Agricultural support system

Abstract

We provide an agricultural support system that can offer useful information based on predictions of potential problems. [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 forecast value acquisition step obtaining forecast values ​​indicating the likelihood of occurrence of a plurality of disorders occurring in plants, and the forecast display control step displaying a first disorder among the plurality of disorders in which at least one of the rate of change of the forecast value over time and the difference between the forecast value and the annual value of the forecast value is of a predetermined magnitude, distinguishing it from second disorders other than the first disorder.

Description

[Technical Field]

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

[0002] As disclosed in the following document, an apparatus for predicting disorders (pests and physiological disorders) occurring in plants (agricultural crops) using a learning model is known in the art. [Prior Art Documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Unexamined Patent Application Publication No. 2021-93957 [Summary of the Invention] [Problem to be Solved by the Invention]

[0004] Although the above-described apparatus can predict the occurrence of disorders, there is a need for a specific method of utilizing the prediction results.

[0005] In view of the above circumstances, the present invention is intended to provide an agricultural support system capable of providing useful information based on disorder occurrence prediction results. [Means for Solving the Problem]

[0006] According to one aspect of the present invention, there is provided an agricultural support system comprising a processor, wherein the processor is configured to execute the following steps by reading a program: in a forecast value acquisition step, forecast values indicating the occurrence probability of each of a plurality of disorders occurring in plants are acquired; and in a forecast display control step, a first disorder among the plurality of disorders, in which at least one of a temporal change rate of the forecast value and a difference between the forecast value and a normal-year value of the forecast value is equal to or greater than a predetermined magnitude, is displayed separately from a second disorder among the plurality of disorders which is other than the first disorder.

[0007] In this configuration, information about plant damage that users should be aware of can be provided to users using forecast values ​​indicating the likelihood of plant damage occurring. [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. [Figure 4] This block diagram shows the functions realized by the information processing device 2 (processor 23). [Figure 5] This figure shows an example of the failure prediction screen DD displayed on user terminal 3. [Figure 6] This figure shows a continuation of the fault prediction screen DD from Figure 5. [Figure 7] This is an activity diagram showing the flow of information processing (display of fault information) 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 trained model that has been pre-trained to learn the correlation between input and output, or a generative AI such as a large-scale language model or visual 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 combining at least a suitable combination of circuits, circuits, processors, and memory. The processor may be a general-purpose processor or a dedicated circuit. In other words, it includes application-specific integrated circuits (ASICs), programmable logic devices (for example, simple programmable logic devices (SPLDs), complex programmable logic devices (CPLDs), and field programmable gate arrays (FPGAs)), etc.

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

[0015] <Agricultural Support System 1> FIG. 1 is a configuration diagram illustrating the agricultural support system 1. The agricultural support system 1 provides services including provision of pesticide spraying schedules and prediction of pest / disease outbreaks for a plurality of users.

[0016] The agricultural support system 1 comprises an information processing device 2 and a plurality of user terminals 3. The information processing device 2 and the user terminals 3 are configured to be communicable with each other via a telecommunication line.

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

[0018] <Information Processing Device 2> FIG. 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 inside the information processing device 2 via the communication bus 20.

[0019] <Communication Unit 21> Although the communication unit 21 is preferably a wired communication means such as USB, IEEE 1394, Thunderbolt (registered trademark), or wired LAN network communication, it may optionally include wireless LAN network communication, mobile communication such as LTE / 5G, and BLUETOOTH (registered trademark) communication as required. That is, it is more preferable to implement the communication unit as a set of the plurality of communication means described above. That is, the information processing device 2 may communicate various types of information from the outside via the communication unit 21 and a network.

[0020] <Storage Unit 22> The storage unit 22 stores various information defined by the foregoing description. For example, the storage unit 22 may be implemented as a storage device such as a solid state drive (SSD) that stores various programs related to the information processing apparatus 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 program operations. The storage unit 22 stores various programs, variables, and the like related to the information processing apparatus 2 executed by the processor 23.

