Data processing device, data processing method, and data processing program

Abstract

This invention provides a data processing device, a data processing method, and a data processing program that can streamline the distribution of products compared to conventional technologies. [Solution] The data processing device comprises an input unit 292 for acquiring user data, a processing unit 294 for performing specific processing using a data generation model that generates predetermined inference results according to the user data, and an output unit 296 for outputting the results of the specific processing to a predetermined device. The input unit 292 acquires image data showing an image of an area including the sales area of ​​the product at the sales outlet of the product as user data. The processing unit 294 performs the process of generating sales status information as specific processing by inputting a prompt to the data generation model instructing it to generate sales status information showing the sales status of the product at the sales outlet based on the user data. The output unit 296 outputs the sales status shown in the sales status information to the product producer's device.

Description

Technical Field

[0001] The technology of the present disclosure relates to a data processing device, a data processing method, and a data processing program.

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the prior art, there is room for improvement in terms of the efficiency of the distribution when applied to the distribution of products.

Means for Solving the Problems

[0005] A first aspect of the technology of this disclosure is a data processing device comprising: an input unit for acquiring user data; a processing unit for performing a specific processing using a data generation model that generates a predetermined inference result corresponding to the user data; and an output unit for outputting the result of the specific processing to a predetermined device, wherein the input unit acquires image data showing an image of an area including the sales area of ​​the product at a sales outlet for the product as the user data; the processing unit performs the process of generating the sales status information as the specific processing by inputting a prompt to the data generation model instructing it to generate sales status information showing the sales status of the product at the sales outlet based on the user data; and the output unit outputs the sales status shown in the sales status information to the device of the producer of the product.

[0006] A second aspect of the technology of this disclosure is a data processing method in which a computer performs a process to acquire user data, perform a specific processing using a data generation model that generates a predetermined inference result corresponding to the user data, and output the result of the specific processing to a predetermined device, wherein the user data is image data showing an image of an area including the sales area of ​​the product at a sales outlet for the product, and a prompt is input to the data generation model instructing it to generate sales status information showing the sales status of the product at the sales outlet based on the user data, thereby performing a process to generate the sales status information as the specific processing, and outputting the sales status shown in the sales status information to the device of the producer of the product.

[0007] A third aspect of the technology of this disclosure is a data processing program that causes a computer to execute a process which involves acquiring user data, performing a specific processing using a data generation model that generates a predetermined inference result corresponding to the user data, and outputting the result of the specific processing to a predetermined device, wherein the user data is image data showing an image of an area including the sales area of ​​the product at a sales outlet for the product, and a prompt is input to the data generation model instructing it to generate sales status information showing the sales status of the product at the sales outlet based on the user data, thereby performing a process to generate the sales status information as the specific processing, and outputting the sales status shown in the sales status information to the device of the producer of the product. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to an embodiment. [Figure 3] This is a schematic diagram showing an overview of a specific process according to the embodiment. [Figure 4] This is a block diagram schematically showing the functional configuration of the specific processing unit of the data processing device according to the embodiment. [Figure 5] This flowchart schematically shows an example of the operation flow of the first specific processing by the data processing device according to the embodiment. [Figure 6] This figure shows an example of a sales status screen (part 1) according to the embodiment. [Figure 7] This figure shows an example of a sales status screen (part 2) according to the embodiment. [Figure 8] This figure shows an example of a sales status screen (part 3) according to the embodiment. [Figure 9] This figure shows an example of a reservation completion screen according to the embodiment. [Figure 10] This flowchart schematically shows an example of the operation flow of the second specific processing by the data processing device according to the embodiment. [Figure 11] This flowchart schematically shows an example of the operation flow of the third specific processing by the data processing device according to the embodiment. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the data processing device, data processing method, and data processing program relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

[0011] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), or an APU (Accelerated Processing Unit).

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0013] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0014] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F controls communication between a plurality of computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when three or more matters are connected and expressed with "and / or", the same concept as "A and / or B" is applied.

[0016] FIG. 1 shows an example of the configuration of the data processing system 10 according to the embodiment. Hereinafter, the case where agricultural products are applied as the products of the present disclosure and a direct sales store of agricultural products is applied as the sales place of the present disclosure will be described.

