Information processing method, program and information processing device

Abstract

To improve plant cultivation results by appropriately introducing methods of exemplary farmers according to cultivation environment of each producer.SOLUTION: An information processing device causes an information processing device to: acquire first data relating to plant cultivation associated with each producer, the first data including environmental data relating to the cultivation environment; receive selection of one or a plurality of specific producers; classify the one or plurality of specific producers into one or plurality of first groups on the basis of the first data of the selected one or plurality of specific producers; and determine similarity between first data of a prescribed group out of the respective first groups and first data of each producer other than the one or plurality of specific producers on the basis of at least the environmental data.SELECTED DRAWING: Figure 12

Description

[Technical Field]

[0001] The present invention relates to an information processing method, a program, and an information processing device. [Background technology]

[0002] Conventionally, there are known techniques for providing guidance on cultivation methods to plant producers. For example, Patent Document 1 discloses that advice is given to each producer according to the production status of each producer (e.g., sugar content, acidity, size, leaf shape, etc.). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6341548 Summary of the Invention [Problem to be solved by the invention]

[0004] However, even if producers produce the same plant, if the cultivation environment is different, the cultivation method suitable for each producer may also differ. With the technology disclosed in Patent Document 1, similar advice is given to each producer in the same region, but the current situation is that they are not necessarily able to cultivate the plant appropriately. This is likely due to the large number of environmental parameters.

[0005] For example, there are many parameters, such as weather (temperature, humidity, weather, etc.) and soil (moisture, temperature, nutrients, geology, etc.), and the effects of these numerous parameters on growth, quality, and yield are extremely complex. To develop cultivation methods and provide agricultural guidance that take these effects into account, it is necessary to understand how each parameter affects quality, yield, and various timing. To do this, tests must be conducted to determine the degree of influence of each parameter. Alternatively, large amounts of training data are required, but the digitalization of information related to agricultural guidance is not yet advanced, and because plants take time to harvest, it will take time to collect large amounts of data now. Ultimately, each producer tries to imitate the materials and cultivation techniques of leading farmers in their region, but even if they adopt the same techniques as leading farmers, they may not necessarily be able to cultivate the same crops.

[0006] Therefore, the disclosed technology aims to provide a system that appropriately incorporates the techniques of competent farmers according to the cultivation environment of each producer, thereby improving plant cultivation results. [Means for solving the problem]

[0007] An information processing method that is one aspect of the disclosed technology includes an information processing device that acquires first data related to plant cultivation associated with each producer, the first data including environmental data related to the cultivation environment, accepts selection of one or more specific producers, classifies the one or more specific producers into one or more first groups based on the first data of the selected one or more specific producers, and determines, based at least on the environmental data, the similarity between the first data of a specific group within each first group and the first data of each producer other than the one or more specific producers. [Effects of the Invention]

[0008] According to the present invention, it is possible to improve the results of plant cultivation by appropriately incorporating the techniques of competent farmers according to the cultivation environment of each producer. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an example of a configuration of an information processing system according to an embodiment of the present disclosure. [Figure 2] FIG. 1 is a block diagram illustrating an example of a server according to an embodiment. [Figure 3] FIG. 2 is a diagram illustrating an example of each processing device according to an embodiment. [Figure 4] An example of first data according to an embodiment [Figure 5] FIG. 10 is a diagram showing an example of a cultivation schedule screen according to an embodiment; [Figure 6] FIG. 10 is a diagram showing an example of a screen for detailed explanation of a cultivation method according to an embodiment. [Figure 7] Screen for registering each piece of information [Figure 8] Screen for entering information about the field [Figure 9] Screen for entering information about an item [Figure 10] Screen with all information entered [Figure 11] Screen for inputting details of cultivation work [Figure 12] FIG. 10 is a sequence diagram illustrating an example of processing by an information processing apparatus and a server according to an embodiment. [Figure 13] A flowchart showing an example of a process related to cultivation guidance according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. The following embodiments are merely examples for explaining the present invention, and are not intended to limit the present invention to the embodiments. Furthermore, the present invention can be modified in various ways without departing from the spirit of the present invention. Furthermore, the same components in each drawing will be designated by the same reference numerals whenever possible, and redundant explanations will be omitted whenever possible.