[0021] <Processor 23> The processor 23 performs processing and control for overall operations related to the information processing apparatus 2. The processor 23 is, for example, a central processing unit (CPU). The processor 23 implements various functions related to the information processing apparatus 2 by reading a predetermined program stored in the storage unit 22. That is, information processing by software stored in the storage unit 22 is specifically implemented by the processor 23, which is an example of hardware, so that the processor 23 can be executed as each functional unit included therein. These will be described in further detail in the next section. Note that the number of the processor 23 is not limited to one, and the information processing apparatus 2 may include a plurality of processors 23 for each function. Further, the information processing apparatus 2 may have a configuration in which these are combined.

[0022] The information processing apparatus 2 may be in an on-premise form or a cloud form. As the cloud-form information processing apparatus 2, for example, the above-described functions and processes 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. As shown in Figure 3, 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 descriptions of the communication unit 31, storage unit 32, and processor 33 are the same as the descriptions of each part in the information processing device 2 and are 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] 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.

[0027] 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 forecast unit 232, a forecast value acquisition unit 233, a forecast display control unit 234, a report reception unit 235, a notification unit 236, and an artificial intelligence unit 240.

[0028] <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 plants (crops) being cultivated, the managed growing area (address of the field), the inventory of pesticides held, and the history of pesticide application, 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 the user includes employees of farmers or companies, one growing area may be shared among multiple users in the user data.

[0029] <Forecast Section 232> The forecasting unit 232 is configured to forecast the likelihood of damage occurring to plants. Specifically, the forecasting unit 232 calculates a forecast value indicating the likelihood of damage based on forecasting conditions, including the predicted date and time, the type of plant, and the plant's growing area, as well as first reference information.

[0030] The disorders for which the forecasting unit 232 calculates forecast values ​​include diseases, pests, and physiological disorders. Physiological disorders include deficiencies of components such as magnesium and calcium, water shortages, excess or deficiency of fertilizer, high-temperature damage, low-temperature damage, sunburn, and root damage. The forecasting unit 232 also predicts the likelihood of a disorder occurring (i.e., the forecast value) for each "type of disorder" for each "type of plant." "Type of plant" is a category that indicates varieties such as strawberries, radishes, onions, broccoli, and cabbage. Furthermore, "type of plant" may be subdivided by subcategories such as varieties like "Sonic" and "Neo Earth" for crops such as onions, and harvest days such as "early-maturing" and "mid-maturing." "Type of disorder" is a disease name such as sooty mold and black rot, a pest name such as armyworms and aphids, or a physiological disease phenomenon name such as magnesium deficiency and water shortage.

[0031] The forecast values ​​may indicate the probability of occurrence on a daily basis, on a multi-day basis, on a weekly basis, or on a monthly basis.

[0032] The first reference information includes the correlation between forecast conditions and the forecast values ​​for each fault, 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 actually occurring faults with the occurrence conditions. The first reference information may also include a forecast value calculation model (artificial intelligence) that has been pre-machine-trained. The forecast value calculation model is included in the artificial intelligence unit 240.

[0033] The forecast value calculation model is trained to take forecast conditions as input and output forecast values. When using such a forecast value calculation model, the forecasting unit 232 inputs the type of plant to be predicted, the region, and the date and time (including future dates and times) into the forecast value calculation model, and causes the model to output at least one possible problem and the probability (forecast value) of at least one problem occurring. The forecasting unit 232 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 forecast value calculation model. Examples of such forecast conditions include weather forecast values ​​up to several weeks in advance, average weather values ​​from the past few years, long-range forecasts of the average climate (information such as "slightly warmer than average" or "slightly rainier"), and average values ​​of forecast values ​​(risk of pest and disease occurrence) from the past few years.

[0034] The forecast value calculation model used by the forecasting unit 232 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 calculation power model, the parameters calculated and tuned through learning constitute the correlation of the first reference information.

[0035] The forecast values ​​calculated by the forecasting unit 232 are linked to input conditions (date and time, plant type, region, weather forecast values, etc.) and stored, for example, in the forecast value database of the storage unit 22.

[0036] <Forecast value acquisition unit 233> The forecast value acquisition unit 233 is configured to acquire forecast values ​​indicating the likelihood of occurrence of multiple problems that may occur in the plants being cultivated by the user. The forecast values ​​acquired by the forecast value acquisition unit 233 may be those predicted by the forecast unit 232 (i.e., those registered in the forecast value database of the storage unit 22), those registered in an external database, or those provided by the user through uploads, specifying a location on the network, etc.