[0017] As shown in FIG. 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. An example of the smart device 14 is a smartphone. In the present embodiment, the data processing device 12 is an example of the "data processing device" according to the technology of the present disclosure. The smart device 14 according to the present embodiment is owned by a user (in the present embodiment, a producer of agricultural products).

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of the "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. Also, the reception device 38, the output device 40, and the camera 42 are connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by contact of an indicator (e.g., a pen or a finger, etc.) by detecting the contact of the indicator. The microphone 38B receives user input by voice by detecting the voice of the user. A control unit 46A, which will be described later, transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, a specific processing unit 290, which will be described later, acquires data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0023] On the other hand, in this embodiment, the data processing system 10 has a webcam 82 connected to the network 54 that captures the area including the sales area of ​​the agricultural products at the aforementioned direct sales outlet for agricultural products. To avoid confusion, only one webcam 82 is shown in Figure 1, but in reality, a webcam 82 is provided for each of the sales areas of agricultural products at the direct sales outlets located at multiple locations targeted by the data processing system 10, and all webcams 82 are connected to the network 54. Therefore, the data processing device 12 can acquire image data obtained from all webcams 82 via the network 54.

[0024] As described above, this embodiment explains how to acquire image data showing an image including the sales area for agricultural products at a direct sales outlet using a webcam 82, but it is not limited to this form. For example, a terminal device that can take pictures and connect to the internet, such as a smartphone or tablet, may be used instead of the webcam 82.

[0025] Although not shown in the diagram, the network 54 is connected to a vehicle management server that manages automated vehicles, which will be described later, that deliver agricultural products from producers' homes or production areas to direct sales outlets. The data processing device 12 is capable of exchanging various types of information with the vehicle management server. Here, an automated vehicle refers to a vehicle that can automatically travel a set section without requiring a driver.

[0026] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0027] As shown in Figure 2, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "data processing program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0028] Storage 32 stores three data generation models: the first data generation model 58A, the second data generation model 58B, and the third data generation model 58C. The first data generation model 58A, the second data generation model 58B, and the third data generation model 58C are used by the specific processing unit 290. In the following, when describing the first data generation model 58A, the second data generation model 58B, and the third data generation model 58C without distinguishing between them, they will be collectively referred to as "data generation model 58".

[0029] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0030] Next, we will describe the processing performed by the specific processing unit 290 when the data processing device 12 performs specific processing to enable the efficient distribution of agricultural products.

[0031] Figure 3 shows a schematic diagram illustrating the outline of the specific processing according to this embodiment. As shown in Figure 3, the specific processing in this embodiment includes a first specific processing step that uses image data acquired from a web camera 82 to present producers with information indicating the sales status of agricultural products at the direct sales store, and accepts reservations from producers for automated delivery of agricultural products to the direct sales store by automated vehicle 90. The specific processing in this embodiment also includes a second specific processing step that arranges for automated vehicle 90 to deliver agricultural products from producers to the direct sales store. Furthermore, the specific processing in this embodiment includes a third specific processing step that arranges for the delivery of unsold agricultural products from the direct sales store to predetermined partner retailers (hereinafter referred to as "secondary distributors" or "secondary distributors") by automated vehicle 90.

[0032] In the data processing device 12 according to this embodiment, a first data generation model 58A is used when performing a first specific processing. Furthermore, in the data processing device 12 according to this embodiment, a second data generation model 58B is used when performing a second specific processing. Moreover, in the data processing device 12 according to this embodiment, a third data generation model 58C is used when performing a third specific processing.

[0033] As described above, in this embodiment, the first specific processing, the second specific processing, and the third specific processing are performed using data generation models 58 prepared individually for each. However, the embodiment is not limited to this configuration. For example, the first specific processing, the second specific processing, and the third specific processing may be performed using a single data generation model 58. Alternatively, two specific processing combinations in the first specific processing, the second specific processing, and the third specific processing may be performed using a common data generation model 58, and the remaining specific processing may be performed using other data generation models 58.

[0034] As shown in Figure 4, the specific processing unit 290 includes an input unit 292, a processing unit 294, and an output unit 296.

[0035] The input unit 292 acquires user data. Specifically, the input unit 292 acquires image data showing an image of the area including the sales area of ​​the product (in this embodiment, agricultural product) at the sales outlet (in this embodiment, direct sales outlet) for the product. More specifically, the input unit 292 acquires image data showing moving images from a predetermined period in the most recent past (in this embodiment, one week) obtained by taking pictures with multiple web cameras 82 installed at each of the multiple direct sales outlets.

