward the response received from the secondary respondent terminal 4B to the primary respondent terminal 4A. The primary respondent may either send the response forwarded to the primary respondent terminal 4A to the user terminal 3 as is, or it may edit the forwarded response and send it to the user terminal 3.

[0055] When the consultation reception unit 232 receives a consultation request from user terminal 3 for another user (for example, an employee or manager of the same farm), the response reception unit 233 forwards the consultation to the user terminal 3 of that other user. If the user who received the consultation is able to provide an answer, they input the answer themselves (for example, instructions for spraying pesticides). If they are unable to provide an answer, the user who received the consultation forwards the consultation to the respondent (instructor). The consultation reception unit 232 then receives the consultation again as a consultation to the respondent, and the response reception unit 233 forwards the consultation to the primary respondent terminal 4A.

[0056] <Forecast Section 234> The forecasting unit 234 is configured to forecast the likelihood of damage occurring to plants. Specifically, the forecasting unit 234 estimates a forecast value indicating the likelihood of damage based on forecasting conditions including the predicted date and time, plant type, plant growing area, etc., and first reference information.

[0057] The disorders for which the forecasting unit 234 estimates forecast values ​​include diseases, pests, and physiological disorders. Physiological disorders include deficiencies of components such as magnesium and calcium, and water shortages. The forecasting unit 234 also predicts the likelihood of a disorder occurring (i.e., the forecast value) for each "type of disorder" for each "type of plant." "Types of plants" are, for example, varieties of strawberries, radishes, onions, broccoli, cabbage, etc. Furthermore, "types of plants" may be subdivided by subcategories such as varieties of onions, such as "Sonic" and "Neo Earth," and harvest days, such as "early-maturing" and "mid-season." "Types of disorders" are, for example, disease names such as sooty mold and black rot, pest names such as armyworms and aphids, or the names of physiological diseases such as magnesium deficiency and water shortages.

[0058] The first reference information includes the correlation between forecast conditions and the forecast values ​​for each failure, and is stored, for example, in the memory unit 22. The first reference information may also include, for example, a table, a function, a simple algorithm, etc., that shows the correlation between features extracted from the forecast conditions and the forecast values. The correlations included in the first reference information can be constructed, for example, by statistically analyzing data recorded by combining actual failures with the conditions for occurrence. The first reference information may also include a prediction value estimation model (artificial intelligence) that has been pre-machine-trained. The prediction value estimation model is included in the artificial intelligence unit 240.

[0059] The prediction value estimation model is trained to take forecast conditions as input and output forecast values. When using such a prediction value estimation model, the forecasting unit 234 inputs the type of plant to be predicted, the region, and the date and time (including future dates and times) into the prediction value estimation model, and causes the prediction value estimation model to output at least one possible disorder and the probability (forecast value) of each of the at least one disorder occurring. The forecasting unit 234 may also input forecast conditions including weather forecast values ​​(weather, atmospheric pressure, temperature, humidity, etc.) for the region where the forecast values ​​are to be output into the prediction value estimation model.

[0060] The forecast value estimation model used by the forecasting unit 234 is constructed using machine learning, for example, with training data that associates the types of plants that have suffered damage in the past, the types of damage that occurred, the regions where the affected plants grew, and the date and time the damage occurred. Furthermore, when weather forecast values ​​are used as forecasting conditions, in addition to the aforementioned plant types, types of damage, regions, and date and time of occurrence, records that associate the weather conditions (weather, atmospheric pressure, temperature, humidity, etc.) at the time of the damage are used as training data. In the forecast value estimation power model, the parameters calculated and tuned through learning constitute the correlation of the first reference information.

[0061] The forecast values ​​predicted by the forecasting unit 234 are linked to input conditions (plant type, region, date and time, weather forecast values, etc.) and stored, for example, in the forecast value database of the storage unit 22.

[0062] The forecasting unit 234 may output a notification (e.g., a push notification) to the user terminal 3 or respondent terminal 4 at a predetermined timing if the forecast value is above a predetermined threshold. The threshold is set, for example, as a percentage of the maximum forecast value (e.g., 80%). The timing for outputting the notification is, for example, the day of or the day before the date on which a forecast value above the threshold was predicted. The forecasting unit 234 may also output a notification if the forecast value is above the threshold for a specific number of consecutive days. The specific number of days is, for example, two days. The threshold, notification timing, specific number of days, and other conditions may differ depending on the type of hazard, the type of plant, etc.

[0063] <Forecast value display control unit 235> The forecast value display control unit 235 is configured to display the forecast values ​​predicted by the forecast unit 234 on the user terminal 3 or the respondent terminal 4. Specifically, the forecast value display control unit 235 displays time-series data on the user terminal 3 or the respondent terminal 4, which includes forecast values ​​indicating the possibility of plant damage occurring at each of several forecast points from the present time onward, and the annual values ​​of the forecast values ​​for each of the multiple forecast points. This allows for the proactive implementation of countermeasures against plant damage based on future forecast values.

