Agricultural Support System

Abstract

To provide an agricultural support system that can provide information based on the results of predicting the occurrence of disorders. [Solution] According to one aspect of the present invention, an agricultural support system is provided that includes a processor configured to execute each of the following steps by reading a program, and in a forecast value display control step, an agricultural support system is provided that displays time series data including forecast values ​​indicating the possibility of damage to plants at each of a number of forecast time points from the current time onwards, and average annual values ​​of the forecast values ​​at each of the multiple forecast time points.

Description

[Technical field]

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

[0002] As disclosed in the following documents, a device that predicts damage (diseases, pests, and physiological damage) that will occur in plants (crops) using a learning model is known. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-93957 Summary of the Invention [Problem to be solved by the invention]

[0004] Although the above-mentioned device is capable of predicting the occurrence of a fault, a concrete method for utilizing the prediction results is required.

[0005] In view of the above circumstances, the present invention provides an agricultural support system capable of providing information based on the results of predicting the occurrence of a problem. [Means for solving the problem]

[0006] According to one aspect of the present invention, there is provided an agricultural support system comprising a processor configured to execute each of the following steps by reading a program, and in a forecast value display control step, an agricultural support system is provided which displays time series data including forecast values ​​indicating the possibility of damage occurring to plants at each of a plurality of forecast time points from the current time onwards, and average annual values ​​of the forecast values ​​at each of the plurality of forecast time points.

[0007] According to such an embodiment, a variety of information can be provided to the user using a forecast value indicating the possibility of damage to the plant. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a configuration diagram showing an agricultural support system 1. [Diagram 2] 2 is a block diagram showing a hardware configuration of an information processing device 2. FIG. [Diagram 3] FIG. 2 is a block diagram showing the hardware configuration of a user terminal 3 and a respondent terminal 4 (primary respondent terminal 4A). [Figure 4] 2 is a block diagram showing functions realized by an information processing device 2 (processor 23). FIG. [Diagram 5] FIG. 2 is a diagram showing an example of the structure of an organization to which a respondent belongs. [Figure 6] 13 is a diagram showing an example of a forecast value display screen FD displayed on the user terminal 3 or the respondent terminal 4. FIG. [Figure 7] 13 is a diagram showing an example of a first map display screen MD1 displayed on the user terminal 3 or the respondent terminal 4. FIG. [Figure 8] 13 is a diagram showing an example of a second map display screen MD2 displayed on the user terminal 3 or the respondent terminal 4. FIG. [Figure 9] 1 is an activity diagram showing the flow of information processing (consultation response processing) executed by the agriculture support system 1. FIG. [Figure 10] 1 is an activity diagram showing a flow of information processing (forecast value display processing) executed by the agriculture support system 1. FIG. [Figure 11] 1 is an activity diagram showing the flow of information processing (fault inference processing) executed by the agricultural support system 1. FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described with reference to the drawings. Various characteristic features shown in the following embodiments can be combined with each other.

[0010] Incidentally, a program for realizing the software appearing in one embodiment may be provided as a non-transitory computer-readable recording medium, or may be provided so as to be downloadable from an external server, or 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] In addition, in various information processing according to an embodiment, an input and an output according to the input can be realized. Here, as long as an output is obtained as a result of the input, the form of 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 judgment formula such as a regression formula constructed by a statistical method), or may be a trained model that has previously trained the correlation between the input and the output, or may be a large-scale language model that can output a desired result by inputting a prompt.

[0012] In one embodiment, the term "unit" may include, for example, a combination of hardware resources implemented by a circuit in the broad sense and software information processing that can be specifically realized by these hardware resources. In one embodiment, various information is handled, and this information is represented by, for example, physical values ​​of signal values ​​representing voltage and current, high and low signal values ​​as a binary bit collection consisting of 0 or 1, or quantum superposition (so-called quantum bits), and communication and calculation can be performed on the circuit in the broad sense.

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

[0014] 1. Hardware Configuration This section describes the hardware configuration.

[0015] <Agricultural Support System 1> Figure 1 is a configuration diagram showing an agricultural support system 1. The agricultural support system 1 provides services to multiple users, such as responding to inquiries about the growth of plants (mainly agricultural crops), forecasting the occurrence of problems, diagnosing problems, and the like.

[0016] The agricultural support system 1 includes an information processing device 2, a user terminal 3, and a respondent terminal 4 (a primary respondent terminal 4A and a secondary respondent terminal 4B). The information processing device 2, the user terminal 3, and the respondent terminal 4 are configured to be able to communicate with each other via a telecommunications line.

[0017] In one embodiment of the agriculture support system 1, the agriculture support system 1 is composed of one or more devices or components. For example, if the agriculture support system 1 is composed only of an information processing device 2, the agriculture support system 1 can be the information processing device 2. These components will be described below.

[0018] <Information processing device 2> 2 is a block diagram showing a hardware configuration of the information processing device 2. The information processing device 2 includes 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 via the communication bus 20 inside the information processing device 2.

[0019] <Communications Division 21> The communication unit 21 is preferably a wired communication means such as USB, IEEE1394, Thunderbolt (registered trademark), wired LAN network communication, etc., but may also include wireless LAN network communication, mobile communication such as LTE / 5G, BLUETOOTH (registered trademark) communication, etc. as necessary. In other words, it is more preferable to implement it as a collection of multiple communication means. In other words, 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 information defined by the above description. This can be implemented, for example, as a storage device such as a solid state drive (SSD) that stores various programs and the like related to the information processing device 2 executed by the processor 23, or as a memory such as a random access memory (RAM) that stores temporarily required information (arguments, arrays, etc.) related to the 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 processes and controls the overall operations 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 out a predetermined program stored in the storage unit 22. That is, information processing by software stored in the storage unit 22 can be specifically 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 single, and 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 an on-premise type or a cloud type. As the information processing device 2 in the cloud type, the above-mentioned functions and processes may be provided in the form of, for example, SaaS (Software as a Service) or cloud computing.

[0023] <User terminal 3> Fig. 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 Fig. 3A, the user terminal 3 includes a communication bus 30, a communication unit 31, a memory unit 32, a processor 33, an output unit 34, and an input unit 35. The communication unit 31, the memory unit 32, the processor 33, the output unit 34, and the input unit 35 are electrically connected via the communication bus 30 inside the user terminal 3. The description of the communication unit 31, the memory unit 32, and the processor 33 will be omitted as they are similar to the description of each unit in the information processing device 2.