[0036] The processing unit 294 performs a specific processing using a data generation model 58 that generates predetermined inference results according to user data. Specifically, the processing unit 294 performs the first specific processing to generate sales status information by inputting a prompt to the first data generation model 58A that instructs it to generate sales status information showing the sales status of products at sales outlets based on user data. More specifically, the processing unit 294 performs the first specific processing to generate sales status information for multiple direct sales outlets by inputting a prompt to the first data generation model 58A that instructs it to generate sales status information for multiple direct sales outlets.

[0037] The output unit 296 outputs the result of the first specific processing to a predetermined device. Specifically, the output unit 296 outputs the sales status indicated by the sales status information to the smart device 14 of the agricultural producer. More specifically, the output unit 296 outputs a sales status screen that displays the sales status indicated by the sales status information separately for each of the multiple direct sales outlets, so that it can be displayed on the smart device 14 of the agricultural producer.

[0038] Thus, in this embodiment, agricultural products are used as the product and a direct sales outlet for agricultural products is used as the sales outlet, but the embodiment is not limited to this form. For example, industrial parts may be used as the product and a store that sells said industrial parts may be used as the sales outlet, or pharmaceuticals may be used as the product and a pharmacy that sells said pharmaceuticals may be used as the sales outlet, and so on.

[0039] In this embodiment, the sales status information includes information on agricultural products that are in excess supply (hereinafter referred to as "excess supply information"), information on agricultural products that are in short supply (hereinafter referred to as "shortage information"), information on agricultural products that are selling well (hereinafter referred to as "best-selling information"), information on the number of visitors to the direct sales outlet (hereinafter referred to as "visitor number information"), and information indicating the projected future shipment volume for each type of agricultural product at the direct sales outlet (hereinafter referred to as "projected shipment volume information").

[0040] Thus, in this embodiment, the sales status information includes all of the following information: oversupply information, shortage information, best-selling product information, visitor count information, and estimated shipment quantity information. However, the embodiment is not limited to this form. For example, the sales status information may include any one of these pieces of information, or it may include a combination of multiple pieces of information other than all of these pieces of information.

[0041] Furthermore, the input unit 292 acquires reservation data as user data from producers indicating that they have made a reservation to deliver the agricultural products they have produced to a direct sales outlet. Specifically, the input unit 292 acquires reservation data from multiple producers for a predetermined period in the most recent past (one day in this embodiment). In this embodiment, the reservation data includes data indicating the desired direct sales outlet, delivery date, and collection time specified by the producer, but it is not limited to this form. For example, in addition to this data, data indicating the type and quantity of agricultural products to be delivered may also be applied as reservation data.

[0042] Then, the processing unit 294 further performs a specific process to arrange delivery vehicles to deliver agricultural products from producers to direct sales outlets, according to the reservations indicated by the reservation data. Specifically, the processing unit 294 generates delivery vehicle information and travel route information by inputting a prompt to the second data generation model 58B instructing it to generate delivery vehicle information and travel route information for each producer, based on the acquired reservation data, indicating delivery vehicles that can efficiently deliver agricultural products from each producer to the desired direct sales outlet. Then, the processing unit 294 performs a second specific process to arrange delivery vehicles using the generated delivery vehicle information and travel route information.

[0043] Here, the delivery vehicle is the aforementioned automated vehicle 90 that automatically moves along a set section, and the processing unit 294 also performs the process of setting the section between the producer and the corresponding direct sales store as the second specific processing.

[0044] Thus, in this embodiment, an automated vehicle 90 is used as the delivery vehicle, and the processing unit 294 performs the process of setting the section between the producer and the corresponding direct sales store as the section, but the embodiment is not limited to this form. For example, a normal vehicle driven by a driver may be used as the delivery vehicle.

[0045] Furthermore, the processing unit 294 uses the aforementioned image data to perform a specific processing step which involves arranging for the delivery of any unsold agricultural products after the end of sales at the direct sales outlet to predetermined distributors.

[0046] Specifically, the input unit 292 acquires image data from the Webcam 82 at each direct sales outlet, showing moving images obtained from a predetermined period of time (10 minutes in this embodiment) in the most recent past. The processing unit 294 then inputs a prompt to the third data generation model 58C, instructing it to generate selection result information showing the selection results of a suitable secondary distributor for unsold agricultural products, based on the acquired image data. This process of generating the selection result information is performed as the third specific process. The processing unit 294 then uses the generated selection result information to arrange for an automated vehicle 90 to deliver the unsold agricultural products to the secondary distributor, which is performed as the third specific process.