[0037] The forecast value acquisition unit 233 may acquire multiple forecast values ​​indicating the likelihood of damage occurring to plants at each of several forecast time points from the present time onward. The forecast time points for the forecast values ​​acquired by the forecast value acquisition unit 233 are typically future dates and times, but may include the present time.

[0038] The forecast value acquisition unit 233 may further acquire the annual values ​​of the forecast values. The "annual values" are, for example, the average of the forecast values ​​for the same period for the same plant and the same region over multiple years (e.g., 5 years) that were previously predicted by the forecast unit 232, as stored in the forecast value database. The same period here may include, for example, a predetermined day (the same day), a predetermined few days (e.g., 3 days including the days before and after the same day), a predetermined week (the same week, or the week including the same day), or a predetermined month (the same month, or the month including the same day or week).

[0039] <Forecast display control unit 234> The forecast display control unit 234 is configured to display the forecast values ​​acquired by the forecast value acquisition unit 233 on the user terminal 3 along with the name of the problem, etc.

[0040] Specifically, the forecast display control unit 234 distinguishes a first fault from among the multiple faults (hereinafter referred to as forecast target faults) for which the forecast value acquisition unit 233 has acquired forecast values, where at least one of the rate of change of the forecast value over time and the difference between the forecast value and the annual value of the forecast value is of a predetermined magnitude, from the second faults other than the first fault, and displays it on the user terminal 3.

[0041] First-class disturbances are those among the forecastable disturbances for which a predicted risk of occurrence has been calculated, and whose risk of occurrence is increasing. Second-class disturbances are those whose risk of occurrence is lower than that of first-class disturbances. Second-class disturbances may also include disturbances whose predicted risk of occurrence is higher than that of first-class disturbances, but whose risk of occurrence is lower than that of first-class disturbances.

[0042] The "rate of change over time of the forecast value" is a numerical value that indicates the degree of increase in the forecast value (probability of occurrence), calculated from the forecast values ​​at multiple forecast points acquired by the forecast value acquisition unit 233. Specific examples include the difference between the maximum value and the minimum or average value of multiple forecast values ​​(daily units) over a predetermined period (e.g., one week), or the ratio obtained by dividing the difference between the maximum value and the minimum or average value of multiple forecast values ​​over a predetermined period by the minimum, maximum, or average value. The predetermined period here may include only points in the future from the present (e.g., the week starting tomorrow), or it may include both the present and future points in time (e.g., the week starting today), or it may include points in the past from the present, as well as the present and future points in time (e.g., the week starting two days ago).

[0043] "The difference between the forecast value and the annual value" refers to the difference or ratio between the forecast value and the annual value. The difference between the forecast value and the annual value is, for example, the value obtained by subtracting the annual value from the maximum, minimum, or average value of multiple forecast values ​​over a given period. The ratio between the forecast value and the annual value is, for example, the value obtained by dividing the maximum, minimum, or average value of multiple forecast values ​​over a given period by the annual value. Furthermore, "the difference between the forecast value and the annual value" may also refer to the difference between the forecast value for a specific day and the annual value for the corresponding day.

[0044] Furthermore, the annual values ​​used for comparison with the forecast values ​​do not necessarily have to be the same date and time as the forecast values, as long as they are annual values ​​for the same period as the forecast values. For example, if the forecast values ​​are given on a daily basis, the annual values ​​used to calculate the difference may be the average of the forecast values ​​for a period that includes the same month and day as the forecast values ​​(for example, one week).

[0045] The forecast display control unit 234 determines a forecast target fault as a first fault if, for example, the rate of change over time of the forecast value is equal to or greater than a predetermined first threshold (for example, a value such as "10%" or "20%" when the forecast value is shown between 0% and 100%), or if the difference between the forecast value and the average value is equal to or greater than a predetermined second threshold (for example, a value such as "20%" when the forecast value is shown between 0% and 100%).

[0046] The forecast display control unit 234 may determine the first disruption using only the rate of change over time of the forecast value (i.e., regardless of the magnitude of the difference between the forecast value and the average value), or it may determine the first disruption using only the difference between the forecast value and the average value (i.e., regardless of the magnitude of the rate of change over time of the forecast value).