[0064] The forecast time points for which the forecast value display control unit 235 displays the forecast value are typically future dates and times, but may include the current time. Multiple forecast time points are set at equal intervals, for example, one day apart. The range of forecast time points displayed by the forecast value display control unit 235 is, for example, one week, but may be longer than one week depending on the forecast value estimation model used by the forecast unit 234, the accuracy of the weather forecast, etc. The forecast value display control unit 235 causes the forecast unit 234 to predict the forecast values ​​for multiple forecast time points.

[0065] The "annual value" is the average of the forecast values ​​for the same plant, the same region, and the same date and time for each year (e.g., 5 years) that were predicted by the forecasting unit 234 in the past, as stored in the forecast value database. The time series data displayed by the forecast value display control unit 235 is generated for each plant type and region. That is, all the forecast values ​​included in a single time series data set are for the same plant and the same region. The time series data displayed on the user terminal 3 or respondent terminal 4 may be numerical values ​​or graphical representations such as graphs.

[0066] The forecast value display control unit 235 should display a comparison between a figure showing the magnitude of the forecast value and a figure showing the magnitude of the average value for each of the multiple forecast time points of the time series data. This makes it possible to grasp in advance the magnitude of the risk of future malfunctions.

[0067] Furthermore, the forecast value display control unit 235 may output a notification to the user terminal 3 or respondent terminal 4 if the value obtained by subtracting the average value from the forecast value is equal to or greater than a predetermined threshold. This allows the user to take early action to suppress the occurrence of failures. The threshold may be a fixed value or a percentage of the average value (for example, 10% of the average value).

[0068] The forecast value display control unit 235 may display information on the user terminal 3 or respondent terminal 4 indicating whether the forecast value is higher or lower than the average value. This allows the user to understand the degree of risk of damage compared to previous years.

[0069] Figure 6 shows an example of a forecast value display screen FD displayed on user terminal 3 or respondent terminal 4. The forecast value display screen FD displays forecast values ​​for the cultivation area selected by the user. The forecast value display screen FD includes a plant selection area SA and multiple forecast value display areas FA. The plant selection area SA displays multiple plant selection buttons B11 for selecting plants (crops). When any of the plant selection buttons B11 are selected by pressing the input unit 35 of user terminal 3, the forecast values ​​for potential problems that may occur in the selected plant are displayed in each forecast value display area FA.

[0070] The forecast value display area FA is the area where forecast values ​​are displayed for each type of fault. Specifically, the forecast value display area FA displays the fault name FN, fault image FI, first forecast value bar FB1, second forecast value bar FB2, risk graph DG, incident report button B12, and countermeasure input button B13.

[0071] The first forecast value bar FB1 is an object that shows the magnitude of the forecast value (probability of occurrence of a problem) for each day from the present (today) to a predetermined period (6 days from now), as predicted by the forecasting unit 234. The first forecast value bar FB1 may change color according to the magnitude of the forecast value. For example, the first forecast value bar FB1 may be colored such that it approaches green as the forecast value is small and approaches red as the forecast value is high.

[0072] The second forecast value bar FB2 is an object that shows the magnitude of the annual value of the forecast for the date on which the first forecast value bar FB1 is displayed. In the example in Figure 6, the second forecast value bar FB2 is positioned behind the first forecast value bar FB1 for the corresponding date, with a portion overlapping.

[0073] The Danger Graph DG is an object that shows the magnitude of the average value of the first forecast value bar FB1 displayed in the forecast value display area FA (the average value of the forecast values ​​for one week). The Danger Graph DG consists of a combination of a bar that shows the magnitude of the forecast value and text that shows the degree of danger (alert level) (for example, "Alert," "Be careful," "Observe," etc.).

[0074] The occurrence report button B12 is an object that accepts input from the user to report the occurrence of a problem when the occurrence of a problem displayed in the forecast value display area FA is observed in the user's growing area. When the input unit 35 of the user terminal 3 performs an input operation on the occurrence report button B12, the forecast value display control unit 235 registers occurrence information, including the type of plant, the type of problem, the date of occurrence of the problem, and user information (growing area), for example, in the problem record database of the storage unit 22. This occurrence information is referenced as an occurrence history from the user terminal 3 or the respondent terminal 4 as appropriate, and is also used as training data for the prediction value estimation model used by the forecast unit 234.

[0075] The countermeasure input button B13 is an object that accepts input from the user to report the implementation of a countermeasure (e.g., spraying pesticides) when the user has taken action against a problem displayed in the forecast value display area FA. When an input operation is performed on the countermeasure input button B13, for example, the forecast value display control unit 235 displays a screen on the user terminal 3 that accepts input of details of the countermeasure (e.g., type of pesticide, area where it was sprayed, spraying date, etc.). The information entered on this screen is linked to the type of plant, the type of problem, etc., and registered in the problem record database as countermeasure implementation information. This countermeasure implementation information is referred to as appropriate as a response history from the user terminal 3 or the respondent terminal 4.