[0011] <System Overview> Fig. 1 is a diagram illustrating an example of a configuration of an information processing system 1 according to an embodiment of the present disclosure. As shown in Fig. 1, the information processing system 1 includes a server 10, processing devices 20A, 20B, 20C, and 20D (hereinafter also referred to as "processing devices 20"), and a processing device 30, and the server 10, the processing devices 20, and the processing device 30 can transmit and receive data to and from each other via a network N. Furthermore, the number of servers 10, processing devices 20, and processing devices 30 may be any number.

[0012] The information processing system 1 provides plant producers with guidance on how to cultivate the plants (hereinafter also referred to as cultivation guidance). The plants include, but are not limited to, vegetables, fruits, or ornamental plants. For example, the plants may include plants classified as fruit trees, fruit vegetables, leafy vegetables, grains, and root vegetables.

[0013] The server 10 is a server that provides cultivation guidance. The server 10 acquires data related to plant cultivation from at least one of the processing devices 20 and 30, for example, via the network N. The server 10 executes the process described below using the acquired cultivation data, and transmits information related to cultivation methods to at least one of the processing devices 20 via the network N.

[0014] Each processing device 20 is an information processing device used by a plant producer. Each processing device 20 is, for example, a personal computer, a smartphone, a tablet terminal, etc. Each processing device 20 transmits data related to plant cultivation to the server 10, for example, via the network N. Furthermore, at least one of the processing devices 20 acquires information related to cultivation methods from the server 10, for example, via the network N, and outputs the information in a predetermined format.

[0015] The processing device 30 is an information processing device used by an organization related to plant producers. The organization is, for example, a JA (agricultural cooperative). The processing device 30 is, for example, a personal computer, a smartphone, a tablet terminal, etc. The processing device 30 transmits data related to cultivation by producers related to the organization to the server 10 via, for example, a network N.

[0016] The network N may be realized by, for example, a network such as the Internet or a mobile phone network, a LAN (Local Area Network), or a combination of these. The following describes in detail each component of the information processing system 1 that enables the present service to be executed.

[0017] <Server configuration> 2 is a block diagram illustrating an example of a server 10 according to one embodiment. The server 10 includes one or more processors (e.g., CPUs) 110, one or more network communication interfaces 120, a storage device (storage unit) 130, and one or more communication buses 150 for interconnecting these components.

[0018] The server 10 may optionally include a user interface 140. The user interface 140 includes a display and / or an input device (such as a keyboard and / or a mouse or some other pointing device).

[0019] The storage device 130 may be, for example, a high-speed random access memory (main storage device) such as a DRAM, an SRAM, or other random access solid-state storage device. Alternatively, the storage device 130 may be a non-volatile memory (auxiliary storage device) such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state storage devices. Alternatively, the storage device 130 may be a non-transitory computer-readable recording medium that stores programs and the like. Alternatively, the storage device 130 may be either a main storage device (memory) or an auxiliary storage device (storage), or may include both.

[0020] The storage device 130 stores data, programs, etc. used by the information processing system 1. For example, the storage device 130 stores first data (for example, FIG. 4) and the like, which will be described later.

[0021] Another example of storage device 130 may be one or more storage devices located remotely from processor 110. In some embodiments, storage device 130 stores programs, modules, and data structures, or a subset thereof, that are executed by processor 110.

[0022] The processor 110 executes a program stored in the storage device 130 to control, for example, the processing executed by the information processing unit 111.

[0023] The information processing unit 111 includes, for example, an acquisition unit 112, a reception unit 113, a classification unit 114, a determination unit 115, a matching unit 116, an output unit 117, and an extraction unit 118.

[0024] The acquisition unit 112 acquires data related to plant cultivation (hereinafter also referred to as "first data") associated with each producer, including environmental data related to the cultivation environment. The acquisition unit 112 acquires the first data of each producer from each processing device 20 used by the producer, for example, via the network N. The first data includes, for example, an ID for identifying the plant producer, the name of the producer, environmental data related to the environment for cultivating the plant, harvest data related to the harvest of the plant, and cultivation calendar data related to the cultivation activities performed by the producer at a specific time. A more detailed description of the first data will be given later.

[0025] The acquiring unit 112 may acquire the first data from the processing device 30 via, for example, the network N. The acquiring unit 112 may also read out the first data stored in the storage device .