[0047] Furthermore, the forecast display control unit 234 may determine a forecast target disturbance as a first disturbance if both the rate of change over time of the forecast value and the difference between the forecast value and the average value are of a predetermined magnitude. For example, the forecast display control unit 234 may determine a forecast target disturbance as a first disturbance if the rate of change over time of the forecast value is greater than or equal to a predetermined first threshold, and the difference between the forecast value and the average value is greater than or equal to a predetermined second threshold.

[0048] Furthermore, the forecast display control unit 234 may determine a forecast target disturbance as a first disturbance if at least one of the rate of change over time of the forecast value and the difference between the forecast value and the annual value is of a predetermined magnitude, and the value of the forecast value itself is of a predetermined magnitude. For example, the forecast display control unit 234 may determine a forecast target disturbance as a first disturbance if the rate of change over time of the forecast value is greater than or equal to a predetermined first threshold, and the representative value (maximum value, minimum value, or average value) of the forecast value for a predetermined period is greater than or equal to a predetermined third threshold (for example, a value such as "40%" when the forecast value is shown between 0% and 100%).

[0049] Furthermore, the forecast display control unit 234 may additionally determine that a first fault is a fault whose rate of change over time of the forecast value or the difference between the forecast value and the annual value of the forecast value is not of a predetermined magnitude, and whose number of reported occurrences or the rate of increase in the number of reported occurrences is above a certain level. The "number of reported occurrences" is, for example, the number of fault occurrence reports received by the report reception unit 235 (described later) from multiple user terminals 3 during a predetermined period (for example, one week).

[0050] Examples of ways to distinguish the first defect from the second defect include adding additional information such as text or icons to the display information for the first defect (such as the name of the first defect) to indicate that it is the first defect (i.e., the risk of occurrence is increasing), decorating the display information for the first defect (e.g., font emphasis, coloring, bordering, etc.), separating the area where the display information for the first defect is placed from the area where the display information for the second defect is placed, and prioritizing the display of the first defect over the second defect (a form in which more information about the first defect is displayed than the information about the second defect). Alternatively, as one way to distinguish the first defect from the second defect, the display information for the second defect may be omitted, and a defect display screen containing only the display information for the first defect may be displayed on the user terminal 3.

[0051] The forecast display control unit 234 may display the first fault in a specific area indicating that it is the first fault, and may also display the second fault in a general area outside the specific area. This allows the user to check all first faults with an increasing risk of occurrence at once. In addition, the user can also check second faults with an increasing risk of occurrence along with the first fault.

[0052] The specific area is positioned above the general area on the screen displayed on the user terminal 3, for example. In this case, the forecast display control unit 234 displays the first fault above the second fault on the screen. The specific area may also be positioned to the left or right of the general area.

[0053] In the specific area and the general area, the display information for the first and second defects are displayed in lists. The specific area and the general area may or may not have a boundary line. In addition, the specific area may or may not display a title or icon indicating that it is a specific area (where the risk of occurrence is increased). Similarly, the general area may or may not display a title or icon indicating that it is a general area.

[0054] The forecast display control unit 234 may, for example, display first-order hazards in a specific area such that the first-order hazard with the highest priority parameter is given priority (for example, it appears higher in the list). Examples of priority parameters include the rate of change over time of the forecast value, the difference between the forecast value and the average value, and the representative value of the forecast value. For example, the forecast display control unit 234 may display multiple first-order hazards in a specific area in descending order of their rate of change over time of the forecast value, and if the rates of change over time are the same, it may display multiple first-order hazards in descending order of the difference between the forecast value and the average value.

[0055] The forecast display control unit 234 may display the first fault in a specific area, and also display the first and second faults in a general area. This allows the system to present the user with faults whose risk of occurrence is increasing in the specific area, while simultaneously presenting the user with a list of faults whose probability of occurrence is predicted (for which a forecast value has been calculated) in the general area. As a result, the user can understand which faults have an increasing risk of occurrence while knowing what faults are predicted to occur, thereby increasing the user's confidence in the fault forecast results.