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

[0025] <Input section 35> The input unit 35 accepts an operation input made by a user. The operation input is transferred as a command signal to the processor 33 via the communication bus 30. The processor 33 may execute a predetermined control or calculation based on the transferred command signal as necessary. The input unit 35 may be included in the housing of the user terminal 3, or may be externally attached. For example, the input unit 35 may be implemented as a touch panel integrated with the output unit 34. When the input unit 35 is implemented as a touch panel, the user can input a tap operation, a swipe operation, or the like to the input unit 35. As the input unit 35, a switch button, a mouse, a track pad, a QWERTY keyboard, or the like can be adopted instead of a touch panel.

[0026] <Respondent Terminal 4> 3B, the primary respondent terminal 4A includes a communication bus 40, a communication unit 41, a memory unit 42, a processor 43, an output unit 44, and an input unit 45. The communication unit 41, the memory unit 42, the processor 43, the output unit 44, and the input unit 45 are electrically connected via the communication bus 40 inside the primary respondent terminal 4A. Descriptions of the communication unit 41, the memory unit 42, the processor 43, the output unit 44, and the input unit 45 will be omitted as they are the same as the descriptions of each unit in the user terminal 3. In addition, the hardware configuration of the secondary respondent terminal 4B is the same as that of the primary respondent terminal 4A.

[0027] 2. Functional configuration In this section, the functional configuration of the present embodiment will be described. Information processing by software stored in the storage 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] 4 is a block diagram showing 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 231> The registration unit 231 registers users who use the user terminal 3. The users are, for example, farmers or employees of organizations (farmers or companies) that manage farms. The registration unit 231 registers user data including personal information of the users (name, address, contact information, affiliated organization, etc.) as well as user ID, type of plant (crop) being cultivated, managed habitat (address of field), etc., in a user database stored in, for example, the storage unit 22. For a user who has multiple habitats, the registration unit 231 registers the addresses of the multiple habitats. In addition, if the user is a farmer or an employee of a company, one habitat can 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 farm instructors, and include, for example, staff of agricultural cooperatives (e.g., JA: Japan Agricultural Co-operatives), agricultural staff of local governments, and employees of supply companies such as pesticide manufacturers. The registration unit 231 registers respondent data including personal information of the respondent (such as name, organization, contact information, etc.), respondent ID, etc., in a respondent database stored in, for example, the storage unit 22.

[0031] <Consultation Reception Department 232> The consultation receiving unit 232 is configured to receive a consultation regarding the growth of plants in a predetermined habitat from the user terminal 3. Specifically, the consultation receiving unit 232 receives input (upload) of matters that the user would like to consult with a respondent (trainer) for each habitat managed by the user in the user terminal 3. The consultation receiving unit 232 links the consultation content received from the user terminal 3 with the user and the habitat, and registers it in a consultation database stored in the storage unit 22, for example.

[0032] The contents of the consultation received by the consultation receiving unit 232 include, for example, the determination (diagnosis) of damage to the plant (disease, pests, and physiological damage), measures against the damage or pests, etc. The contents of the consultation input by the user to the user terminal 3 include, for example, an image of the plant to be consulted about, text explaining the type, state, symptoms, etc. of the plant, numerical values, symbols, etc.

[0033] The user, for example, selects a respondent (primary respondent) to consult from among the candidate respondents (trainers) presented on the user terminal 3, and inputs the consultation. The candidate respondent is extracted by the consultation receiving unit 232 from among the respondents registered in the respondent database according to the habitat of the subject of the consultation (the habitat registered by the user). Note that the consultation receiving unit 232 may automatically select a respondent according to the habitat without accepting the selection of a respondent from the user terminal 3.

[0034] Furthermore, the consultation receiving unit 232 may receive a consultation not from a respondent (trainer) but from another user (for example, an employee, manager, or owner of the same farm). In this case, the other user is selected as the person to consult in the user terminal 3. In this way, by making it possible to receive a consultation from another user, it is possible to visualize the occurrence of troubles in the farm, accumulate trouble histories, strengthen monitoring of the farm, educate employees, and so on.

[0035] <Answer Reception Section 233> The answer receiving unit 233 is configured to transfer the consultation received by the consultation receiving unit 232 to a respondent (primary respondent or secondary respondent) registered in the respondent database, and to receive an answer from the respondent. The answer receiving unit 233 links the received answer content with the respondent and the consultation content, and registers it in the consultation database. As a result, the answer content is stored in association with the user who made the consultation (consultant) and place of origin, in addition to the respondent and the consultation content.

[0036] The answer receiving unit 233 transmits to the answerer terminal 4 (primary answerer terminal 4A or secondary answerer terminal 4B) images for consultation uploaded from the user terminal 3, diagnostic information held by the information processing device 2 (for example, predicted values ​​for the occurrence of a fault, as described below, and the occurrence status of the fault inferred from the images), etc.

[0037] The answer to the inquiry includes, for example, information on the determination of the problem and countermeasures (type of pesticide used, timing, etc.). The answerer inputs this information in the answerer terminal 4. The answer receiving unit 233 transmits the information received from the answerer terminal 4 to the user terminal 3 as the answer to the inquiry.

[0038] The answer receiving unit 233 may transfer the consultation to the primary answerer terminal 4A of the primary answerer selected from the answers assigned according to the location of the habitat that is the subject of the consultation received by the consultation receiving unit 232, and may receive an answer to the consultation from the primary answerer terminal 4A. This allows the answer to the consultation to be considered by the primary answerer assigned in advance to the habitat that is the subject of the consultation, thereby enabling a quick solution to the consultation.

[0039] The primary respondent may be assigned, for example, based on the relationship between the area of ​​responsibility of the first organization to which the primary respondent belongs (e.g., a JA branch office) and the location of the habitat of the subject of the consultation, or based on the relationship between the area of ​​responsibility set for each individual respondent and the location of the habitat.

[0040] When a re-transfer instruction is received from the primary answerer terminal 4A, or when no answer is received from the primary answerer terminal 4A within a predetermined period of time, the answer receiving unit 233 may transfer the consultation to the secondary answerer terminal 4B of the secondary answerer selected from among the answerers belonging to the second organization that has a collaborative relationship with the first organization to which the primary answerer belongs, and may receive an answer from the secondary answerer terminal 4B. The second organization is an upper organization of the first organization, or an organization that is set up to be collaborative with the first organization. This allows the secondary answerer to back up the consultation when the primary answerer is unable to answer the consultation. Therefore, in addition to the effect of quickly resolving the consultation, it is possible to ensure that an appropriate answer is provided to the user's consultation.