[0076] The forecast value display control unit 235 may, as a notification when the value obtained by subtracting the average value from the forecast value (the difference between the first forecast value bar FB1 and the second forecast value bar FB2) is greater than or equal to a predetermined threshold, display a text message or icon on the forecast value display screen FD (specifically, the forecast value display area FA), or it may highlight the corresponding first forecast value bar FB1 by changing its color, shape, etc.

[0077] The forecast value display control unit 235, for example, in response to a display request from the user, causes the user terminal 3 to display time-series data of forecast values. Furthermore, when the response receiving unit 233 transfers a consultation to the respondent terminal 4, the forecast value display control unit 235 displays, for example, time-series data of forecast values ​​for plants related to the consultation, along with images and consultation content transmitted from the user terminal 3, on the respondent terminal 4. Note that the forecast value display screen FD displayed on the user terminal 3 and the forecast value display screen FD displayed on the respondent terminal 4 do not necessarily have the same configuration. For example, the forecast value display screen FD displayed on the respondent terminal 4 does not need to include the occurrence report button B12 and the countermeasure input button B13.

[0078] <Map display control unit 236> The map display control unit 236 is configured to display a map containing various information about plant damage on the user terminal 3 or the respondent terminal 4.

[0079] Specifically, the map display control unit 236 displays a polygon map on the user terminal 3 or respondent terminal 4, which includes polygons indicating plant habitats and communication information associated with those polygons. The "communication information" is information indicating consultations regarding plant growth in the habitat indicated by the associated polygon (consultations received by the consultation reception unit 232). This allows the user to check the history of past problems, countermeasures, etc., by referring to the communication information of nearby habitats (polygons) on the polygon map.

[0080] A polygon is a figure that reflects the shape of a habitat on a map. The map display control unit 236 generates a polygon map using, for example, map data and habitat data. The map data and habitat data may be stored in the storage unit 22, or they may be obtained from a database stored on a server outside the information processing device 2. The habitat data includes information such as the location (address), shape, and area of ​​the habitat (cultivated land such as rice paddies and fields).

[0081] The communication information included in the polygon map also includes information about consultations conducted by other users, not just the user viewing the polygon map. Typically, the polygon map includes communication information about consultations from all users who have made their consultation content public, and this communication information is displayed on each user's user terminal 3.

[0082] The map display control unit 236 may display information on the polygon map indicating whether a consultation has been resolved or not. This allows the user to refer to communication information only for resolved or unresolved consultations, thereby improving the efficiency of information collection. The information indicating whether a consultation has been resolved or not may be included in the communication information (displayed as communication information) or displayed separately from the communication information.

[0083] Furthermore, the map display control unit 236 accepts the selection of communication information in the polygon map and displays a history of the consultations indicated by the selected communication information (consultations received by the consultation reception unit 232) and the answers to those consultations (answers received by the answer reception unit 233). This allows the user to refer to the consultation history of other users in habitats close to their own habitat and collect information about potential problems and countermeasures for those problems.

[0084] Communication information (history) is labeled according to the type of obstacle and / or the type of plant. The map display control unit 236 receives requests from the user terminal 3 or respondent terminal 4 for sorting by obstacle type or plant type, switching between displaying and not displaying, searching, etc.

[0085] The map display control unit 236 may further display the cultivation history, which includes at least one of the plant's growth status and management work history, in the growing area indicated by the polygon associated with the selected communication information. This allows the user to refer to the plant's cultivation history along with past consultation history, enabling the user to collect more information. The "growth status" includes whether or not a problem occurred, the type of problem that occurred, and the timing of the problem. The "management work history" includes pesticide application history, fertilization history, sowing time, planting time, etc. The pesticide application history includes the type of pesticide, the timing of application, and the number of applications. The fertilization history includes the type of fertilizer, the timing of fertilization, and the number of applications.

[0086] The map display control unit 236 may further display the occurrence status of the problem inferred by the problem prediction unit 238 (described later) from the plant images included in the consultation indicated by the selected communication information (images acquired by the image acquisition unit 237, described later). This allows the user to refer to the occurrence status of the problem along with the past consultation history, thereby enabling the user to collect more information.

[0087] Figure 7 shows an example of the first map display screen MD1 displayed on user terminal 3 or respondent terminal 4. The first map display screen MD1 includes a polygon map display area PA and a communication display area CA.

[0088] The polygon map display area PA displays a polygon map that includes habitat polygons HP, a first communication icon CI1, and a second communication icon CI2. The polygon map in Figure 7 is created by overlaying habitat polygons HP onto general map data, and further assigning either the first communication icon CI1 or the second communication icon CI2 to a predetermined habitat polygon HP.