[0056] The forecast display control unit 234 may display multiple faults in the general area, regardless of the type of first fault or second fault, in an order based on the magnitude of the forecast value. This allows faults with an increasing risk of occurrence to be displayed in the specific area, while faults sorted based on the magnitude of the fault's forecast value, regardless of the increase in the risk of occurrence, are displayed in the general area. As a result, the user can obtain two types of information (fault information based on the increase in the risk of occurrence and fault information based on the risk of occurrence itself) from a single screen. Therefore, it becomes easier for the user to consider the priority of countermeasures against faults.

[0057] Specifically, the forecast display control unit 234 displays the display information for the first and second faults in the general area, for example, so that the first or second fault with the larger minimum, maximum, or average value of the forecast value for a predetermined period is given priority (for example, it appears higher in the list).

[0058] Furthermore, the forecast display control unit 234 may group the first and second hazards according to the range of magnitude of the forecast value (level indicating the magnitude of the risk of occurrence) in the general area, and display the display information for the first and second hazards for each group.

[0059] Furthermore, the forecast display control unit 234 may display the first and second hazards separately in the general area. Alternatively, the forecast display control unit 234 may display only the second hazard among multiple forecastable hazards in the general area without displaying the first hazard.

[0060] The forecast display control unit 234 displays the names of the first and second obstacles, and may also display detailed information about the first obstacle, which is not displayed for the second obstacle, along with its name. This makes the first obstacle stand out by displaying detailed information and allows the user to see the details of the first obstacle, thereby improving user convenience.

[0061] Detailed information that is displayed only for the first type of ailment (i.e., included in the information displayed for the first type of ailment but not for the second type of ailment) includes, for example, forecast values, average values ​​of forecast values, images showing the ailment, and pesticides effective against the ailment.

[0062] In this embodiment, "agricultural chemicals" refers to agents used to control diseases or pests (fungicides, insecticides, herbicides, etc.) and agents used to improve physiological disorders (enhance or suppress physiological functions) (growth promoters, germination inhibitors, etc.).

[0063] The forecast display control unit 234 may display time-series data on the user terminal 3 as detailed information to be displayed only for the first fault, including the forecast values ​​for each of the multiple forecast time points from the present time onward, and the average values ​​of the forecast values ​​for each of the multiple forecast time points. This allows the user to understand the change in the risk rate of the first fault occurring and the deviation from the average values, enabling them to systematically implement preventive measures against the first fault.

[0064] Multiple forecast points are set, for example, at equal intervals of one day each. The range of forecast points displayed by the forecast display control unit 234 is, for example, within one week, but may be longer than one week depending on the forecast value calculation model used by the forecast unit 232, the accuracy of the weather forecast, etc.

[0065] The range of time series data forecasts (the display period for forecast values) and the period of forecast values ​​used to determine the first wave of an emergency should be the same. This increases the correlation between the displayed time series data and the determination of the first wave of an emergency. For example, if the range of time series data forecasts is 6 days, the first wave of an emergency is determined by the rate of change over time calculated from the forecast values ​​for these 6 days, or by the difference between the forecast values ​​for these 6 days and the average values.

[0066] The time-series data displayed on the user terminal 3 by the forecast display control unit 234 is generated for each plant species and region. That is, all 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 may be numerical values ​​or graphical representations such as graphs. For example, the forecast display control unit 234 may display a graphical representation showing the magnitude of the forecast value and a graphical representation showing the magnitude of the average value for each of the multiple forecast points in the time-series data, in comparison.

[0067] The forecast display control unit 234 may display information about the first hazard, including detailed information, in a specific area. That is, the forecast display control unit 234 may display the name and detailed information (e.g., time-series data) of the first hazard within the specific area. Also, when the forecast display control unit 234 displays the first hazard in the general area, it does not have to display the detailed information of the first hazard in the general area. For example, the forecast display control unit 234 may display the first hazard and the second hazard in the general area with the same amount of information (e.g., in a form that includes only the name and image of the hazard).

[0068] The forecast display control unit 234 may also display spraying suitability information, which indicates the degree of appropriateness of pesticide spraying on a daily basis, along with time-series data. This allows the user to plan a pesticide spraying schedule based on the likelihood of the first problem occurring and the degree of appropriateness of pesticide spraying.

[0069] The suitability of pesticide application is a numerical value that indicates the physical ease of application of pesticides, for example, based on weather forecast values. For example, on rainy or snowy days, or on windy days, the suitability of pesticide application is judged to be low.