[0041] The period until the consultation is transferred to the secondary respondent is set arbitrarily, for example, one week, etc. Furthermore, the reply receiving unit 233 may notify the primary respondent terminal 4A that no reply has been input after a predetermined first period has elapsed since the consultation was transferred to the primary respondent terminal 4A, and may then transfer the consultation to the secondary respondent terminal 4B after a predetermined second period has elapsed since the notification.

[0042] The answer receiving unit 233 may adjust the display form of the inquiry on the primary answerer terminal 4A (or the secondary answerer terminal 4B) according to the occurrence state of the trouble inferred by the trouble inferring unit 238 described later using the plant image included in the inquiry. This makes it possible to present the inquiries that should be answered preferentially to the primary answerer, which makes it easier to quickly solve the inquiries that require urgent attention.

[0043] For example, the answer receiving unit 233 assigns a priority to each consultation according to the occurrence status of the inferred fault, and displays the consultations on the primary answerer terminal 4A or the secondary answerer terminal 4B in descending order of priority. The answer receiving unit 233 may also attach a label or icon indicating a high priority to a consultation with a high priority, or highlight the consultation by changing the font, coloring, or the like. The priority is a numerical value representing the risk of the fault. For example, the priority may be calculated by the fault inferring unit 238 described later when the occurrence status of the fault is inferred, or may be calculated using the type or degree of the inferred fault and a table that defines the risk in advance.

[0044] The habitat of the respondent and the organizational structure of the respondent (the affiliation relationships between organizations) are recorded, for example, in a respondent database.

[0045] The answers of the primary answerer can only be viewed by other answerers who belong to the first organization or the second organization among the answerers registered in the answerer database. Therefore, even if a respondent is registered in the answerer database, if the organization he or she belongs to is not the same first organization as the primary answerer and does not belong to the second organization, for example, the map display control unit 236 restricts viewing of the answers of the primary answerer (i.e., the answers are not displayed on the terminal). This makes it possible to protect the user's personal information, etc.

[0046] In addition, under the above conditions, viewing may be restricted not only to the answer of the primary respondent but also to the entire consultation history including the answer. Furthermore, a viewing restriction may be set for the consultation history such that users other than the consultant or users outside the organization (farmer) to which the consultant belongs cannot view the consultation history. In addition, the viewing restriction conditions (for example, whether or not to disclose the consultation history to other users) may be set by individual users.

[0047] FIG. 5 is a diagram showing an example of the structure of an organization to which a respondent belongs. In FIG. 5, "A" to "T" each indicate one respondent (instructor). Also, "U" to "Z" surrounded by dashed lines each indicate one user (e.g., a farmer) who consults with the respondent. In the example of FIG. 5, the respondent belongs to a respondent organization having a hierarchical structure consisting of a first hierarchical organization O1, a second hierarchical organization O2, a third hierarchical organizations O31, O32, and O33, and a fourth hierarchical organizations O41, O42, O43, O44, and O45.

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

[0049] 5, among the fourth hierarchical organizations O41, O42, O43, O44, and O45, a link (dashed line) is set between the fourth hierarchical organization O42 in region II and the fourth hierarchical organization O43 in region III. Similarly, among the third hierarchical organizations O31, O32, and O33, a link is set between the third hierarchical organization O31 in α prefecture and the third hierarchical organization O32 in β prefecture.

[0050] In FIG. 5, for example, when user X inputs a consultation, respondent P in charge of the habitat managed by user X (the habitat to be consulted about) is selected as the primary respondent by the response receiving unit 233 from among the respondents belonging to the fourth hierarchical organization O43 (corresponding to the "first organization" in the processing of the response receiving unit 233) in region III in which the habitat managed by user X (the habitat to be consulted about) is located, and the consultation is transferred to respondent P's terminal (primary respondent terminal 4A).

[0051] If the respondent P is unable to respond to the consultation himself, he / she inputs to the primary respondent terminal 4A a message indicating that he / she cannot respond (re-transfer of the consultation). If the response receiving unit 233 receives the re-transfer of the consultation or if no response is input from the primary respondent within a predetermined period of time, the response receiving unit 233 selects respondent G or respondent H who belongs to the third hierarchical organization O32 (corresponding to the "second organization" in the processing of the response receiving unit 233) in β prefecture, which is a higher organization than the fourth hierarchical organization O43 in region III, or respondent M or respondent N who belongs to the fourth hierarchical organization O42 (corresponding to the "second organization" in the processing of the response receiving unit 233) in region II that is set up to cooperate with the fourth hierarchical organization O43 in region III, as a secondary respondent, and transfers the consultation to the terminal of the secondary respondent (secondary respondent terminal 4B).

[0052] If the secondary respondent is also unable to provide an answer, the answer receiving unit 233 may further transfer the consultation to a respondent in an organization higher than the second organization (in the above example, the second-level organization O2) or an organization that is set up to collaborate with the second organization (in the above example, the third-level organization O31 in prefecture α).

[0053] The answer receiving unit 233 may also receive a nomination of a secondary answerer from the primary answerer. In this case, the primary answerer inputs information on the answerer to be nominated as the secondary answerer from the primary answerer terminal 4A. The nominated answerer may be an answerer belonging to the second organization (higher organization or affiliated organization), or an answerer belonging to an organization that does not fall under either the higher organization or affiliated organization (an answerer outside the organizational structure such as a prefectural employee in the example of FIG. 5).

[0054] The answer receiving unit 233 may transmit the answer received from the secondary answerer terminal 4B directly to the user terminal 3 as an answer from the secondary answerer, or may transfer the answer received from the secondary answerer terminal 4B to the primary answerer terminal 4A. The primary answerer may send the answer transferred to the primary answerer terminal 4A to the user terminal 3 as is, or may edit the transferred answer and send it to the user terminal 3.

[0055] When the consultation receiving unit 232 receives a consultation from a user terminal 3 for another user (e.g., an employee or manager of the same farm), the reply receiving unit 233 transfers the consultation to the user terminal 3 of the other user. If the user who received the consultation is able to reply, he or she inputs the reply (e.g., instructions to spray pesticides) himself or herself. On the other hand, if he or she is unable to reply, the user who received the consultation transfers the consultation to the replying person (instructor). The consultation receiving unit 232 accepts the consultation again as a consultation for the replying person, and the reply receiving unit 233 transfers the consultation to the primary replying person terminal 4A.