[0026] The reception unit 113 receives the selection of one or more specific producers (hereinafter also referred to as "specific producers"). The reception unit 113 receives information regarding the selection of one or more specific producers from the processing device 30, for example, via the network N from the processing device 30. In this case, a user using the processing device 30 operates the processing device 30 to send information regarding one or more producers that satisfy predetermined conditions to the server 10. A producer that satisfies the predetermined conditions is, for example, a producer that produces plants whose quality (e.g., sugar content, acidity, size, etc.) and / or yield are higher than a predetermined threshold, and is referred to as a specific producer. In addition, specific producers may include producers known as wise farmers.

[0027] The receiving unit 113 may accept the selection of one or more specified producers based on the first data acquired by the acquiring unit 112. The receiving unit 113 may select one or more producers as specified producers, for example, based on harvest data included in the first data. The receiving unit 113 may select one or more producers as specified producers based on one or more pieces of information (e.g., quality and / or harvest volume, etc.) included in the harvest data if each piece of information satisfies a predetermined condition. More specifically, the receiving unit 113 may select as specified producers producers of plants whose quality (e.g., sugar content, acidity, size, etc.) and / or harvest volume are higher than a predetermined threshold. Producers other than specified producers are also referred to as "general producers."

[0028] The classification unit 114 classifies each of the selected specified producers into one or more first groups based on the first data of the selected specified producers. The classification unit 114 classifies each of the selected specified producers into one or more first groups, for example, by inputting the first data of each selected specified producer into a machine learning model that performs clustering. The classification unit 114 may associate the ID of each specified producer classified into a specific first group with information indicating that the specified producer belongs to the specific first group and store the associated information in the storage device 130. The classification method used by the classification unit 114 to classify each specified producer may be any method that can be used to classify the specified producers using the first data, and may be a method using all of the first data or a method using only part of the first data.

[0029] The determination unit 115 determines the similarity between the first data of a predetermined group among the first groups and the first data of each producer (each general producer) different from the one or more specific producers, based at least on the environmental data. For example, for each predetermined group among the first groups, the determination unit 115 determines the similarity between the first data including the environmental data of each specific producer belonging to the predetermined group and the first data including the environmental data of each general producer. As a specific example, the determination unit 115 may vectorize the first data and determine the similarity of the vectors, or may determine the mean square error of the corresponding data. For each predetermined group, the determination unit 115 associates each general producer whose similarity is higher than a threshold.

[0030] Furthermore, the determination unit 115 may, for example, calculate a score indicating the tendency of the cultivation environment of a specific producer belonging to a predetermined first group classified by the classification unit 114 from the environmental data of the specific producer. The determination unit 115, for example, determines the similarity between the first data of a general producer among the producers acquired by the acquisition unit 112 and the first data of the predetermined first group based on the calculated score. For example, if this similarity is higher than a predetermined threshold, the determination unit 115 determines that the cultivation environment of the general producer is similar to the cultivation environment of the first group.

[0031] By performing the above process, the similarity between the first data of the specific producer's group and the first data of general producers can be determined based at least on the environmental data, thereby determining which specific producer's group's cultivation environment the general producer's cultivation environment is similar to. As a result, it becomes possible to provide cultivation guidance to the general producer based on the cultivation method of the specific producer with a similar legal environment, thereby improving the cultivation results of the general producer.

[0032] The classification unit 114 may classify each producer (general producer) different from the specific producer into one or more second groups based on the similarity. For example, the classification unit 114 classifies one or more general producers whose cultivation environment is determined by the determination unit 115 to be similar to that of a specific first group into the same second group. For example, the classification unit 114 classifies general producers whose similarity is within a predetermined range into the same second group. The classification unit 114 may associate the ID of a general producer classified into a specific second group with information indicating that the general producer belongs to the specific second group and store the associated information in the storage device 130.

[0033] The matching unit 116 matches a predetermined group from each first group with one or more groups from the second group that are similar to the predetermined group. For example, the matching unit 116 matches the predetermined first data with a second group (also referred to as a "similar group") to which general producers whose cultivation environments have been determined by the determination unit 115 to be similar to the predetermined first group belong. For example, the matching unit 116 associates both the predetermined first group and the second group to which general producers whose cultivation environments have been determined to be similar to the predetermined first group belong. As a specific example, the matching unit 116 may associate the group IDs of the predetermined group in the first group with the similar group in the second group, or may associate information indicating matching with each specific producer in the predetermined group in the first group with the IDs of each producer in the similar group in the second group, and store the association in the storage device 130.

[0034] The above process makes it possible to group a specific producer with multiple general producers who have similar cultivation environments, and to provide the general producers in the group with the same cultivation guidance suited to their respective environments all at once.