[0089] The first communication icon CI1 is an example of communication information indicating that there are resolved inquiries in the habitat indicated by the assigned habitat polygon HP. The second communication icon CI2 is an example of communication information indicating that there are unresolved inquiries in the habitat indicated by the assigned habitat polygon HP.

[0090] Communication information included in the polygon map may be represented by the color of each habitat polygon HP. For example, habitat polygon HPs with resolved consultations may be colored green, and habitat polygon HPs with unresolved consultations may be colored red. Such coloring of habitat polygon HPs may be used in conjunction with communication icons. Also, habitat polygon HPs corresponding to habitats with no consultations do not need to be displayed (colored) in the polygon map. Furthermore, as a communication icon attached to the habitat polygon HP, an icon indicating the type (category) of the problem being consulted (for example, a virus icon for diseases, an insect icon for pests, a boar icon for vermin, etc.) may be displayed.

[0091] In the polygon map display area PA, when an input operation is performed from user terminal 3 or respondent terminal 4 on a habitat polygon HP to which communication information (first communication icon CI1 or second communication icon CI2) is attached, or on the communication icon itself, the history of the consultation indicated by the selected communication information is displayed in the communication display area CA.

[0092] The communication display area CA includes the disability name FN, disability image FI, consultant information CI, consultation message CM, respondent information AI, and response message AM. The disability name FN includes the disability name and plant name, which are extracted from the consultation content or response content. The disability image FI is selected from a pre-prepared set of images corresponding to the extracted disability name. The consultant information CI is information about the user who submitted the consultation. The consultation message CM is the consultation content sent by the user. The consultation message CM may also include non-text information such as images. The respondent information AI is information about the respondent (instructor) who submitted the response. The response message AM is the response content sent by the respondent. The response message AM may also include non-text information such as images.

[0093] The map display control unit 236 may display an object (for example, a "Purchase Pesticides" button) in the communication display area CA displayed on the user terminal 3 that accepts the purchase of pesticides included in the respondent's answer. When the user terminal 3 makes an input operation on the object for purchasing pesticides, the map display control unit 236 may, for example, display a link (URL) to a pesticide purchase site (EC site), or transition the display screen of the user terminal 3 to the purchase site. Alternatively, the map display control unit 236 may directly accept the purchase of pesticides through an input operation on the object for purchasing pesticides.

[0094] The communication information contained in the polygon map is not limited to information indicating consultations received by the consultation reception unit 232, but may also include information regarding consultations obtained from external services other than those provided by the agricultural support system 1, or from external servers other than the information processing device 2.

[0095] Furthermore, the polygon map may include information indicating the magnitude of the forecast values ​​predicted by the forecasting unit 234. For example, the map display control unit 236 may overlay a layer (heatmap) on the polygon map that color-codes areas on the map according to the magnitude of the forecast values. The forecast value heatmap may, for example, be color-coded for each section divided into mesh units for which forecast values ​​are predicted. The map display control unit 236 may also display the forecast value heatmap independently of the polygon map on the user terminal 3 or the respondent terminal 4. Furthermore, the independent heatmap may include communication information common to both the polygon map and the heatmap. Heatmaps are generated for each type of hazard and each type of plant.

[0096] Figure 8 shows an example of the second map display screen MD2 displayed on user terminal 3 or respondent terminal 4. The second map display screen MD2 includes a heatmap display area HA and a communication display area CA. The communication display area CA is the same as that of the first map display screen MD1.

[0097] The heatmap display area HA shows a heatmap that includes the first communication icon CI1 and the second communication icon CI2. The heatmap in Figure 8 divides general map data into multiple sections and colors each section according to the magnitude of the forecast value. Areas with small forecast values ​​are colorless, and as the forecast value increases, the color of the section becomes darker (or approaches red). In the example in Figure 8, the lower right section contains the occurrence prediction area OA, where the forecast value is large (high probability of trouble occurring). The lines drawn in the heatmap display area HA represent roads on the map.

[0098] The first communication icon CI1 and the second communication icon CI2 displayed in the heatmap display area HA are the same as those in the first map display screen MD1. However, in the second map display screen MD2, the communication icons are not associated with polygons indicating habitats, but are placed at the location on the map of the habitat where the consultation occurred.

[0099] <Image acquisition unit 237> The image acquisition unit 237 is configured to acquire inference images, including plants, from the user terminal 3. The inference image is, for example, an image taken by the camera of the user terminal 3, which includes at least the affected part of the plant to be diseased. The image acquisition unit 237 may also acquire plant images included in consultations received by the consultation reception unit 232.

[0100] <Disability Prediction Section 238> The damage prediction unit 238 is configured to predict the occurrence of damage in plants included in the prediction image, based on prediction information including at least the prediction image acquired by the image acquisition unit 237, the predicted value at the time the prediction image was acquired as predicted by the forecasting unit 234, and second reference information. This allows for the prediction of damage using the predicted value, which represents the probability of damage occurring, thereby improving the accuracy of damage prediction based on plant images.