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

[0057] The disorders for which the forecast unit 234 estimates the forecast value include diseases, pests, and physiological disorders. The physiological disorders include deficiencies of components such as magnesium and calcium, and water shortages. The forecast unit 234 also predicts the occurrence probability (i.e., forecast value) of disorders for a "type of plant" for each "type of disorder." The "type of plant" is, for example, varieties such as strawberry, radish, onion, broccoli, and cabbage. Furthermore, the "type of plant" may be subdivided by subcategories such as varieties of crops such as onion, such as "Sonic" and "Neo Earth," and harvest days such as "early" and "mid-season." The "type of disorder" is, for example, disease names such as black sooty mold and black rot, pest names such as cutworms and aphids, or phenomena of physiological diseases such as magnesium deficiency and water shortage.

[0058] The first reference information includes a correlation between the forecast conditions and the forecast values ​​of each fault, and is stored in, for example, the storage unit 22. The first reference information may include, for example, a table, a function, a simple algorithm, or the like, indicating a correlation between a feature amount extracted from the forecast conditions and the forecast value. The correlation included in the first reference information can be constructed, for example, by statistically analyzing data that combines an actually occurring fault with the occurrence conditions and records the combined data. The first reference information may also include a forecast value estimation model (artificial intelligence) that has been previously subjected to machine learning. The forecast value estimation model is included in the artificial intelligence unit 240.

[0059] The forecast value estimation model is trained so that it can input forecast conditions and output forecast values. When using such a forecast value estimation model, the forecast unit 234 inputs the type of plant to be predicted, the region, and the date and time (including future dates and times) to the forecast value estimation model, and causes the forecast value estimation model to output at least one possible failure and the probability (forecast value) of the occurrence of each of the at least one failure. The forecast unit 234 may also input forecast conditions including weather forecast values ​​(weather, air pressure, temperature, humidity, etc.) of the region for which the forecast value is to be output to the forecast value estimation model.

[0060] The prediction value estimation model used by the forecast unit 234 is constructed by machine learning using, as teacher data, a record associating the type of plant where a failure occurred in the past, the type of failure that occurred, the area where the plant grew, and the date and time of the failure. When a weather forecast value is used as a forecast condition, a record associating the weather (weather, air pressure, temperature, humidity, etc.) at the time of the failure in addition to the above-mentioned plant type, type of failure, area, and date and time of the failure is used as teacher data. In the prediction value estimation ability model, parameters calculated, tuned, etc. by learning configure the correlation of the first reference information.

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

[0062] When the forecast value is equal to or greater than a predetermined threshold, the forecast unit 234 may output a notification (e.g., a push notification) to notify the user terminal 3 or the respondent terminal 4 of a danger at a predetermined timing. The threshold is set, for example, as a percentage (e.g., 80%) of the maximum forecast value. The timing for outputting the notification is, for example, the day or the day before the date when the forecast value equal to or greater than the threshold is predicted. The forecast unit 234 may also output the notification when a specific number of consecutive days occur when the forecast value is equal to or greater than the threshold. The specific number of days is, for example, two days. The conditions such as the threshold, notification timing, and specific number of times may differ depending on the type of obstacle, 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 including forecast values ​​indicating the possibility of damage occurring to plants at each of a plurality of forecast time points from the present time onwards, and average annual values ​​of the forecast values ​​at each of the plurality of forecast time points on the user terminal 3 or the respondent terminal 4. This makes it possible to preventively take measures against damage to plants based on future forecast values.

[0064] The forecast time point at which the forecast value display control unit 235 displays the forecast value is typically a date and time in the future from the current time point, but may include the current time point. The multiple forecast time points are set, for example, at equal intervals of one day. 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 forecast values ​​for multiple forecast time points.

[0065] The "normal value" is the average value of forecast values ​​for the same plant, the same region, and the same date and time for each year (e.g., five years) predicted by the forecasting unit 234 in the past, which are stored in the forecast value database. The time series data displayed by the forecast value display control unit 235 is generated for each type of plant and each region. In other words, the forecast values ​​included in one piece of time series data are all for the same plant and the same region. The time series data displayed on the user terminal 3 or the respondent terminal 4 may be numerical values ​​or may be graphical, such as a graph.

[0066] The forecast value display control unit 235 may display a figure showing the magnitude of the forecast value and a figure showing the magnitude of the annual value in comparison at each of a plurality of forecast time points of the time series data. This allows the magnitude of the risk of future failure occurrence to be grasped in advance.

[0067] Furthermore, the forecast value display control unit 235 may output a notification to the user terminal 3 or the respondent terminal 4 when the value obtained by subtracting the normal year value from the forecast value is equal to or greater than a predetermined threshold. This allows the user to take measures to prevent the occurrence of a fault at an early stage. The threshold may be a fixed value or a percentage of the normal year value (for example, 10% of the normal year value).

[0068] The forecast value display control unit 235 may display information indicating that the forecast value is higher or lower than the normal year value on the user terminal 3 or the respondent terminal 4. This allows the user to understand the degree of risk of a failure compared to normal years.

[0069] FIG. 6 is a diagram showing an example of a forecast value display screen FD displayed on the user terminal 3 or the respondent terminal 4. The forecast value display screen FD displays forecast values ​​for a 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. Multiple plant selection buttons B11 for selecting a plant (agricultural crop) are displayed in the plant selection area SA. When any one of the plant selection buttons B11 is selected by a pressing operation using the input unit 35 of the user terminal 3, forecast values ​​for damage that may occur to the selected plant are displayed in each forecast value display area FA.

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

[0071] The first forecast value bar FB1 is an object that indicates the magnitude of the forecast value (probability of occurrence of a fault) for each day from the present time (today) to a predetermined period (six days from now) predicted by the forecast unit 234. The color of the first forecast value bar FB1 may change according to the magnitude of the forecast value. For example, the first forecast value bar FB1 may be colored in a color that approaches green as the forecast value is smaller and approaches red as the forecast value is higher.

[0072] The second forecast value bar FB2 is an object that indicates the size of the average value of the forecast value for the date on which the first forecast value bar FB1 is displayed. In the example of Fig. 6, the second forecast value bar FB2 is arranged so as to overlap part of the first forecast value bar FB1 for the corresponding date.