[0047] The first data generation model 58A, the second data generation model 58B, and the third data generation model 58C are so-called generative AI (Artificial Intelligence). An example of these data generation models 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data, image data, and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0048] For example, the processing unit 294 inputs a prompt (hereinafter referred to as the "first prompt") to the first data generation model 58A, along with image data acquired from multiple direct sales outlets by the input unit 292, stating, "This is image data showing the most recent past week of the sales area for agricultural products at each direct sales outlet. From this image data, please generate information on agricultural products that are in excess supply, agricultural products that are in short supply, agricultural products that are selling well, the number of visitors at each direct sales outlet, and the estimated future shipment volume for each type of agricultural product at each direct sales outlet during this period." As a result, the first data generation model 58A generates the above-mentioned information on excess supply, shortages, best-selling products, visitor numbers, and estimated shipment volumes as sales status information.

[0049] Furthermore, for example, the processing unit 294 inputs a prompt (hereinafter referred to as the "second prompt") to the second data generation model 58B along with the reservation data acquired by the input unit 292, stating, "This is reservation data showing the reservation status of delivery vehicles for each producer over the past day. Based on this reservation status, please generate delivery vehicle information for each producer, indicating an automated vehicle capable of efficiently delivering agricultural products to the direct sales outlets desired by each producer, and travel route information indicating the travel route." As a result, the second data generation model 58B generates the delivery vehicle information and travel route information.

[0050] Furthermore, for example, the processing unit 294 inputs a prompt (hereinafter referred to as the "third prompt") to the third data generation model 58C along with the image data acquired by the input unit 292, stating, "This is image data showing the current status of agricultural products at each direct sales outlet. From this status of agricultural products, derive the types and quantities of unsold agricultural products, and taking this result into consideration, select an appropriate secondary distributor from the partners and generate selection result information showing the selection result." As a result, the third data generation model 58C generates the selection result information.

[0051] Next, the operation of the data processing system 10 will be explained.

[0052] First, with reference to Figure 5, the flow of the first specific processing in the specific processing will be explained. Note that the flow of the first specific processing shown in Figure 5 is an example of a "data processing method" relating to the technology of this disclosure. The first specific processing according to this embodiment is executed when any producer inputs an instruction to display the sales status screen via the smart device 14. To avoid confusion, here we will explain the case in which image data for the most recent past week (hereinafter simply referred to as "image data") obtained by taking pictures with Web cameras 82 installed at each direct sales store is sequentially accumulated (updated) in the database 24.

[0053] In step S300, the input unit 292 is acquired by reading all image data from the database 24.

[0054] In step S302, the processing unit 294 generates the first prompt described above as an example.

[0055] In step S304, the processing unit 294 inputs the generated first prompt, along with the read image data, to the first data generation model 58A to generate the sales status information described above. As described above, the generated sales status information includes information on excess supply, shortages, best-selling items, visitor numbers, and estimated shipment quantities.

[0056] In step S306, the output unit 296 uses the generated sales status information to output a sales status screen that displays the sales status indicated by the sales status information separately for each of the multiple direct sales outlets, so that it can be displayed on the smart device 14 of the accessing producer.

[0057] Figure 6 shows an example of a sales status screen displayed on the display 40A of the accessing smart device 14.

[0058] As shown in Figure 6, this sales status screen displays information indicating the producer (hereinafter simply referred to as "producer") who possesses the smart device 14 that accessed the site (in the example shown in Figure 6, the information is "Nogyo Taro").

[0059] Furthermore, this sales status screen displays, for each direct sales outlet, an image of the sales area obtained by taking a picture with the web camera 82 (in this case, the most recent still image), information showing the delivery history of agricultural products to the producer's corresponding direct sales outlet (hereinafter simply referred to as "direct sales outlet"), information showing the estimated delivery time from the producer to the direct sales outlet, and information showing the address of the direct sales outlet.

[0060] Furthermore, this sales status screen displays information indicating the secondary distribution destinations for agricultural products that remain unsold at each direct sales outlet. Accordingly, the database 24 of the data processing device 12 according to this embodiment contains various types of information that are displayed on the sales status screen shown in Figure 6.