[0101] The second reference information includes the correlation between the inference information and predicted values ​​and the occurrence of the problem, and is stored, for example, in the memory unit 22. The inference information includes, in addition to the inference image, for example, the acquisition date, acquisition location, and plant type of the inference image. The second reference information may also include, for example, a table, function, simple algorithm, etc., that shows the correlation between the features (e.g., vector data) and predicted values ​​extracted from the inference information (typically the propulsion image) and the occurrence of the problem. The correlations included in the second reference information can be constructed, for example, by statistically analyzing data recorded by combining the plant image, occurrence date, occurrence location, plant type, and predicted value for actual problems. Furthermore, the second reference information may also include a problem prediction model (artificial intelligence) that has been pre-machine-trained. The problem prediction model is included in the artificial intelligence unit 240.

[0102] The fault prediction model includes a first form that takes prediction information as input and outputs the fault occurrence status, a second form that takes prediction information and forecast values ​​as input and outputs the fault occurrence status, and a third form that takes prediction information as input and outputs the likelihood of fault occurrence. When using the first form of the prediction value prediction model, the forecast values ​​are used as judgment information to determine whether or not to perform prediction using the fault prediction model.

[0103] When the first form of the damage prediction model is used, the second reference information includes a lower limit of the predicted value for determining whether or not damage has occurred, and a damage prediction model that has been trained to take prediction information, including a prediction image, as input and output the type of damage. The damage prediction unit 238 predicts that no damage has occurred to the plants included in the prediction image if the predicted value is below the lower limit included in the second reference information, and if the predicted value is above the lower limit, it inputs the prediction information, including the prediction image, into the damage prediction model to predict the type of damage occurring to the plants included in the prediction image. As a result, when there is a high probability of damage occurring (when the predicted value is above the lower limit), the damage prediction model can perform highly accurate predictions. Furthermore, when there is a low probability of damage occurring (when the predicted value is below the lower limit), processing by the damage prediction model is skipped, thereby reducing the processing load on the processor 23.

[0104] When the second form of damage prediction model is used, the second reference information includes a damage prediction model that has been trained to take prediction information and forecast values ​​as inputs and output the type of damage. The damage prediction unit 238 inputs the prediction information and forecast values ​​into the damage prediction model to predict the type of damage occurring to the plants included in the prediction image.

[0105] When the third form of fault prediction model is used, the second reference information includes a determination threshold and a fault prediction model that has been trained to take prediction information, including prediction images, as input and output the probability of multiple faults occurring. For each fault, the fault prediction unit 238 predicts that the fault has occurred if the product of the probability of occurrence output by the fault prediction model and the predicted value is equal to or greater than the determination threshold.

[0106] The first and third forms of damage prediction models are constructed using machine learning, for example, with training data that associates images of affected parts of plants that have previously experienced damage, the type of damage that occurred, the region where the affected plants grew, and the date and time the damage occurred. The second form of damage prediction model is constructed using machine learning, with training data that, in addition to the same affected part images, type of damage, region, and date and time of occurrence as the first form, further associates records with predicted values ​​at the time of damage occurrence. In these damage prediction models, the parameters calculated and tuned through learning constitute the correlation of the second reference information.

[0107] The damage prediction unit 238 may predict the occurrence of damage to plants included in plant images based on prediction information, which includes at least plant images included in the consultation received by the consultation reception unit 232, and third reference information. The third reference information includes the correlation between the prediction information and the occurrence of damage, and is stored, for example, in the storage unit 22. In addition to plant images, the prediction information includes, for example, the acquisition date, acquisition location, and plant type of the plant image. The third reference information may also include, for example, tables, functions, simple algorithms, etc., that show the correlation between feature quantities (e.g., vector data) and predicted values ​​extracted from the prediction information (typically plant images) and the occurrence of damage. The correlations included in the third reference information can be constructed, for example, by statistically analyzing data recorded by combining plant images, occurrence dates, occurrence locations, and plant types for damages that have actually occurred. Furthermore, the third reference information may also include a damage prediction model (artificial intelligence) that has been pre-machine-learned.

[0108] <Point Management Department 239> The point management unit 239 is configured to award points, which can be exchanged for goods or services, to users who have submitted inquiries to the consultation reception unit 232. This provides an incentive for users to submit inquiries and can revitalize communication on the agricultural support service provided by the information processing device 2.

[0109] Specifically, the point management unit 239 awards a predetermined number of points to the account of a user whose consultation has been accepted (registered in the database) from the user terminal 3, for each consultation.

[0110] Furthermore, the point management unit 239 accepts requests from users to exchange points for goods or services. Examples of exchangeable goods or services include products handled by the organization to which the respondent belongs, and service vouchers usable within that organization. Upon receiving a point exchange instruction from a user, the point management unit 239 causes the user terminal 3 to, for example, display a website for exchanging points. Once the point exchange is complete, the point management unit 239 deducts the exchanged points from the user's account.