[0073] The risk graph DG is an object that shows the size of the average value (average value of forecast values ​​for one week) of the first forecast value bar FB1 displayed in the forecast value display area FA. The risk graph DG is composed of a combination of a bar showing the size of the forecast value and text showing the risk level (alert level) (for example, "alert," "caution," "watch," etc.).

[0074] The occurrence report button B12 is an object that accepts input for a user to report the occurrence of a problem when the occurrence of the problem displayed in the forecast value display area FA is recognized in the user's own habitat. When an input operation is performed on the occurrence report button B12 by the input unit 35 of the user terminal 3, 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, user information (habitat), etc., in a problem record database of the storage unit 22, for example. The occurrence information is appropriately referred to as an occurrence history from the user terminal 3 or the respondent terminal 4, and is used as teacher data for a forecast value estimation model used by the forecast unit 234.

[0075] The countermeasure input button B13 is an object that accepts input for a user to report the implementation of a countermeasure (e.g., spraying a pesticide) when the user implements a countermeasure for the 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 causes the user terminal 3 to display a screen that accepts input of details of the countermeasure (e.g., type of pesticide, growing area where sprayed, spraying date, etc.). The information input on the screen is linked to the type of plant, type of problem, etc., and registered in the problem record database as countermeasure implementation information. The countermeasure implementation information is referred to as a response history from the user terminal 3 or the respondent terminal 4 as appropriate.

[0076] The forecast value display control unit 235 may display a text message or an icon on the forecast value display screen FD (specifically, the forecast value display area FA) as a notification when the value obtained by subtracting the normal 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, or may highlight the corresponding first forecast value bar FB1 by changing the color, shape, etc.

[0077] The forecast value display control unit 235, for example, receives a display request from a user and causes the user terminal 3 to display time-series data of forecast values. In addition, for example, when the response receiving unit 233 transfers a consultation to the respondent terminal 4, the forecast value display control unit 235 causes the respondent terminal 4 to display time-series data of forecast values ​​of a plant related to the consultation together with an image and the content of the consultation transmitted from the user terminal 3. 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 need to 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 cause the user terminal 3 or the respondent terminal 4 to display a map including various information related to plant damage.

[0079] Specifically, the map display control unit 236 displays a polygon map including polygons indicating the habitat of plants and communication information associated with the polygons on the user terminal 3 or the respondent terminal 4. The "communication information" is information indicating an inquiry (an inquiry accepted by the inquiry accepting unit 232) regarding the growth of plants in the habitat indicated by the associated polygon. This allows the user to check the occurrence status 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 may be acquired from a database stored in a server external to the information processing device 2. The habitat data includes information such as the position (address), shape, area, etc. of the habitat (arable land such as rice paddies and fields).

[0081] The communication information included in the polygon map includes information about consultations made by users other than the user viewing the polygon map. Typically, the polygon map includes communication information about consultations made by all users who have made the contents of their consultations public, and this communication information is displayed on the user terminal 3 of each user.

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

[0083] Furthermore, the map display control unit 236 may receive a selection of communication information on the polygon map, and may display a history of the consultation indicated by the selected communication information (the consultation received by the consultation receiving unit 232) and the answer to the consultation (the answer received by the answer receiving unit 233). This allows the user to refer to the consultation history of other users in habitats close to the user's own habitat, and to collect information on the possibility of a disorder, measures to deal with the disorder, and the like.

[0084] The communication information (history) is labeled by the type of obstacle and / or the type of plant. The map display control unit 236 accepts, from the user terminal 3 or the respondent terminal 4, sorting by the type of obstacle or the type of plant, switching on / off display, search, etc.

[0085] The map display control unit 236 may further display a cultivation history including at least one of the growth status and management work history of the plant in the growing area indicated by the polygon associated with the selected communication information. This allows the user to refer to the cultivation history of the plant along with the past consultation history, so that the user can collect more information. The "growth status" includes the presence or absence of a problem, the type of problem that occurred, the time of the problem, etc. The "management work history" includes a history of pesticide spraying, a history of fertilization, the time of sowing, the time of planting, etc. The history of pesticide spraying includes the type of pesticide, the time of pesticide spraying, the number of times the pesticide was sprayed, etc. The history of fertilization includes the type of fertilizer, the time of fertilization, the number of times the pesticide was sprayed, etc.

[0086] The map display control unit 236 may further display the occurrence status of a fault inferred by the fault inferring unit 238 described later from a plant image (an image acquired by the image acquiring unit 237 described later) included in the consultation indicated by the selected communication information. This allows the user to refer to the occurrence status of a fault together with the past consultation history, thereby allowing the user to collect more information.

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

[0088] In the polygon map display area PA, a polygon map including a habitat polygon HP, a first communication icon CI1, and a second communication icon CI2 is displayed. The polygon map in Fig. 7 is obtained by superimposing a habitat polygon HP on general map data, and further by adding a first communication icon CI1 or a second communication icon CI2 to a specific habitat polygon HP.

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

[0090] The communication information included in the polygon map may be expressed as the color of each habitat polygon HP. For example, a habitat polygon HP with a resolved consultation may be colored green, and a habitat polygon HP with an unresolved consultation may be colored red. Such coloring of the habitat polygon HP may be used in combination with the communication icon. Furthermore, a habitat polygon HP corresponding to a habitat with no consultation may not be displayed (colored) in the polygon map. Furthermore, an icon indicating the type (category) of the problem to be consulted (for example, a virus mark icon for disease, an insect mark icon for pests, a boar mark icon for vermin, etc.) may be displayed as a communication icon attached to the habitat polygon HP.

[0091] In the polygon map display area PA, when an input operation is performed from the user terminal 3 or the 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 consultation history indicated by the selected communication information is displayed in the communication display area CA.

[0092] The communication display area CA includes a disability name FN, a disability image FI, consultation information CI, a consultation message CM, answerer information AI, and an answer message AM. The disability name FN includes a disability name and a plant name, which are extracted from the consultation content or the answer content. The disability image FI is an image corresponding to the extracted disability name selected from images prepared in advance. The consultation information CI is information about the user who sent the consultation. The consultation message CM is the consultation content sent from the user. The consultation message CM may include information other than text, such as images. The answerer information AI is information about the answerer (instructor) who sent the answer. The answer message AM is the answer content sent from the answerer. The answer message AM may also include information other than text, such as images.