[0061] When the sales status screen shown in Figure 6 is displayed on the smart device 14's display 40A, the producer specifies the display area of ​​the direct sales outlet to which they want to deliver their agricultural products via the touch panel 38A. Once the producer has specified the display area of ​​any direct sales outlet, the sales status screen changes to the one shown in Figure 7 as an example.

[0062] As shown in Figure 7, this sales status screen maintains the display of information regarding the direct sales outlets designated by the producers, and also displays a map image showing the delivery route from the producers to the direct sales outlets. Accordingly, the database 24 of the data processing device 12 according to this embodiment also has information (address in this embodiment) indicating the location where each corresponding producer's agricultural products are shipped from pre-registered. The map image showing the delivery route can be created using conventionally known route search software.

[0063] Furthermore, this sales status screen displays information showing the trend in the number of visitors to the direct sales outlet, created using visitor count information (in the example shown in Figure 7, it is displayed as "Weekly Visit Volume"), and information showing the trend in the prices of best-selling agricultural products, created using best-selling product information (in the example shown in Figure 7, it is displayed as "Best-Selling Products").

[0064] Furthermore, this sales status screen displays information such as the average unit price, appropriate shipment volume, and unit price at secondary distribution channels for scarce agricultural products, which are created using the missing information (in the example shown in Figure 7, this is information related to "broccoli (scarce)").

[0065] Furthermore, this sales status screen displays information about agricultural products that the direct sales outlet requests delivery of (in the example shown in Figure 7, information about "Beets (requested by the store)" is displayed). Therefore, in the data processing system 10 according to this embodiment, information about agricultural products that the direct sales outlet requests delivery of is registered in the database 24 of the data processing device 12 by the person in charge at the direct sales outlet.

[0066] Although not shown in the illustration, the sales status screen shown in Figure 7 can display information such as the excess supply information indicating that there is an excess of agricultural products at the corresponding direct sales outlet, and the projected shipment volume information indicating the projected shipment volume for each type of agricultural product, as a modal or pop-up screen on the screen.

[0067] When the sales status screen shown in Figure 7 is displayed on the smart device 14's display 40A, producers who wish to reserve delivery of agricultural products to the displayed direct sales outlet by delivery vehicle specify the map image showing the delivery route via the touch panel 38A. Once the producer specifies the map image, the sales status screen changes to the one shown in Figure 8 as an example.

[0068] As shown in Figure 8, this sales status screen maintains the display of information about the direct sales outlet designated by the producer, and also displays a calendar 40A1 that includes dates for the current day and beyond, and a time slot selection button 40A2 that accepts selection of any available time slot for collection (in the example shown in Figure 8, time slots in 30-minute increments from 7:00 to 9:30).

[0069] When the calendar 40A1 and the time slot selection button 40A2 are displayed, the producer specifies the desired date for delivery of agricultural products by delivery vehicle via the touch panel 38A on the calendar 40A1. The producer then specifies the time slot selection button 40A2 corresponding to the desired time slot for collection of the agricultural products via the touch panel 38A, and then specifies the reservation button 40A3 via the touch panel 38A.

[0070] Therefore, in step S308, the processing unit 294 determines whether the reservation button 40A3 has been specified by the producer. If the determination is negative, the first identification process is terminated; however, if the determination is positive, the process proceeds to step S310.

[0071] In step S310, the processing unit 294 performs a predetermined registration process, and then terminates the first identification process.

[0072] In this embodiment, the registration process involves registering the aforementioned reservation data, which indicates the direct sales outlet, delivery date, and collection time specified by the producer, in the database 24, and also making a provisional reservation for an automated vehicle 90 that is not reserved for the reserved date. The sales status screen then displays information related to the reservation (such as the "delivery reservation number" in the example shown in Figure 8). However, it goes without saying that the embodiment is not limited to this form.

[0073] Figure 9 shows an example of the reservation completion screen displayed on the smart device 14's display 40A after the first identification process described above has been completed.

[0074] Next, with reference to Figure 10, the flow of the second specific processing in the specific processing will be explained. The second specific processing according to this embodiment is executed at a predetermined time (in this embodiment, 0:00 AM every day).

[0075] In step S400, the input unit 292 retrieves all reservation data registered in the most recent past day by reading it from the database 24.