[0035] The acquisition unit 112 may acquire activity information related to cultivation activities performed by a specific producer within a predetermined group of the first group. For example, the acquisition unit 112 acquires cultivation calendar data related to cultivation activities performed by a specific producer at a specific time from a processing device used by the specific producer belonging to the predetermined first group. As a non-limiting example, the cultivation calendar data includes the time when fertilizer was applied, the amount of fertilizer, the type of fertilizer, the time when watering was performed, the amount of water, the time when leaves were cut (pruning time), etc. The acquisition unit 112 may acquire the cultivation calendar data from the processing device 30. The acquisition unit 112 may also read previously accumulated cultivation calendar data from the storage device 130.

[0036] The output unit 117 outputs the activity information acquired by the acquisition unit 112 to an information processing device used by a producer included in a similar group of the second group matched with a predetermined group of the first group. The output unit 117, for example, outputs cultivation calendar data of a specific producer belonging to a predetermined group of the first group to a processing device used by a general producer belonging to a similar group matched with the predetermined group. The output unit 117 may, for example, transmit screen information for displaying the cultivation calendar data to the processing device via the network N or transmit a pop-up notification. The specific producer whose cultivation calendar data is output to the general producer may be the specific producer with the highest harvest data among the specific producers in the predetermined group. The output activity information may also be common activity information shared by all the specific producers in the predetermined group. The common activity information includes, for example, that the activity time is within a predetermined period (e.g., pruning time is within a predetermined period) and the activity content or amount related to the activity is within a predetermined range (e.g., the amount of watering is within a predetermined range).

[0037] Through the above process, general producers can easily confirm the appropriate cultivation method by receiving notification of the cultivation method used by a specific producer in a similar cultivation environment. As a result, general producers can improve the production capacity of plants by cultivating them based on the cultivation method.

[0038] The determination unit 115 may determine the similarity between the first data of each general producer and the first data of a specific producer based on each data selected by the classification unit 114. For example, the classification unit 114 may accept selection of specific data of interest from the first data of general producers and form second groups of general producers using the selected data. As a specific example, the classification unit 114 may select producers (or fields) that apply similar amounts of fertilizer, and the determination unit 115 may classify these general producers (or fields) into respective second groups. Furthermore, the classification unit 114 may select general producers (or fields) that produce high-ranked agricultural products, and the determination unit 115 may classify these general producers (or fields) into respective second groups.

[0039] The above process makes it possible to group general producers by focusing on specific data from the first data, thereby improving the classification accuracy of general producers. The improved classification accuracy makes it possible to provide more detailed cultivation guidance to specific producers.

[0040] The extraction unit 118 extracts predetermined activity information from the acquired activity information. For example, the extraction unit 118 extracts predetermined information from the cultivation calendar data acquired by the acquisition unit 112. As a non-limiting example, the extraction unit 118 extracts information regarding the time when fertilizer was applied from the cultivation calendar data that includes information regarding the time when fertilizer was applied and information regarding the time when watering was performed.

[0041] Before the processing of the extraction unit 118 is performed, the server 10 may acquire information specifying information included in the cultivation calendar data (hereinafter also referred to as "specified information"). For example, the server 10 acquires "the time when fertilizer was applied" from the processing device 30 as specified information. The extraction unit 118 may extract information regarding the time when fertilizer was applied from the cultivation calendar data based on the specified information.

[0042] The output unit 117 may output the behavior information extracted by the extraction unit 118 to an information processing device used by a producer included in the second group matched with the predetermined group of the first group.

[0043] By the above process, only the necessary cultivation calendar data can be output to the processing device used by general producers. For example, only the cultivation calendar data that an organization such as JA (agricultural cooperative) determines to be necessary can be output to the processing device used by general producers.

[0044] The acquiring unit 112 may acquire the first data for each type of plant. For example, the acquiring unit 112 acquires the first data regarding a specific plant. As a non-limiting example, when the server 10 provides cultivation guidance to producers of eggplants, tomatoes, and cucumbers, the acquiring unit 112 may acquire the first data for each of the eggplants, tomatoes, and cucumbers.

[0045] When the acquiring unit 112 acquires the first data for each type of plant, the accepting unit 113 may accept a selection of a specific producer for each type. Furthermore, when the acquiring unit 112 acquires the first data for each type of plant, the classifying unit 114 may classify the specific producers into a first group for each type. Furthermore, when the acquiring unit 112 acquires the first data for each type of plant, the classifying unit 114 may classify general producers into a second group for each type.