[0093] The map display control unit 236 may display an object (for example, a "Purchase Pesticide" button) for accepting the purchase of pesticides included in the answer from the respondent, in the communication display area CA displayed on the user terminal 3. When an input operation is performed on the object for purchasing pesticides from the user terminal 3, the map display control unit 236, for example, displays a link (URL) to a site (EC site) for purchasing pesticides, transitions the display screen of the user terminal 3 to the purchasing site, and the like. The map display control unit 236 may also directly accept the purchase of pesticides by inputting an operation on the object for purchasing pesticides.

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

[0095] The polygon map may also include information indicating the magnitude of the forecast value predicted by the forecasting unit 234. For example, the map display control unit 236 may display a layer (heat map) in which regions on the map are colored according to the magnitude of the forecast value, superimposed on the map on which the polygons are displayed. The heat map of the forecast value is, for example, color-coded for each section divided into mesh units for predicting the forecast value. The map display control unit 236 may also display the heat map of the forecast value on the user terminal 3 or the respondent terminal 4, independent of the polygon map. Furthermore, the independent heat map may include communication information common to the polygon map. The heat map is generated for each type of obstacle and type of plant.

[0096] 8 is a diagram showing an example of the second map display screen MD2 displayed on the user terminal 3 or the respondent terminal 4. The second map display screen MD2 includes a heat map display area HA and a communication display area CA. The communication display area CA is common to the first map display screen MD1.

[0097] In the heat map display area HA, a heat map including a first communication icon CI1 and a second communication icon CI2 is displayed. The heat map in FIG. 8 is obtained by dividing general map data into a number of sections, and coloring each section according to the magnitude of the forecast value. Areas where the forecast value is small are colorless, and as the forecast value increases, the color of the section becomes darker (or approaches red). In the example of FIG. 8, a predicted occurrence area OA where the forecast value is large (high probability of occurrence of a fault) is present in the lower right part. The lines drawn in the heat map display area HA indicate roads on the map.

[0098] The first communication icon CI1 and the second communication icon CI2 displayed in the heat map 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 arranged at the locations on the map of the habitats where the consultations occurred.

[0099] <Image acquisition unit 237> The image acquiring unit 237 is configured to acquire an image for estimation including a plant from the user terminal 3. The image for estimation is an image including at least an affected part of a plant for which disease determination is to be performed, which is captured by, for example, a camera provided in the user terminal 3. The image acquiring unit 237 may also acquire an image of a plant included in a consultation accepted by the consultation accepting unit 232.

[0100] <Fault prediction section 238> The failure inference unit 238 is configured to infer the occurrence state of a failure in the plant included in the image for estimation based on the inference information including at least the image for estimation acquired by the image acquisition unit 237, the forecast value at the time when the image for estimation was acquired predicted by the forecast unit 234, and the second reference information. This allows the occurrence of a failure to be inferred using the forecast value, which is the possibility of failure occurrence, and therefore the accuracy of inferring a failure based on the image of the plant can be improved.

[0101] The second reference information includes the correlation between the estimation information and the forecast value and the occurrence status of the failure, and is stored in, for example, the storage unit 22. The estimation information includes, in addition to the estimation image, for example, the acquisition date of the estimation image, the acquisition location, the type of plant, etc. The second reference information may include, for example, a table, a function, a simple algorithm, etc., indicating the correlation between the feature amount (for example, vector data) extracted from the estimation information (typically the propulsion image) and the forecast value and the occurrence status of the failure. The correlation included in the second reference information can be constructed, for example, by statistically analyzing the data recorded by combining the actually occurring failure with the plant image, the occurrence date, the occurrence location, the plant type, and the forecast value. The second reference information may also include a failure estimation model (artificial intelligence) that has been previously subjected to machine learning. The failure estimation model is included in the artificial intelligence unit 240.

[0102] The fault prediction model includes a first form in which prediction information is input and a fault occurrence status is output, a second form in which prediction information and a forecast value are input and a fault occurrence status is output, and a third form in which prediction information is input and a fault occurrence probability is output. When the first form of the forecast value prediction model is used, the forecast value is used as determination information for determining whether or not to perform prediction using the fault prediction model.

[0103] When the first type of failure inference model is used, the second reference information includes a lower limit value of a forecast value for determining whether or not a failure occurs, and a failure inference model that is trained to be able to output a type of failure by inputting inference information including an image for inference. When the forecast value is below the lower limit value included in the second reference information, the failure inference unit 238 infers that no failure has occurred in the plant included in the image for inference, and when the forecast value is equal to or greater than the lower limit, the failure inference unit 238 infers the type of failure occurring in the plant included in the image for inference by inputting inference information including an image for inference to the failure inference model. This allows highly accurate inference to be made by the failure inference model when the possibility of failure occurrence is high (when the forecast value is equal to or greater than the lower limit). Also, when the possibility of failure occurrence is low (when the forecast value is less than the lower limit), the processing by the failure inference model is skipped, thereby reducing the processing load of the processor 23.

[0104] When the second type of failure inference model is used, the second reference information includes a failure inference model that is trained so as to be able to input the inference information and the forecast value and output the type of failure. The failure inference unit 238 inputs the inference information and the forecast value to the failure inference model, thereby inferring the type of failure occurring in the plant included in the inference image.

[0105] When the fault inference model of the third form is used, the second reference information includes a judgment threshold and a fault inference model that is trained to be able to output the occurrence probability of a plurality of faults by inputting inference information including an inference image. When the product of the occurrence probability output by the fault inference model and the forecast value for each fault is equal to or greater than the judgment threshold, the fault inference unit 238 infers that the fault has occurred.

[0106] The first and third types of fault inference models are constructed by machine learning using as training data a record that associates, for example, an image of an affected part of a plant where a fault has occurred in the past, the type of fault that has occurred, the area where the plant was growing, and the date and time of the fault. The second type of fault inference model is constructed by machine learning using as training data a record that associates, in addition to the same image of the affected part, the type of fault, the area, and the date and time of the fault as in the first type, a forecast value at the time of the fault. In these fault inference models, parameters calculated, tuned, etc. by learning constitute the correlation of the second reference information.