[0070] The forecast display control unit 234 calculates the suitability for pesticide application based on the weather forecast values ​​and the second reference information. The second reference information includes the correlation between the weather forecast values ​​and the suitability for pesticide application, and is stored, for example, in the memory unit 22. The second reference information may also include, for example, a table, function, simple algorithm, etc., that shows the correlation between features extracted from the weather forecast values ​​and the suitability for pesticide application. The correlation included in the second reference information can be constructed, for example, by statistically analyzing data recorded by combining weather conditions and the suitability for pesticide application. The second reference information may also include a suitability calculation model (artificial intelligence) that has been pre-machine-trained. The suitability calculation model is included in the artificial intelligence unit 240.

[0071] The spraying suitability information may be, for example, a numerical value, an indicator (level or rank), or an icon that represents the degree of suitability for pesticide application. The forecast display control unit 234 may, for example, display the spraying suitability information for each forecast day included in the time-series data of the predicted values ​​of the obstacle. Alternatively, the forecast display control unit 234 may display the spraying suitability information and the weather forecast information for that day (information showing predicted values ​​such as weather, temperature, and rainfall) for each forecast day included in the time-series data.

[0072] Figure 5 shows an example of the fault prediction screen DD displayed on user terminal 3. Figure 6 shows a continuation of the fault prediction screen DD from Figure 5. As shown in Figure 5, the fault prediction screen DD includes a first display area DA1 and a second display area DA2.

[0073] The first display area DA1 is the area where weather forecast information WI and spraying suitability information SI are displayed. In the first display area DA1, for example, weather forecast information WI for the same period as the time series data TD displayed for the first fault is displayed. Weather forecast information WI includes, for example, the date, forecast weather, maximum temperature, and minimum temperature. Spraying suitability information SI is displayed in a one-to-one correspondence with weather forecast information WI (i.e., on a daily basis). In the example in Figure 5, spraying suitability information SI is displayed as an icon indicating the suitability for pesticide spraying. In the example in Figure 5, it is shown that the 7th is highly suitable for pesticide spraying, while the 8th and 9th are unsuitable for pesticide spraying.

[0074] The second display area DA2 is the area where the risk level (predicted value) of damage (pests and diseases) is displayed. The second display area DA2 is located below the first display area DA1 in the damage prediction screen DD. As shown in Figures 5 and 6, the second display area DA2 includes the plant selection area PA, the specific area SA, and the general area GA.

[0075] The plant selection area PA contains multiple plant selection objects PO for selecting the type of plant whose fault information will be displayed in the second display area DA2. When an input operation is performed on a plant selection object PO, information about the fault that may occur in the plant corresponding to the selected plant selection object PO is displayed in the specific area SA and the general area GA. In the example in Figure 5, the plant selection object PO displays an image (icon) representing the plant, but the plant selection object PO may also display text representing the plant.

[0076] The specific area SA is the area where information about the first fault is displayed. In the example in Figure 5, information about multiple first faults is arranged vertically. The information about the first fault displayed in the specific area SA includes the fault name DN, the fault image DI, and the time-series data TD of the predicted value.

[0077] The time-series data TD consists of multiple first forecast value bars FB1 and multiple second forecast value bars FB2. 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 (5 days from now), calculated by the forecasting unit 232. 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 such that it approaches green as the forecast value is small and approaches red as the forecast value is high. The second forecast value bar FB2 is an object that shows the magnitude of the annual value of the forecast value for the date on which the first forecast value bar FB1 is displayed. In the example in Figure 5, the second forecast value bar FB2 is placed adjacent to the first forecast value bar FB1 for the corresponding date. Also, the second forecast value bar FB2 is colored in a different color from the first forecast value bar FB1.

[0078] The general area GA shown in Figure 6 is an area where information on first and second hazards is displayed together in a list. In the example in Figure 6, the general area GA includes the first group display area GDA1, the second group display area GDA2, the third group display area GDA3, the fourth group display area GDA4, and the fifth group display area GDA5. The first group display area GDA1 displays group information on first and second hazards at the "Alert" level, which has the highest forecast value. The second group display area GDA2 displays group information on first and second hazards at the "Caution" level, which has the next highest forecast value. The third group display area GDA3 displays group information on first and second hazards at the "Caution" level, which has an intermediate forecast value. The fourth group display area GDA4 displays group information on first and second hazards at the "Observe" level, which has a forecast value lower than the intermediate level. The fifth group display area GDA5 displays group information on first and second hazards at the "Low Risk" level, which has a forecast value of zero or close to zero.