[0111] <Artificial Intelligence Department 240> The artificial intelligence unit 240 is configured to receive input from each functional unit and return the instructed output. The artificial intelligence used by the information processing device 2 in each functional unit may be common to all units, or it may be prepared individually for each functional unit.

[0112] Specific algorithms used in machine learning for artificial intelligence include nearest neighbors, naive Bayes, decision trees, support vector machines, deep learning using neural networks, and regression models.

[0113] The artificial intelligence unit 240 has a trained model constructed using a learning method such as supervised learning, unsupervised learning, or self-supervised learning. In supervised learning, machine learning is performed using training data. Training data consists of pairs of input data and output data (correct answer data) for training. The trained model included in the artificial intelligence unit 240 can undergo additional training as transfer learning or fine-tuning using new data acquired from the user terminal 3, etc.

[0114] 3.Agricultural support methods This section describes the agricultural support method of the information processing device 2. In this agricultural support method, each part of the information processing device 2 is executed by a computer as each step. The agricultural support method includes the first embodiment, the second embodiment, and the third embodiment.

[0115] <First Embodiment> The agricultural support method of the first embodiment comprises a consultation reception step, a response reception step, and a map display control step. In the consultation reception step, a consultation is received from the user terminal 3. In the response reception step, the consultation is forwarded to the primary respondent terminal 4A, which is selected from among the respondents assigned according to the location of the growing area that is the subject of the consultation, and a response to the consultation is received from the primary respondent terminal 4A. In the map display control step, a polygon map is displayed which includes polygons indicating the growing areas of plants and communication information associated with the polygons.

[0116] Figure 9 is an activity diagram showing the flow of information processing (consultation response processing) performed by the agricultural support system 1. The following sections will explain the information processing in accordance with each activity in this activity diagram.

[0117] The consultation process begins when the user inputs a consultation request regarding plant growth on user terminal 3 (Activity A110). The information processing device 2 (processor 23) receives data indicating the content of the consultation from user terminal 3 and accepts the consultation (Activity A120). After accepting the consultation, the information processing device 2 forwards the consultation to respondent terminal 4 (primary respondent terminal 4A) (Activity A130).

[0118] The respondent to whom the consultation is forwarded enters their response on respondent terminal 4 (Activity A140). The information processing device 2 accepts the response by receiving data indicating the content of the response from respondent terminal 4 (Activity A150). If no response is received from respondent terminal 4, the information processing device 2 forwards the consultation to another respondent terminal 4 (secondary respondent terminal 4B) and accepts the response from that respondent terminal 4.

[0119] After receiving the response, the information processing device 2 outputs the response to the user terminal 3 that initiated the consultation, and, upon request from the user terminal 3, outputs a polygon map reflecting the history of the consultation as communication information to the user terminal 3 (Activity A160). As a result, the response to the consultation and the polygon map are displayed on the user terminal 3 as appropriate (Activity A170).

[0120] <Second Embodiment> The agricultural support method of the second embodiment includes a forecast value display control step. In the forecast value display control step, time-series data is displayed that includes forecast values ​​indicating the possibility of damage occurring to plants at each of several forecast time points from the present time onward, and the annual values ​​of the forecast values ​​for each of the multiple forecast time points.

[0121] Figure 10 is an activity diagram showing the flow of information processing (forecast value display processing) performed by the agricultural support system 1. Below, the information processing will be explained according to each activity in this activity diagram.

[0122] The forecast value display process begins when the user inputs the type of plant and its habitat for which they wish to check the forecast values ​​on user terminal 3 (Activity A210). The information processing device 2 (processor 23) retrieves the forecast values ​​and typical values ​​corresponding to the plant and habitat input from user terminal 3 from the database (Activity A220). If the forecast values ​​for the specified plant and habitat have not yet been calculated, the information processing device 2 calculates those forecast values. After obtaining the forecast values, the information processing device 2 outputs time-series data including the forecast values ​​and typical values ​​to user terminal 3 (Activity A230). As a result, the time-series data is displayed on user terminal 3 (Activity A240).

[0123] <Third Embodiment> The third embodiment of the agricultural support method comprises an image acquisition step and a damage estimation step. In the image acquisition step, an estimation image including plants is acquired. In the damage estimation step, the occurrence of damage in the plants is estimated based on the estimation image, the predicted value at the time the estimation image was acquired, and reference information.

[0124] Figure 11 is an activity diagram showing the flow of information processing (fault prediction processing) performed by agricultural support system 1. The following sections will explain the information processing in accordance with each activity in this activity diagram.