[0107] The fault inference unit 238 may infer the occurrence status of a fault in a plant included in a plant image based on the inference information including at least a plant image included in the consultation accepted by the consultation acceptance unit 232 and the third reference information. The third reference information includes a correlation between the inference information and the occurrence status of a fault, and is stored in, for example, the storage unit 22. The inference information includes, in addition to the plant image, for example, the acquisition date, acquisition location, and type of plant. The third reference information may include, for example, a table, a function, a simple algorithm, and the like, which indicate the correlation between the feature amount (for example, vector data) and the forecast value extracted from the inference information (typically a plant image) and the occurrence status of a fault. The correlation included in the third reference information can be constructed, for example, by statistically analyzing data recorded by combining an actually occurring fault with a plant image, the occurrence date, the occurrence location, and the type of plant. The third reference information may also include a fault inference model (artificial intelligence) that has been previously subjected to machine learning.

[0108] <Points Management Department 239> The point management unit 239 is configured to give points that can be exchanged for products or services to a user who has received a consultation from the consultation reception unit 232. This makes it possible to give an incentive to the user for inputting a consultation, and to stimulate communication in the agricultural support service provided by the information processing device 2.

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

[0110] Furthermore, the point management unit 239 accepts an exchange of points for goods or services from the user. Examples of exchangeable goods or services include goods handled by the organization to which the respondent belongs, and service coupons that can be used at the organization. When an instruction to exchange points is accepted from a user, the point management unit 239 causes the user terminal 3 to execute, for example, displaying a website for exchanging points. When the exchange of points is completed, the point management unit 239 subtracts 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 an instructed output. The artificial intelligence used by each functional unit of the information processing device 2 may be a common one, or may be prepared individually for each functional unit.

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

[0113] The artificial intelligence unit 240 has a trained model constructed by 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). The training data is composed of a pair of input data for learning and output data (correct answer data). The learning model included in the artificial intelligence unit 240 can perform additional learning as transfer learning or fine tuning using new data acquired from the user terminal 3 or the like.

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

[0115] First Embodiment The agricultural support method of the first embodiment includes a consultation receiving step, a response receiving step, and a map display control step. In the consultation receiving step, a consultation is received from a user terminal 3. In the response receiving step, the consultation is transferred to a primary respondent terminal 4A of a primary respondent selected from among the respondents assigned according to the location of the habitat 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 including polygons indicating the habitat of the plant and communication information associated with the polygons is displayed.

[0116] 9 is an activity diagram showing the flow of information processing (consultation response processing) executed by the agriculture support system 1. In the following, the information processing will be described along with each activity in this activity diagram.

[0117] The consultation response process starts when a user inputs a consultation about plant growth in the user terminal 3 (activity A110). The information processing device 2 (processor 23) accepts the consultation by receiving data indicating the consultation content from the user terminal 3 (activity A120). After accepting the consultation, the information processing device 2 transfers the consultation to the respondent terminal 4 (primary respondent terminal 4A) (activity A130).

[0118] The answerer to whom the consultation has been transferred inputs an answer in the answerer terminal 4 (activity A140). The information processing device 2 accepts the answer by receiving data indicating the content of the answer from the answerer terminal 4 (activity A150). If no answer is input from the answerer terminal 4, the information processing device 2 transfers the consultation to another answerer terminal 4 (secondary answerer terminal 4B) and accepts the answer from that answerer terminal 4.

[0119] After receiving the answer, the information processing device 2 outputs the answer to the user terminal 3 that performed the consultation, and upon request from the user terminal 3, outputs a polygon map that reflects the history of the consultation as communication information to the user terminal 3 (activity A160). As a result, the answer to the consultation and the polygon map are appropriately displayed on the user terminal 3 (activity A170).

[0120] <Second embodiment> The agricultural support method of the second embodiment includes a forecast value display control step in which time-series data including forecast values ​​indicating the possibility of damage occurring to plants at each of a plurality of forecast time points from the current time onward and average year values ​​of the forecast values ​​at each of the plurality of forecast time points are displayed.

[0121] 10 is an activity diagram showing the flow of information processing (forecast value display processing) executed by the agriculture support system 1. Below, the information processing will be described along with each activity of this activity diagram.

[0122] The forecast value display process starts when a user inputs the type and habitat of a plant for which the user wishes to check the forecast value into the user terminal 3 (activity A210). The information processing device 2 (processor 23) acquires the forecast value and the average year value corresponding to the plant and habitat input from the user terminal 3 from the database (activity A220). If the forecast value for the specified plant and habitat has not been calculated, the information processing device 2 calculates the forecast value. After acquiring the forecast value, the information processing device 2 outputs time series data including the forecast value and the average year value to the user terminal 3 (activity A230). As a result, the time series data is displayed on the user terminal 3 (activity A240).

[0123] <Third embodiment> The agricultural support method of the third embodiment includes an image acquiring step and a damage inferring step. In the image acquiring step, an image for inference including a plant is acquired. In the damage inferring step, a damage occurrence state in the plant is inferred based on the image for inference, a forecast value at the time when the image for inference was acquired, and reference information.

[0124] 11 is an activity diagram showing the flow of information processing (fault inference processing) executed by the agricultural support system 1. The information processing will be described below along with each activity in this activity diagram.

[0125] The fault inference process is started when the user inputs information such as an image of a plant for which the occurrence of a fault is to be confirmed in the user terminal 3 (activity A310). The information processing device 2 (processor 23) accepts the image input from the user terminal 3 and acquires the corresponding forecast value from the database (activity A320). After acquiring the image and the forecast value, the information processing device 2 determines whether the forecast value is equal to or greater than a lower limit (activity A330). If the forecast value is equal to or greater than the lower limit, the information processing device 2 infers the occurrence of a fault using a fault inference model or the like (activity A340). On the other hand, if the forecast value is less than the lower limit, the information processing device 2 infers that no fault has occurred and skips activity A340. After inferring the fault, the information processing device 2 outputs the inference result to the user terminal 3 (activity A350). As a result, the fault inference result is displayed on the user terminal 3 (activity A360).

[0126] 4. Effect The operation of this embodiment can be summarized as follows: That is, by using the forecast value indicating the possibility of damage to the plant, various information can be provided to the user.

[0127] Although the embodiment of the present invention has been described above, the present invention is not limited to this, and can be modified as appropriate without departing from the technical concept of the invention.

[0128] 5.Other In the above embodiment, the information processing device 2 performs various storage and control, but multiple external devices may be used instead of the information processing device 2. That is, various information and programs may be distributed and stored in multiple external devices using block chain technology or the like.