[0076] In step S402, the processing unit 294 generates the second prompt described above as an example.

[0077] In step S404, the processing unit 294 inputs the generated second prompt, along with the read reservation data, to the second data generation model 58B, thereby generating the delivery vehicle information and travel route information described above.

[0078] In step S406, the processing unit 294 uses the generated delivery vehicle information and travel route information to perform the process of arranging an automated vehicle 90 according to this information to the vehicle management server, including setting the section for the automated vehicle 90 as described above, and then terminates the second identification process.

[0079] Next, with reference to Figure 11, the flow of the third specific processing in the specific processing will be explained. The third specific processing according to this embodiment is executed when a predetermined timing occurs (in this embodiment, at the end of the operating hours of each direct sales store each day).

[0080] In step S500, the input unit 292 obtains the most recent image data registered at that time by reading it from the database 24.

[0081] In step S502, the processing unit 294 generates the third prompt described above as an example.

[0082] In step S504, the processing unit 294 inputs the generated third prompt together with the read image data to the third data generation model 58C, thereby generating the selection result information described above.

[0083] In step S506, the processing unit 294 uses the generated selection result information to execute a process to the vehicle management server described above to arrange for the delivery of unsold agricultural products, as indicated by the selection result information, from the direct sales outlet selling the agricultural products to the selected secondary distributor using the automated vehicle 90, and then terminates the third identification process.

[0084] As described above, in the data processing system 10 according to this embodiment, the input unit 292 acquires image data showing an image of the area including the sales area of ​​the product at the sales outlet as user data, and the processing unit 294 inputs a prompt to the data generation model instructing it to generate sales status information showing the sales status of the product at the sales outlet based on the user data, thereby performing the process of generating sales status information as a specific process, and the output unit 296 outputs the sales status shown in the sales status information to the product producer's device. As a result, producers can refer to the sales status of their products at the sales outlet to determine whether or not it is necessary to deliver their products to the sales outlet, and if so, the timing of such delivery, etc., thereby making the distribution of products more efficient compared to conventional technology.

[0085] Furthermore, in the data processing system 10 according to this embodiment, agricultural products are used as the product, and direct sales outlets are used as the sales outlets. Therefore, the distribution of agricultural products through direct sales outlets can be made more efficient.

[0086] Furthermore, in the data processing system 10 according to this embodiment, the input unit 292 acquires the image data from direct sales outlets located at multiple locations, the processing unit 294 performs a specific process to generate sales status information for the direct sales outlets at multiple locations, and the output unit 296 outputs the sales status indicated by the sales status information to the devices of agricultural producers for each of the multiple direct sales outlets. As a result, producers can determine whether or not to deliver their produce to the direct sales outlets at multiple locations, and if so, the timing of such deliveries, thereby making the distribution of agricultural products more efficient.

[0087] Furthermore, in the data processing system 10 according to this embodiment, the sales status information includes at least one of the following pieces of information: information on agricultural products that are in excess supply, information on agricultural products that are in short supply, information on agricultural products that are selling well, and information on the number of visitors to the direct sales outlet. As a result, producers can refer to the information included in the sales status information, thereby making the distribution of agricultural products more efficient.

[0088] Furthermore, in the data processing system 10 according to this embodiment, the input unit 292 further acquires reservation data as user data from producers indicating that they have made a reservation to deliver the agricultural products they have produced to a direct sales outlet, and the processing unit 294 further performs a specific process to arrange a delivery vehicle to deliver the agricultural products from the producer to the direct sales outlet according to the reservation indicated by the reservation data. As a result, the effort required of producers to arrange the delivery of agricultural products from producers to direct sales outlets can be reduced, and the distribution of agricultural products can be made more efficient.

[0089] Furthermore, in the data processing system 10 according to this embodiment, an automated vehicle that automatically moves along a set section is used as the delivery vehicle, and the processing unit 294 further performs a specific process to set the section between the producer and the corresponding direct sales outlet as the section. As a result, agricultural products can be delivered by unmanned delivery vehicles, making the distribution of agricultural products more efficient.

[0090] Furthermore, in the data processing system 10 according to this embodiment, the sales status information includes information indicating the estimated future shipment volume for each type of agricultural product at the direct sales outlet. As a result, producers can refer to the estimated shipment volume of agricultural products, thereby making the distribution of agricultural products more efficient.