[0125] The fault prediction process begins when the user inputs information such as an image of a plant whose fault status they wish to check on user terminal 3 (Activity A310). The information processing device 2 (processor 23) receives the image input from user terminal 3 and retrieves the corresponding predicted value from the database (Activity A320). After obtaining the image and predicted value, the information processing device 2 determines whether the predicted value is above or below the lower limit (Activity A330). If the predicted value is above or below the lower limit, the information processing device 2 uses a fault prediction model to predict the occurrence of the fault (Activity A340). On the other hand, if the predicted value is below the lower limit, the information processing device 2 predicts that no fault has occurred and skips Activity A340. After predicting the fault, the information processing device 2 outputs the prediction result to user terminal 3 (Activity A350). As a result, the fault prediction result is displayed on user terminal 3 (Activity A360).

[0126] 4. Effect The function of this embodiment can be summarized as follows: Users can collect information about plant growth relatively easily.

[0127] Although embodiments of the present invention have been described above, the present invention is not limited thereto and can be modified as appropriate without departing from the technical spirit of the invention.

[0128] 5. Others In the above embodiment, the information processing device 2 performed various storage and control functions, but instead of the information processing device 2, multiple external devices may be used. That is, various information and programs may be stored in a distributed manner across multiple external devices using blockchain technology or the like.

[0129] The embodiments of this model are not limited to the agricultural support system 1, but may also be agricultural support methods or programs. The agricultural support method comprises each step of the agricultural support system 1. The program causes a computer to function as the agricultural support system 1.

[0130] The agricultural support system 1 does not necessarily have to include a forecasting unit 234, a forecast value display control unit 235, an image acquisition unit 237, a fault prediction unit 238, and a point management unit 239.

[0131] The product may be provided in any of the following embodiments.

[0132] (1) An agricultural support system comprising a processor, the processor configured to perform the following steps by reading a program, the map display control step of displaying a polygon map including polygons indicating plant habitats and communication information associated with the polygons, wherein the communication information is information indicating consultation regarding plant growth in the habitat indicated by the associated polygons.

[0133] (2) The agricultural support system described in (1) above, wherein in the map display control step, information indicating whether or not the consultation has been resolved is displayed on the polygon map.

[0134] (3) An agricultural support system as described in (1) or (2) above, wherein the map display control step accepts the selection of communication information in the polygon map and displays the history of the consultation indicated by the selected communication information and the response to the consultation.

[0135] (4) The agricultural support system described in (3) above, wherein the map display control step further displays a cultivation history including at least one of the plant growth status and management work history in the growing area indicated by the polygon associated with the selected communication information.

[0136] (5) An agricultural support system as described in (3) or (4) above, wherein the processor is configured to further perform the following steps: in the fault estimation step, the processor estimates the occurrence of a fault in the plant included in the plant image based on the plant image and reference information, where the reference information includes a correlation between the plant image and the occurrence of a fault; and in the map display control step, the processor further displays the occurrence of the fault estimated from the plant image.

[0137] (6) An agricultural support system according to any one of (1) to (5) above, wherein the processor is configured to perform the following steps: in the consultation reception step, it receives the consultation from a user terminal; and in the response reception step, it transfers the consultation to the primary respondent terminal of a primary respondent selected from among the respondents assigned according to the location of the growing area that is the subject of the consultation, and receives a response to the consultation from the primary respondent terminal.

[0138] (7) An agricultural support system comprising a processor, the processor configured to perform the following steps by reading a program, the consultation receiving step receiving a consultation from a user terminal regarding the growth of plants in a growing area, and the response receiving step transferring the consultation to a primary respondent terminal of a primary respondent selected from among respondents assigned according to the location of the growing area to which the consultation pertains, and receiving a response to the consultation from the primary respondent terminal.

[0139] (8) In the agricultural support system described in (6) or (7) above, in the response reception step, if the primary respondent terminal issues a request for retransmission, or if a response is not received from the primary respondent terminal within a predetermined period, the consultation is forwarded to the secondary respondent terminal of a secondary respondent selected from among respondents belonging to a second organization that has a cooperative relationship with the first organization to which the primary respondent belongs, and a response is received from the secondary respondent terminal, wherein the second organization is a higher-level organization of the first organization, or an organization that has established a cooperative relationship with the first organization.

[0140] (9) In the agricultural support system described in (8) above, the responses of the primary respondent can only be viewed by other respondents belonging to the first organization or by respondents belonging to the second organization among the registered respondents.

[0141] (10) An agricultural support system according to any one of (6) to (9) above, wherein the processor is configured to further perform the following steps: in the fault estimation step, the processor estimates the occurrence of a fault in the plant included in the plant image based on the plant image and reference information, where the reference information includes a correlation between the plant image and the occurrence of a fault; and in the response reception step, the display format of the consultation on the primary respondent terminal is adjusted according to the estimated occurrence of a fault. Of course, this is not always the case.