[0129] The aspect of the present embodiment is not limited to the agriculture support system 1, and may be an agriculture support method or a program. The agriculture support method includes each step of the agriculture support system 1. The program causes a computer to function as the agriculture support system 1.

[0130] The agriculture support system 1 does not necessarily have to include the consultation receiving unit 232, the answer receiving unit 233, the map display control unit 236, and the point management unit 239.

[0131] It may be provided in any of the following ways:

[0132] (1) An agricultural support system comprising a processor configured to execute each of the following steps by reading a program, wherein a forecast value display control step displays time series data including forecast values ​​indicating the possibility of damage to plants at each of a plurality of forecast time points from the current time onwards, and average annual values ​​of the forecast values ​​at each of the plurality of forecast time points.

[0133] (2) In the agricultural support system described in (1) above, in the forecast value display control step, a figure indicating the magnitude of the forecast value and a figure indicating the magnitude of the average value are displayed in contrast to each other at each of the multiple forecast time points of the time series data.

[0134] (3) In the agricultural support system described in (1) or (2) above, in the forecast value display control step, a notification is output when a value obtained by subtracting the normal year value from the forecast value is equal to or greater than a predetermined threshold value.

[0135] (4) In the agricultural support system described in any one of (1) to (3) above, in the forecast value display control step, information indicating that the forecast value is higher or lower than the normal year value is displayed.

[0136] (5) In the agricultural support system described in any one of (1) to (4) above, the processor is configured to further execute the following steps: in the image acquisition step, an image for prediction including a plant is acquired; and in the damage prediction step, a damage occurrence status in the plant is predicted based on the image for prediction, the forecast value at the time when the image for prediction was acquired, and reference information; wherein the reference information includes a correlation between the image for prediction and the forecast value, and the damage occurrence status.

[0137] (6) An agricultural support system comprising a processor configured to execute each of the following steps by reading a program, wherein an image acquisition step acquires an image for prediction including a plant, and a damage inference step infers a damage occurrence status in the plant based on the image for prediction, a forecast value at the time when the image for prediction was acquired, and reference information, wherein the forecast value indicates the possibility of damage occurring to the plant, and the reference information includes a correlation between the image for prediction and the forecast value, and the damage occurrence status.

[0138] (7) In the agricultural support system described in (5) or (6) above, the reference information includes a lower limit value of the forecast value for determining whether or not a fault has occurred, and a fault prediction model that has been trained to be able to input the image for prediction and output the type of fault, and in the fault prediction step, if the forecast value is below the lower limit value, it is predicted that no fault has occurred, and if the forecast value is equal to or greater than the lower limit value, the type of fault that has occurred is predicted by inputting the image for prediction into the fault prediction model. Of course, this is not the case.

[0139] Finally, although various embodiments according to the present disclosure have been described, these are presented as examples and are not intended to limit the scope of the invention. The novel embodiment can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. The embodiments and their modifications are included within the scope and spirit of the invention, and are included in the scope of the invention and its equivalents described in the claims. [Explanation of symbols]

[0140] 1: Agricultural support system 2: Information processing equipment 3: User terminal 4: Respondent's device 4A: Primary respondent terminal 4B: Secondary respondent terminal 20: Communication bus 21: Communications Department 22: Storage section 23: Processor 30: Communication bus 31: Communications Department 32: Storage section 33: Processor 34: Output section 35: Input section 40: Communication bus 41: Communications Department 42: Storage section 43: Processor 44: Output section 45: Input section 231: Registration Department 232: Consultation Reception Department 233: Answer Reception Department 234: Forecast Department 235: Forecast value display control unit 236: Map display control unit 237: Image acquisition unit 238: Fault prediction section 239:Point Management Department 240: Artificial Intelligence Department AI: Respondent information AM: Reply message B11: Plant selection button B12: Report occurrence button B13: Measures input button CA: Communication display area CI:Consultant Information CI1: 1st communication icon CI2: Second communication icon CM: Consultation message DG: Risk Graph FA: Forecast value display area FB1: First forecast bar FB2: Second forecast bar FD: Forecast value display screen FI:Fault Image FN : Fault name HA: Heat map 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: Predicted area of ​​occurrence PA: Polygon map display area SA: Plant Selection Area

Claims

1. An agricultural support system, comprising: A processor is provided. The processor is configured to execute the following steps by reading the program: In the forecast value display control step, time series data including forecast values ​​indicating the possibility of damage occurring to plants at each of a plurality of forecast time points from the current time onwards and average annual values ​​of the forecast values ​​at each of the plurality of forecast time points are displayed, wherein the average annual value is an average value of the forecast values ​​at the same date and time for a plurality of years predicted in the past.

2. The agricultural support system according to claim 1, In the forecast value display control step, a figure indicating the magnitude of the forecast value and a figure indicating the magnitude of the average year value are displayed in contrast to each other at each of the multiple forecast time points of the time series data.

3. The agricultural support system according to claim 1, In the forecast value display control step, a notification is output when a value obtained by subtracting the normal year value from the forecast value is equal to or greater than a predetermined threshold value.

4. The agricultural support system according to claim 1, The agricultural support system, in the forecast value display control step, displays information indicating that the forecast value is higher or lower than the average year value.

5. An agricultural support system, comprising: A processor is provided. The processor is configured to execute the following steps by reading the program: In the forecast value display control step, time series data including forecast values ​​indicating the possibility of damage occurring to plants at each of a plurality of forecast time points from the current time point onward and average annual values ​​of the forecast values ​​at each of the plurality of forecast time points are displayed; In the image acquisition step, an image for estimation including a plant is acquired, An agricultural support system, in which in the damage prediction step, the occurrence status of damage in a plant is predicted based on the prediction image, the forecast value at the time the prediction image was acquired, and reference information, wherein the reference information includes a correlation between the prediction image and the forecast value, and the occurrence status of damage.

6. In the agricultural support system according to claim 5 , The reference information is a lower limit value of the predicted value for determining whether or not a fault has occurred; a fault prediction model that is trained so as to be able to input the prediction image and output a fault type; Including, In the fault prediction step, if the forecast value is below the lower limit value, it is predicted that no fault has occurred, and if the forecast value is equal to or greater than the lower limit value, the type of fault that has occurred is predicted by inputting the prediction image into the fault prediction model.

7. In the agricultural support system according to any one of claims 1 to 6, In the forecast value display control step, an object that accepts an input for reporting the occurrence of a fault or an input for reporting the implementation of measures against the fault is displayed together with the time-series data.

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