[0079] In the general area GA of Figure 6, multiple fault indicator objects DO, each displaying information about the first or second fault, are shown within their corresponding group display areas. The fault indicator object DO displays only the fault name DN and fault image DI. In other words, the fault information displayed in the general area GA includes only the fault name DN and fault image DI.

[0080] Here, "Downy mildew," displayed in the first group display area GDA1, is the first defect, also displayed in the specific area SA in Figure 5. However, in the general area GA in Figure 6, only the defect name DN and defect image DI are displayed, similar to the second defects such as "Aphids." In other words, the amount of information displayed for the first defect in the general area GA is less than the amount of information displayed for both the first and second defects in the specific area SA. Furthermore, in the general area GA, the amount of information for the first defect and the second defect is the same, and the first and second defects are not distinguished when displayed.

[0081] Furthermore, when an input operation is performed on user terminal 3 for information on any fault in the specific area SA or general area GA, more detailed information about that fault (for example, a description of the fault, effective countermeasures, past occurrence history, past countermeasure (pesticide spraying) history, etc.) will be displayed on user terminal 3.

[0082] <Reporting Department 235> The reporting unit 235 is configured to receive reports of failures from the user terminal 3. The failures that the reporting unit 235 receives include both first and second failures.

[0083] The report receiving unit 235 receives reports of the occurrence of a fault, for example, by inputting an object (report button) for receiving fault reports, which is displayed for each of the multiple faults on the user terminal 3. The report button is displayed, for example, on the fault prediction screen DD that the forecast display control unit 234 displays on the user terminal 3.

[0084] <Notification section 236> The notification unit 236 is configured to notify other user terminals 3, separate from the user terminal 3 from which the report reception unit 235 received the report, of the occurrence of the first failure. In other words, when a user reports the occurrence of the first failure, the notification unit 236 sends a notification to the user terminals 3 of other related users indicating that the first failure has occurred. This allows users to quickly become aware of the occurrence of the first failure. "Other related users" are, for example, users whose managed growing areas are in the same region, or users who cultivate the same type of plant. The notification unit 236 notifies each user terminal 3 of the occurrence of the first failure, for example, in the form of a push notification.

[0085] <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.

[0086] 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.

[0087] 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.

[0088] 3. Information Processing Methods This section describes the information processing method of the information processing device 2. In this information processing method, the functions of each part of the information processing device 2 are executed as separate steps.

[0089] This information processing method comprises a forecast value acquisition step and a forecast display control step. In the forecast value acquisition step, forecast values ​​indicating the probability of occurrence of multiple disorders that occur in plants are acquired. In the forecast display control step, among the multiple disorders, a first disorder in which at least one of the rate of change of the forecast value over time and the difference between the forecast value and the average value of the forecast value is of a predetermined magnitude is displayed separately from the second disorder, which is a disorder other than the first disorder.

[0090] Figure 7 is an activity diagram showing the flow of information processing (display of fault information) performed by the agricultural support system 1. The following sections will explain the information processing according to each activity in this activity diagram.

[0091] The process of displaying fault information begins with the information processing device 2 (processor 23) calculating a forecast value indicating the likelihood of a fault occurring (Activity A110). After calculating the forecast value, the information processing device 2 acquires the calculated forecast value and information necessary for determining the first fault and displaying information about the first fault (such as average values) (Activity A120).

[0092] After obtaining forecast values, the information processing device 2 determines the first fault from among the multiple faults for which forecast values ​​have been obtained (Activity A130). After determining the first fault, the information processing device 2 outputs a fault prediction screen to the user terminal 3 that distinguishes between the first fault and the second fault (Activity A140). As a result, the fault prediction screen is displayed on the user terminal 3 (Activity A150).

[0093] 4. Effect The function of this embodiment can be summarized as follows: By using forecast values ​​that indicate the likelihood of plant damage occurring, information about damage that users should be aware of can be provided to the user.