[0091] Furthermore, in the data processing system 10 according to this embodiment, the processing unit 294 further performs a specific process using image data to arrange for the delivery of unsold agricultural products to predetermined distributors after sales at the direct sales outlet have ended. Therefore, there is a possibility that unsold agricultural products will also be sold, making the distribution of agricultural products more efficient.

[0092] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0093] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0094] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0095] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0096] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0097] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0098] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0099] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0100] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0101] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0102] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0103] In the above embodiment, the case in which the data processing device of the present disclosure is applied to a data processing device 12 configured as a server has been described, but the present invention is not limited to this form. For example, the data processing device of the present disclosure may be applied to a smart device 14.

[0104] Furthermore, although the above embodiment describes a case in which the sales status screen is displayed on a smart device 14 owned by the producer, the embodiment is not limited to this form. For example, the sales status screen may be displayed on an information processing device other than the smart device 14 used by the producer.

[0105] Furthermore, although not mentioned in the above embodiment, the direct sales outlets initially displayed on the sales status screen may be limited to only those that can deliver agricultural products from the accessing producer. Additionally, the types of agricultural products displayed on the sales status screen may be limited to only those produced by the accessing producer.

[0106] In relation to the above, the following additional information is disclosed.

[0107] <Note 1> An input section for acquiring user data, A processing unit that performs specific processing using a data generation model that generates predetermined inference results according to the user data, The system includes an output unit that outputs the result of the specified processing to a predetermined device, The input unit acquires image data as user data, which includes an image of the area in the sales location of the product that includes the sales area of ​​the product. The processing unit performs the process of generating the sales status information as the specific process by inputting a prompt to the data generation model instructing it to generate sales status information indicating the sales status of the products at the sales outlet based on the user data. The output unit outputs the sales status indicated by the sales status information to the producer's device of the product. Data processing device. <Note 2> The aforementioned products are agricultural products, The aforementioned sales outlet is a direct sales outlet. The data processing device described in Appendix 1. <Note 3> The input unit acquires the image data from the direct sales outlets located at multiple locations. The processing unit performs the process of generating the sales status information at the direct sales outlets at the plurality of locations as the specific processing. The output unit outputs the sales status indicated by the sales status information to the devices of the agricultural producers at each of the multiple direct sales outlets. The data processing device described in Appendix 2. <Note 4> The aforementioned sales information includes at least one of the following: information on agricultural products that are in excess supply, information on agricultural products that are in short supply, information on agricultural products that are selling well, and information on the number of visitors to the direct sales outlet. The data processing device described in Appendix 2 or Appendix 3. <Note 5> The input unit further acquires reservation data from the producer as user data, indicating that the producer has made a reservation to deliver the agricultural products he has produced to the direct sales outlet. The processing unit further performs the process of arranging a delivery vehicle to deliver the agricultural products from the producer to the direct sales outlet, in accordance with the reservation data, as the specific processing. A data processing device described in any one of the appendices 2 through 4. <Note 6> The aforementioned delivery vehicle is an automated vehicle that automatically moves along a set section. The processing unit further performs the process of setting the interval between the producer and the corresponding direct sales outlet as the specified interval, The data processing device described in Appendix 5. <Note 7> The aforementioned sales status information includes information indicating the projected future shipment volume for each type of agricultural product at the aforementioned direct sales outlet. A data processing device described in any one of the appendices 2 through 6. <Note 8> The processing unit further performs the specified processing, using the image data, to arrange for the delivery of any unsold agricultural products at the direct sales outlet to a predetermined distributor after the sale of those products has ended. A data processing device described in any one of the appendices 2 through 7. <Note 9> Retrieve user data, A specific processing is performed using a data generation model that generates predetermined inference results according to the user data. A data processing method for outputting the results of the specified processing to a predetermined device, As user data, image data showing an image of the area including the sales area for the product at the product sales location is obtained. By inputting a prompt into the data generation model instructing it to generate sales status information showing the sales status of the products at the sales outlet based on the user data, the process of generating the sales status information is performed as the specific process. The sales status information indicated by the sales status information is output to the producer's device of the product. A data processing method in which a computer performs the processing. <Note 10> Retrieve user data, A specific processing is performed using a data generation model that generates predetermined inference results according to the user data. A process for outputting the result of the specified process to a predetermined device, As user data, image data showing an image of the area including the sales area for the product at the product sales location is obtained. By inputting a prompt into the data generation model instructing it to generate sales status information showing the sales status of the products at the sales outlet based on the user data, the process of generating the sales status information is performed as the specific process. The sales status information indicated by the sales status information is output to the producer's device of the product. A data processing program that instructs a computer to perform a task. [Explanation of Symbols]