[0046] Through the above process, general producers can be matched with specific producers who cultivate the same or similar types of plants as the general producer, and can cultivate plants based on the cultivation methods of the same or similar specific producers.

[0047] The classification unit 114 may classify one or more specified producers into one or more first groups based at least on the environmental data. For example, the classification unit 114 may classify the one or more specified producers into one or more first groups by inputting at least the environmental data of the first data of the one or more specified producers into a machine learning model that performs clustering. As described above, the classification method is not particularly limited.

[0048] Through the above process, specific producers with similar environmental data can be classified into the same first group. As a result, general producers can receive cultivation guidance based on the cultivation methods of specific producers in the first group whose environmental data are similar to their own.

[0049] The classification unit 114 may classify the products into one or more first groups based on the environmental data, and then subdivide the groups based on data included in the first data other than the environmental data. For example, the classification unit 114 may first classify the products into a plurality of provisional groups using the environmental data included in the first data of a specific producer, and then further classify each provisional group based on data included in the first data other than the environmental data to form first groups.

[0050] The above processing makes it possible to classify specific producers with a focus on environmental data, and to match specific producers with each general producer while reducing the influence of environmental data.

[0051] The first data on cultivation may include data on plant cultivation for each of the producer's fields. A producer may have multiple fields, and since each field has different soil components and environmental data, it may be appropriate to manage the first data for each field.

[0052] When the first data is managed for each field of each general producer, the determination unit 115 may include determining the similarity of the first data of a predetermined group of the first group for each data related to the cultivation of plants in each field of each general producer.

[0053] Through the above process, when a general producer has multiple fields, it becomes possible to match each field with a specific producer, and even if the producer is the same, appropriate cultivation guidance can be provided for each field.

[0054] 3 is a diagram illustrating an example of each processing device 20 according to one embodiment of the disclosure. Each processing device 20 includes one or more processors (e.g., CPUs) 210, one or more network communication interfaces 220, a storage device (storage unit) 230, a user interface 240, and one or more communication buses 250 for interconnecting these components.

[0055] The user interface 240 includes a display 251 and an input device 252 (such as a keyboard and / or a mouse or some other pointing device).

[0056] The storage device 230 may be, for example, a high-speed random access memory (main storage device) such as a DRAM, an SRAM, or other random access solid-state storage device. Alternatively, the storage device 230 may be a non-volatile memory (auxiliary storage device) such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state storage devices. Alternatively, the storage device 230 may be a non-transitory computer-readable recording medium that stores programs and the like. Alternatively, the storage device 230 may be either a main storage device (memory) or an auxiliary storage device (storage), or may include both.

[0057] The storage device 230 stores data and programs used by the information processing system 1. For example, the storage device 230 stores application programs for each processing device 20 in the information processing system 1.

[0058] The processor 210 executes a program stored in the storage device 230 to configure an information processing unit 211. The information processing unit 211 includes, for example, a web browser and an email application.

[0059] The web browser enables browsing of web pages provided by the server 10 for inputting cultivation-related data or receiving cultivation guidance. The web browser appropriately displays and transitions between web pages, provides information, and transmits and receives data. For example, the web browser uses a web page to send a request set or input by a user to the information processing device 10. The transmitted information may be, for example, data related to plant cultivation.

[0060] The processor 210 may also execute installed client applications to enable the execution of functions provided by the server 10. The processor 210 has an information processing unit 211, which executes the functions of a platform that inputs data related to plant cultivation and provides plant cultivation guidance. The information processing unit 211 has a communication control unit 212, a display control unit 213, and an operation control unit 214.

[0061] The communication control unit 212 outputs first data related to plant cultivation to the server 10. The first data includes at least one of environmental data, cultivation data, and cultivation calendar data, which are shown in FIG. 4 and will be described later, and is input, set, or selected by the producer via the user interface 240. The communication control unit 212 also acquires screen information related to screen examples, which will be described later, from the server 10.

[0062] The display control unit 213 controls the display 251 to display various screens related to cultivation guidance and various screens that enable input, setting, or selection of first data, based on the screen information acquired by the communication control unit 212.

[0063] The operation control unit 214 receives user operations on UI widgets displayed on each screen, transmits operation information to an application of the processing device 20, or outputs the operation information to the server 10. For example, the operation control unit 214 may output first data or the like that has been input, set, or selected by a producer or the like to the server 10.

