System

Abstract

To provide a system capable of improving the efficiency of the distribution of farm products and providing a smart agricultural environment.SOLUTION: The system includes means for inputting a harvest schedule for produce, means for generating a pickup schedule, means for directing a self-driving transport vehicle to each farm based on the schedule, means for collecting produce when the self-driving transport vehicle arrives at the farm, means for performing image analysis to identify the collected produce, means for matching produce data with inventory data of the sales facility, means for determining an appropriate sales facility based on the inventory data, means for transmitting information of the sales facility to the self-driving transport vehicle, means for delivering the produce to the sales facility by the self-driving transport vehicle, means for attaching a label to the produce during delivery, means for applying a brand design to the produce, means for delivering the produce, means for generating sales promotion data related to the delivered produce, and means for distributing the sales promotion data to an information display device of the sales facility.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the 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] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In modern agriculture, agricultural producers transport their products to markets themselves, manually labeling and branding them. This requires producers to expend a great deal of time and effort, which is one of the reasons why young people, in particular, are increasingly turning away from agriculture. There is also a need to improve the efficiency of agricultural product delivery. Furthermore, sales at appropriate sales facilities are delayed, making inventory management and sales promotion difficult. Therefore, the present invention aims to solve these problems and provide an efficient delivery system that automates the distribution and brand building of agricultural products. [Means for solving the problem]

[0005] The present invention relates to a system for collecting agricultural produce and delivering it to a sales facility using an autonomous transport vehicle. The present invention solves the above-mentioned problems by providing a system that includes the following means:

[0006] 1. Provide a means to input harvest schedules for agricultural produce, allowing producers to easily input harvest data into the system.

[0007] 2. Provide a means for automatically generating a collection schedule based on the input harvest schedule.

[0008] 3. Provide a means to send autonomous transport vehicles to each farm according to the generated schedule.

[0009] 4. The autonomous transport vehicle will have a means to collect produce when it arrives at the farm.

[0010] 5. Install image analysis tools to identify collected produce.

[0011] 6. Provide a means to reconcile identified produce data with sales facility inventory data.

[0012] 7. Provide a means to determine the appropriate sales facility based on sales facility inventory data.

[0013] 8. Provide a means for transmitting information about the sales facility to the autonomous transport vehicle.

[0014] 9. Provide a means for autonomous transport vehicles to deliver produce to determined sales facilities.

[0015] 10. Provide means for labeling and branding produce during delivery.

[0016] 11. Providing a means of delivery of produce at sales facilities.

[0017] 12. Provide means for generating promotional data relating to delivered produce and distributing it to information displays at the sales facility.

[0018] This will improve the efficiency of agricultural product distribution, create added value through branding, and provide a smart agricultural environment that young people find attractive. It will also enable sales at optimal sales facilities, resolving issues with inventory management and sales promotion.

[0019] An "autonomous transport vehicle" is a vehicle that has the ability to automatically drive along a pre-set route and collect and deliver cargo.

[0020] "Agricultural products" refers to all agricultural crops produced by farms, including fresh vegetables, fruits, etc.

[0021] "Sales facility" refers to a place where collected agricultural products are sold to consumers, and mainly refers to direct sales outlets and supermarkets.

[0022] "Harvest schedule" refers to information about agricultural products that farmers plan to harvest in advance on a specific date.

[0023] A "collection schedule" is a schedule that plans the optimal date, time, and route for collecting agricultural products from each farm.

[0024] "Image analysis" is a technology that uses devices such as cameras and scanners to analyze collected image data of agricultural products and identify their type and quality.

[0025] "Inventory data" refers to information about the quantity and type of produce currently stored at a sales facility.

[0026] A "label" is a display attached to agricultural products that contains information such as the product's name, place of origin, and brand.

[0027] "Brand design" refers to a specific design or logo applied to agricultural products or their packaging, intended to add value to the product.

[0028] "Promotional data" refers to information intended for sales promotion, including the characteristics and recommended points of agricultural products, promotional messages, etc.

[0029] An "information display device" is a device for visually displaying promotional data, and refers to display equipment such as digital signage. [Brief explanation of the drawings]

[0030] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0031] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0032] First, the terms used in the following description will be explained.

[0033] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0034] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0035] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0036] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple 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), Bluetooth (registered trademark), etc.

[0037] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0038] [First embodiment]

[0039] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0040] 1, a 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.

[0041] 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 a "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. The database 24 and the communication I / F 26 are also 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).

[0042] 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. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0043] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A 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, the specific processing unit 290 acquires the data indicating the user input.