[0108] 10 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 22 Computers 24 Databases 26 Communication I / F 28 processors 30 RAM 32 storage 34 bus 36 Computer 38 Reception device 38A Touch Panel 38B Microphone 40 Output device 40A Display 40B speaker 42 cameras 44 Communication I / F 46 processors 46A Control Unit 48 RAM 50 storage 52 bus 54 Network 56 Specific Processing Program 58 Data Generation Models 58A First Data Generation Model 58B Second Data Generation Model 58C Third Data Generation Model 60 Reception Output Program 82 Webcams 90 Automated Vehicles 290 Specific Processing Unit 292 Input section 294 Processing Unit 296 Output section< / url:>

Claims

1. An input section for acquiring user data, A processing unit that performs specific processing using a data generation model that generates predetermined inference results according to the user data, The system includes an output unit that outputs the result of the specified processing to a predetermined device, The input unit acquires image data as user data, which includes an image of the area in the sales location of the product that includes the sales area of ​​the product. The processing unit performs the process of generating the sales status information as the specific process by inputting a prompt to the data generation model instructing it to generate sales status information indicating the sales status of the products at the sales outlet based on the user data. The output unit outputs the sales status indicated by the sales status information to the producer's device of the product. Data processing device.

2. The aforementioned products are agricultural products, The aforementioned sales outlet is a direct sales outlet. The data processing device according to claim 1.

3. The input unit acquires the image data from the direct sales outlets located at multiple locations. The processing unit performs the process of generating the sales status information at the direct sales outlets at the plurality of locations as the specific processing. The output unit outputs the sales status indicated by the sales status information to the devices of the agricultural producers at each of the multiple direct sales outlets. The data processing apparatus according to claim 2.

4. The aforementioned sales information includes at least one of the following: information on agricultural products that are in excess supply, information on agricultural products that are in short supply, information on agricultural products that are selling well, and information on the number of visitors to the direct sales outlet. The data processing apparatus according to claim 2 or claim 3.

5. The input unit further acquires reservation data from the producer as user data, indicating that the producer has made a reservation to deliver the agricultural products he has produced to the direct sales outlet. The processing unit further performs the process of arranging a delivery vehicle to deliver the agricultural products from the producer to the direct sales outlet, in accordance with the reservation data, as the specific processing. The data processing apparatus according to claim 2 or claim 3.

6. The aforementioned delivery vehicle is an automated vehicle that automatically moves along a set section. The processing unit further performs the process of setting the interval between the producer and the corresponding direct sales outlet as the specified interval, The data processing device according to claim 5.

7. The aforementioned sales status information includes information indicating the projected future shipment volume for each type of agricultural product at the aforementioned direct sales outlet. The data processing apparatus according to claim 2 or claim 3.

8. The processing unit further performs the specified processing, using the image data, to arrange for the delivery of any unsold agricultural products at the direct sales outlet to a predetermined distributor after the sale of those products has ended. The data processing apparatus according to claim 2 or claim 3.

9. Retrieve user data, A specific processing is performed using a data generation model that generates predetermined inference results according to the user data. A data processing method for outputting the results of the specified processing to a predetermined device, As user data, image data showing an image of the area including the sales area for the product at the product sales location is obtained. By inputting a prompt into the data generation model instructing it to generate sales status information showing the sales status of the products at the sales outlet based on the user data, the process of generating the sales status information is performed as the specific process. The sales status information indicated by the sales status information is output to the producer's device of the product. A data processing method in which a computer performs the processing.

10. Retrieve user data, A specific processing is performed using a data generation model that generates predetermined inference results according to the user data. A process for outputting the result of the specified process to a predetermined device, As user data, image data showing an image of the area including the sales area for the product at the product sales location is obtained. By inputting a prompt into the data generation model instructing it to generate sales status information showing the sales status of the products at the sales outlet based on the user data, the process of generating the sales status information is performed as the specific process. The sales status information indicated by the sales status information is output to the producer's device of the product. A data processing program that instructs a computer to perform a task.

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