[0064] <Data example> Next, an example of the first data will be described. Fig. 4 is a diagram showing an example of the first data according to one embodiment.

[0065] The first data shown in FIG. 4 includes, by way of example and not limitation, various data / information such as "ID," "name," "environmental data," "cultivation data," "harvest data," and "cultivation calendar data."

[0066] "ID" includes, for example, identification information for identifying the producer of the plant. "Name" includes, for example, the name or nickname of the producer.

[0067] "Environmental data" includes, for example, "soil" and "climate." "Soil" includes, for example, the type and properties of the soil in which the plants are grown. "Climate" includes the type of climate in which the plants are grown. "Climate" may include, for example, the temperature, precipitation, humidity, etc. in which the plants are grown. "Environmental data" may also include information indicating the region in which the plants are grown.

[0068] The "cultivation data" includes, for example, the "item" and "variety" of a plant. The "item" is, for example, the type of vegetable. The "variety" is, for example, the individual vegetables that make up the "item."

[0069] "Harvest data" includes, for example, the "quality" and "harvest yield" of plants harvested at a specific time. "Quality" includes, for example, information regarding sugar content, acidity, size, etc. Furthermore, the information may be qualitative information such as "high sugar content" or quantitative information such as "sugar content is 15." "Harvest yield" is information indicating the yield of plants harvested at a specific time. The information may be qualitative information such as "high yield" or quantitative information such as "harvest yield is 1250 kg."

[0070] The "cultivation calendar data" includes, for example, information about the cultivation practices of a producer, such as the time when fertilizer was applied, the amount of fertilizer, the type of fertilizer, the time when watering was performed, the amount of water, the time when leaves were cut, etc. The cultivation calendar data includes, for example, information about the cultivation practices of a specific producer, and may be used as a manual for general producers to improve their cultivation results.

[0071] Furthermore, if the same producer owns multiple fields, the first data may include environmental data, cultivation data, and harvest data for each field. Since the first data is data related to cultivation, it may also be referred to as cultivation-related data.

[0072] <Screen example> Next, an example of a screen related to cultivation guidance displayed on a processing device of a general producer will be described. Fig. 5 is a diagram showing an example of a cultivation schedule screen according to one embodiment. The screen shown in Fig. 5 displays, for example, a cultivation method based on cultivation calendar data of a specific producer.

[0073] In the example shown in Figure 5, the cultivation method that a general producer should follow in February 2024 is displayed on a calendar. The screen information of the screen shown in Figure 5 includes information indicating the cultivation method of a specific producer that has been determined to be similar. The screen information of the screen shown in Figure 5 is output by the output unit 117 of the server 10, received by the processing device 20 of the general producer, and is information that is displayed on the display 251 by the display control unit 213 of the processing device 20.

[0074] In the example shown in Figure 5, "Fertilization" is displayed in the boxes for February 5th and February 21st on the calendar. This allows general producers to confirm that they should apply fertilizer on February 5th and February 21st.

[0075] In the example shown in Figure 5, "Pruning" is displayed in the boxes for February 12th and 28th on the calendar. This allows general producers to confirm that they should make selections on February 12th and 28th.

[0076] In the example shown in FIG. 5, "Pesticides" is displayed in the boxes for February 9th and February 27th on the calendar. This allows general producers to confirm that they need to spray pesticides on February 9th and February 27th. Furthermore, "Fertilization," "Pruning," and "Pesticides" displayed on the screen shown in FIG. 5 are tappable buttons. For example, tapping "Fertilization" displayed in the box for February 5th will transition to the screen shown in FIG. 6.

[0077] FIG. 6 is a diagram showing an example of a screen for detailed explanation of a cultivation method according to one embodiment. In the example shown in FIG. 6, "Apply fertilizer A," "total amount 220 kg," and "amount per 10 are 120 kg" are displayed on the display 251. This allows a general producer to confirm the fertilizer and amount to be applied on February 5th, enabling cultivation based on the detailed cultivation method. In addition, in the example shown in FIG. 6, a photo or illustration of fertilizer A is displayed at the bottom of the screen.

[0078] Next, examples of screens on which the producer inputs each piece of information will be described with reference to Figures 7 to 11. Figure 7 shows a screen on which the producer registers each piece of information related to plant cultivation.

[0079] The producer inputs the date on which cultivation work will be performed in the input field C1 shown in Figure 7. In the example shown in Figure 7, "2022 / 04 / 25" is input in the input field C1. Any method may be used to input the work date, and for example, the date may be selected from a calendar.