[0094] 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.

[0095] 5. Other 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.

[0096] 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 execute each step of the agricultural support system 1.

[0097] If forecast values ​​are obtained from outside the agricultural support system 1, the agricultural support system 1 does not necessarily need to be equipped with a forecasting unit 232.

[0098] The product may be provided in any of the following embodiments.

[0099] (1) An agricultural support system comprising a processor, wherein the processor is configured to perform the following steps by reading a program, wherein in the forecast value acquisition step, a forecast value indicating the probability of occurrence of a plurality of disorders occurring in plants is acquired, and in the forecast display control step, a first disorder among the plurality of disorders, in which at least one of the rate of change of the forecast value over time and the difference between the forecast value and the annual value of the forecast value is of a predetermined magnitude is displayed separately from second disorders other than the first disorder.

[0100] (2) An agricultural support system as described in (1) above, wherein in the forecast display control step, the first fault is displayed in a specific area indicating that it is the first fault, and the second fault is displayed in a general area outside the specific area.

[0101] (3) An agricultural support system as described in (2) above, wherein in the forecast display control step, the first fault is displayed in the specific area and the first and second faults are displayed in the general area.

[0102] (4) In the agricultural support system described in (3) above, the forecast display control step displays the plurality of obstacles in the general area in an order based on the magnitude of the forecast value, regardless of the type of the first obstacle and the second obstacle.

[0103] (5) An agricultural support system according to any one of (1) to (4) above, wherein the forecast display control step displays the name of the first obstacle and the name of the second obstacle, and for the first obstacle, displays detailed information that is not displayed for the second obstacle, along with the name.

[0104] (6) An agricultural support system according to any of (1) to (5) above, wherein the processor is configured to further perform the following steps: in the report reception step, it receives a report of the occurrence of the first failure from a user terminal; and in the notification step, it notifies other user terminals of the occurrence of the first failure. Of course, this is not always the case.

[0105] 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]

[0106] 1: Agricultural support system 2: Information Processing Device 3: User 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 231: Registration Department 232: Forecasting Department 233: Forecast value acquisition unit 234: Forecast Display Control Unit 235: Reporting Department 236: Notification Department 240: Artificial Intelligence Department DA1: 1st display area DA2: 2nd display area DD: Fault prediction screen DI: Image of the fault DN: Name of the problem DO: Fault display object FB1: First forecast value bar FB2: Second forecast value bar GA: General area GDA1: First group display area GDA2: Second group display area GDA3: Third group display area GDA4: 4th group display area GDA5: Fifth group display area PA: Plant Selection Area PO: Plant Selection Object SA:Specific area SI: Application suitability information TD: Time series data WI: Weather forecast information

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 forecast value acquisition step, forecast values ​​indicating the likelihood of occurrence for each of several problems that can occur in plants are acquired. In the forecast display control step, the agricultural support system displays a first fault among the plurality of faults, where at least one of the rate of change of the forecast value over time and the difference between the forecast value and the annual value of the forecast value is of a predetermined magnitude, distinguishing it from the second faults other than the first fault among the plurality of faults.

2. In the agricultural support system described in claim 1, In the forecast display control step, the first fault is displayed in a specific area indicating that it is the first fault, and the second fault is displayed in a general area outside the specific area, in an agricultural support system.

3. In the agricultural support system described in claim 2, The agricultural support system, in the forecast display control step, displays the first fault in the specific area and displays the first and second faults in the general area.

4. In the agricultural support system described in claim 3, In the forecast display control step, the agricultural support system displays the multiple obstacles in the general area, regardless of the type of the first obstacle and the second obstacle, in an order based on the magnitude of the forecast value.

5. In the agricultural support system described in claim 1, In the forecast display control step, the agricultural support system displays the name of the first obstacle and the name of the second obstacle, and for the first obstacle, displays detailed information that is not displayed for the second obstacle, along with the name.

6. In the agricultural support system according to any one of claims 1 to 5, The aforementioned processor is configured to perform the following steps: In the reporting reception step, a report of the occurrence of the first failure is received from the user terminal. In the notification step, the agricultural support system notifies other user terminals of the occurrence of the first failure.

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