[0142] Finally, while various embodiments relating to this disclosure have been described, these are presented as examples only and are not intended to limit the scope of the invention. These novel embodiments can be implemented in a variety of other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims and their equivalents. [Explanation of Symbols]

[0143] 1: Agricultural support system 2: Information Processing Device 3: User terminal 4: Respondent's terminal 4A: Primary respondent terminal 4B: Secondary respondent terminal 20: Communications bus 21: Communications Department 22: Storage section 23: Processor 30: Communications bus 31: Communications Department 32: Storage section 33: Processor 34: Output section 35: Input section 40: Communications bus 41: Communications Department 42: Storage section 43: Processor 44: Output section 45: Input section 231: Registration Department 232: Consultation Department 233: Response Reception Department 234: Forecasting Department 235: Forecast Value Display Control Unit 236: Map display control unit 237: Image acquisition unit 238: Problem Prediction Department 239: Point Management Department 240: Artificial Intelligence Department AI: Respondent information AM: Reply message B11: Plant selection button B12: Report Incident Button B13: Input button for countermeasures CA: Communication display area CI: Client Information CI1: First communication icon CI2: Second communication icon CM: Consultation Message DG: Risk Graph FA: Forecast value display area FB1: First forecast value bar FB2: Second forecast value bar FD: Forecast value display screen FI: Fault Image FN: Name of the problem HA: Heatmap display area HP: Habitat Polygon MD1: First map display screen MD2: Second map display screen O1: 1st layer organization O2 :Second layer organization O31: 3rd layer organization O32: 3rd layer organization O33: 3rd layer organization O41: 4th layer organization O42: 4th layer organization O43: 4th layer organization O44: 4th layer organization O45: 4th layer organization OA: Occurrence prediction area PA: Polygon Map Display Area SA: Plant Selection Area

Claims

1. It is an agricultural support system, Equipped with a processor, The aforementioned processor is configured to perform the following steps by reading a program: In the map display control step, a polygon map is displayed that includes polygons indicating the plant's habitat and communication information associated with the polygons. The aforementioned communication information is information indicating consultation regarding plant growth in the habitat shown by the associated polygon, in an agricultural support system.

2. In the agricultural support system described in claim 1, In the map display control step, the agricultural support system displays information on the polygon map indicating whether or not the consultation has been resolved.

3. In the agricultural support system described in claim 1, The agricultural support system, in the map display control step, accepts the selection of communication information in the polygon map and displays the history of the consultation indicated by the selected communication information and the response to that consultation.

4. In the agricultural support system described in claim 3, The agricultural support system further displays, in the map display control step, a cultivation history including at least one of the plant growth status and management work history in the growing area indicated by the polygon associated with the selected communication information.

5. In the agricultural support system described in claim 3, The aforementioned processor is configured to perform the following steps: In the damage estimation step, the occurrence of damage in the plant included in the plant image is estimated based on the plant image and reference information, where the reference information includes the correlation between the plant image and the occurrence of damage. The aforementioned map display control step further displays the occurrence of damage inferred from the plant images, in an agricultural support system.

6. In the agricultural support system described in claim 1, The aforementioned processor is configured to perform the following steps: In the consultation request step, the consultation is received from the user's terminal. In the response reception step, the agricultural support system forwards the consultation to the primary respondent's terminal, which is selected from among the respondents assigned according to the location of the growing area that is the subject of the consultation, and also receives a response to the consultation from the primary respondent's terminal.

7. It is an agricultural support system, Equipped with a processor, The aforementioned processor is configured to perform the following steps by reading a program: In the consultation request step, users can submit inquiries from their terminals regarding plant growth in their habitat. In the response reception step, the agricultural support system forwards the consultation to the primary respondent's terminal, which is selected from among the respondents assigned according to the location of the growing area that is the subject of the consultation, and also receives a response to the consultation from the primary respondent's terminal.

8. In the agricultural support system according to claim 6 or claim 7, In the response reception step, if the primary respondent's terminal instructs for retransmission, or if a response is not received from the primary respondent's terminal within a predetermined period, the consultation is forwarded to the secondary respondent's terminal, which is selected from among the respondents belonging to the second organization that has a cooperative relationship with the first organization to which the primary respondent belongs, and a response is received from the secondary respondent's terminal. The second organization is an agricultural support system that is a superior organization to the first organization, or an organization with which a partnership with the first organization has been established.

9. In the agricultural support system described in claim 8, An agricultural support system in which the responses of the primary respondent can only be viewed by other registered respondents belonging to the first organization or by respondents belonging to the second organization.

10. In the agricultural support system described in claim 6, The aforementioned processor is configured to perform the following steps: In the damage estimation step, the occurrence of damage in the plant included in the plant image is estimated based on the plant image and reference information, where the reference information includes the correlation between the plant image and the occurrence of damage. In the response reception step, the agricultural support system adjusts the display format of the consultation on the primary respondent's terminal according to the estimated occurrence of the problem.

Images