[0080] The producer inputs information about the farm field into the input field C2 shown in Fig. 7. When the input field C2 is selected on the screen shown in Fig. 7, the screen transitions to the screen shown in Fig. 8.

[0081] FIG. 8 is a screen for inputting information about a farm field. For example, if a producer is cultivating eggplants, he or she selects the check box adjacent to "Eggplant" shown in FIG. 8. The producer also selects the environment in which the eggplants will be cultivated. In the example shown in FIG. 8, the check boxes for "Yamate 1," "Yamate 2," and "Kawayoko 3" are selected. The information selected in the example shown in FIG. 8 is information included in the environmental data.

[0082] Returning to Figure 7, the producer inputs information about the type of plant to be cultivated in the input field C3. When the input field C3 is selected on the screen shown in Figure 7, the screen transitions to the screen shown in Figure 9.

[0083] Figure 9 is a screen for entering information about an item. For example, if a producer is cultivating eggplants, he or she selects input field C4 and enters "eggplant" as the item name. The producer also selects input field C5 and enters "Senryo eggplant."

[0084] Fig. 10 shows a screen in which information has been entered into input fields C1 to C3. The producer can check the information they have entered on the screen shown in Fig. 10. When button B10 displayed at the bottom of the screen shown in Fig. 10 is selected, the screen transitions to the screen shown in Fig. 11.

[0085] FIG. 11 shows a screen for inputting the details of cultivation work to be performed by the producer. For example, the producer selects the details of the work to be performed on the date (April 25, 2022) entered in the input field C1 from the screen area D10. This allows the producer to register the details of the work along with each piece of information. The registered information is transmitted to the server 10 via the network N. The server 10 may store the information in the storage device 130 as the producer's cultivation data.

[0086] <Operation description> Next, a description will be given of the operation of the information processing system 1. Fig. 12 is a sequence diagram showing an example of processing related to matching with a specific producer according to one embodiment.

[0087] In step S11, the processing device 20 transmits first data of the producer to the server 10. The first data includes, for example, environmental data or cultivation data. The processing device 20 transmits, for example, the first data including environmental data related to the cultivation environment to the server 10.

[0088] In step S12, the processing device 30 transmits first data of the producer to the server 10. The first data includes, for example, harvest data. Note that step S12 is not necessarily a necessary process.

[0089] In step S13, the processing device 30 transmits information about the specific producer to the server 10. For example, the processing device 30 transmits information for identifying the specific producer to the server 10. Note that step S13 is not necessarily a necessary process.

[0090] In step S14, the reception unit 113 of the server 10 receives the selection of one or more specific producers. The specific producers can also be automatically selected by the server 10 using the harvest product data of the first data, for example.

[0091] In step S15, the classification unit 114 of the server 10 classifies the selected one or more specific producers into one or more first groups based on the first data of the selected one or more specific producers.

[0092] In step S16, the judgment unit 115 judges the similarity between the first data of a specific group among the first groups and the first data of each producer (each general producer) different from one or more specific producers, based at least on the environmental data.

[0093] In step S17, the general producers are classified into one or more second groups based on the similarities.

[0094] In step S18, a predetermined group from each of the first groups is matched with one or more groups from the second groups that are similar to the predetermined group.

[0095] By performing the above process, the similarity between the first data of the specific producer's group and the first data of general producers can be determined based at least on the environmental data, thereby determining which specific producer's group's cultivation environment the general producer's cultivation environment is similar to. As a result, it becomes possible to provide cultivation guidance to the general producer based on the cultivation method of the specific producer with a similar legal environment, thereby improving the cultivation results of the general producer.

[0096] FIG. 13 is a flowchart illustrating an example of a process related to cultivation guidance according to an embodiment.

[0097] In step S21, the acquisition unit 112 of the server 10 acquires activity information related to cultivation activities by a specific producer in a predetermined group of the first group. The specific producer is, for example, a specific producer in the predetermined group whose harvest data has the highest evaluation.

[0098] In step S22, the server 10 makes settings related to notification of the acquired activity information. The extraction unit 118 of the server 10, for example, extracts the time period of each activity information from the acquired activity information. The server 10, for example, sets each extracted time period as information of a notification point to be notified to the producer's processing device. The notification point is, for example, information indicating the time period of each activity, such as fertilization, pruning, and pesticide application, as shown in FIG. 5.

[0099] In step S23, when the notification point arrives, the output unit 117 of the server 10 outputs the action information corresponding to the notification point to the processing device used by each producer included in the group of the second group matched with the specified group of the first group.

[0100] In step S24, the acquisition unit 112 of the server 10 acquires data related to cultivation. For example, the acquisition unit 112 of the server 10 acquires data indicating the details of the cultivation activity from a processing device used by a general producer who received cultivation guidance at each notification point.

[0101] Through the above process, it will be possible to provide general producers with cultivation guidance at an appropriate time based on the cultivation methods of specific producers who have similar legal circumstances, thereby improving the cultivation results of general producers.

[0102] It should be noted that the order of the processes shown in Figures 12 and 13 can be changed, other processes can be inserted, or certain processes can be deleted, without departing from the spirit of the disclosed technology.

[0103] Although one embodiment of the present disclosure has been described above in detail, it is not limited to the above embodiment, and various modifications and variations are possible within the scope of the claims. For example, in the present disclosure, some of the processes performed by each of the information processing devices 10, 20, and 30 may be transferred to another information processing device, multiple information processing devices may be integrated as appropriate, or all processes may be performed by a single device. Furthermore, each of the information processing devices 10, 20, and 30 may be managed by a single organization or by different organizations. [Explanation of symbols]

[0104] 1...information processing system, 10...server, 20A to 20D...processing devices, 30...processing device, 110...processor, 111...information processing unit, 112...acquisition unit, 113...reception unit, 114...classification unit, 115...determination unit, 116...matching unit, 117...output unit, 118...extraction unit, 120...network communication interface, 130...storage device, 140...user interface, 150...communication bus, 210...processor, 211...information processing unit, 212...communication control unit, 213...display control unit, 214...operation control unit, 220...network communication interface, 230...storage device, 240...user interface, 250...communication bus, 251...display, 252...input device, B10...button, C1 to C5...input fields, D10...screen area, N...network

Claims

1. The information processing device acquiring first data relating to the cultivation of plants, the first data being associated with each producer, the first data including environmental data relating to the cultivation environment; accepting a selection of one or more particular producers; classifying the one or more selected specific producers into one or more first groups based on the first data of the one or more selected specific producers; determining a similarity between first data of a predetermined group among the first groups and first data of each producer other than the one or more specific producers based at least on the environmental data; An information processing method that performs the above.

2. classifying each of the different producers into one or more second groups based on the similarities; Matching the predetermined group among the first groups with a group similar to the predetermined group among the one or more second groups; The information processing method according to claim 1 , further comprising:

3. Acquiring activity information regarding cultivation activities by the specific producer in the predetermined group of the first group; outputting the behavior information to another information processing device used by a producer included in the second group matched with the predetermined group of the first group; The information processing method according to claim 2, further comprising:

4. Determining the similarity includes: The information processing method according to claim 2 , further comprising determining similarity based on selected data from the first data of each of the producers.

5. The information processing method according to claim 1 , wherein the acquiring step includes acquiring the first data for each type of plant.

6. The information processing method according to claim 1 , wherein the classifying into one or more first groups includes classifying based at least on the environmental data.

7. The information processing method according to claim 6, wherein classifying into one or more first groups includes subdividing the groups based on data contained in the first data other than the environmental data after classification based on the environmental data.

8. the first data includes data regarding the cultivation of plants in each field of the producer, The determination of the similarity includes: The information processing method according to claim 1 , further comprising determining a similarity between each of the data relating to the cultivation of plants in each of the fields of the producer and the first data of the predetermined group.

9. For information processing devices acquiring first data relating to the cultivation of plants, the first data being associated with each producer, the first data including environmental data relating to the cultivation environment; accepting a selection of one or more particular producers; classifying the one or more selected specific producers into one or more first groups based on the first data of the one or more selected specific producers; determining a similarity between first data of a predetermined group among the first groups and first data of each producer other than the one or more specific producers based at least on the environmental data; A program that executes the following.

10. acquiring first data relating to the cultivation of plants, the first data being associated with each producer, the first data including environmental data relating to the cultivation environment; accepting a selection of one or more particular producers; classifying the one or more selected specific producers into one or more first groups based on the first data of the one or more selected specific producers; determining a similarity between first data of a predetermined group among the first groups and first data of each producer other than the one or more specific producers based at least on the environmental data; An information processing device that executes the above.

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