[0044] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0045] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0046] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0047] 2, in the data processing device 12, a specific process 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 "program" according to the technology of the present 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 process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0048] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0049] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0050] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0051] The present invention relates to a system for collecting agricultural produce using autonomous transport vehicles and delivering it to sales facilities. To implement the present invention, several key elements must function in combination. Each element and its specific function are described below.

[0052] 1. Input harvest schedule

[0053] User: Provides an interface for inputting planned harvesting of agricultural produce. Specifically, farmers can use their smartphones or tablets to input the planned harvest date, type, and quantity.

[0054] 2. Generate a pickup schedule

[0055] Server: Collects harvest schedule data and generates an optimal collection schedule based on each farmer's location information. The generated schedule is sent to the autonomous transport vehicle.

[0056] 3. Setting up autonomous driving routes

[0057] Terminal: The terminal installed in the autonomous transport vehicle sets the optimal route based on the schedule information received from the server, allowing the autonomous transport vehicle to visit farms efficiently.

[0058] 4. Collecting agricultural products

[0059] Terminal: When the autonomous transport vehicle arrives at the farm, the terminal uses sensors and cameras to recognize the produce and automatically collects it, which is then placed in a collection container inside the truck.

[0060] 5. Produce Identification

[0061] Terminal: An image analysis system inside the truck identifies the type and quality of the produce collected. This information is sent to a server.

[0062] 6. Decision on sales facilities

[0063] Server: Using the identified product data, the server compares it with the inventory data of each sales facility and determines which sales facility each product should be delivered to. The server sends this information to the terminal of the autonomous transport vehicle.

[0064] 7. Label and brand design

[0065] Terminal: Labeling and branding is done in the truck. Labels are automatically generated and applied to produce based on a theme or message predefined by the user.

[0066] 8. Produce Delivery

[0067] Terminal: The autonomous transport vehicle will make the delivery to the selected sales facility. When the truck arrives at the sales facility, it will automatically unload and deliver the produce.

[0068] 9. Providing promotional data

[0069] Server: When agricultural products are delivered to a sales facility, the server generates promotional data, which includes the characteristics and recommended points of the agricultural products, and distributes it to information display devices (such as digital signage) at the sales facility.

[0070] Specific examples

[0071] User: Farmer A enters his / her tomato harvesting plan for May 1st into the application. The harvest plan data is sent to the server.

[0072] Server: Based on the received harvest schedule data, it generates the optimal collection route and sends it to the autonomous transport vehicle.

[0073] Terminal: The autonomous transport vehicle sets a route to arrive at Farm A at 9:00 a.m. and departs. When the truck arrives at Farm A, it automatically collects the tomatoes and stores them inside the truck.

[0074] Terminal: The image analysis system identifies the tomato and sends the data to the server.

[0075] Server: Checks the inventory information of farm shop B and decides to deliver the tomatoes to farm shop B. This information is sent to the truck.

[0076] Terminal: A label based on the theme "Organic Fresh" is generated in the truck and attached to the tomatoes. The truck then departs for Farm Shop B.

[0077] Terminal B arrives at the direct sales store and automatically unloads and delivers the tomatoes.

[0078] Server: Generates a promotional message saying, "Fresh organic tomatoes from Farm A have arrived!" and displays it on the digital signage at Farm B's farm store.

[0079] The integrated system will efficiently and automatically carry out a series of processes, from collecting, identifying, delivering, branding and promoting agricultural products.

[0080] The processing flow will be explained below.

[0081] Step 1:

[0082] User: Enters the planned harvest date for agricultural produce. Specifically, the user uses a smartphone or tablet to enter the planned harvest date, type of produce, and amount.

[0083] Step 2:

[0084] Server: Receives harvest schedule data. The server saves the input data and aggregates harvest schedule information for all farmers.

[0085] Step 3:

[0086] Server: Generates a collection schedule. The server calculates the optimal collection route based on each farmer's location information and the planned harvest date, and creates a schedule. The generated schedule is sent to the autonomous transport vehicle.

[0087] Step 4:

[0088] Terminal: Sets the autonomous driving route. The terminal inside the truck sets the autonomous driving route based on the schedule information received from the server.

[0089] Step 5:

[0090] Terminal: Start automatic driving. The automatic transport vehicle heads to the farm according to the set route.

[0091] Step 6:

[0092] Terminal: After arriving at the farm, the terminal collects the produce. Using sensors and cameras, the terminal recognizes the produce and automatically loads it onto the truck.

[0093] Step 7:

[0094] Terminal: Identifies agricultural products. An image analysis system inside the truck identifies the collected produce and assesses its type and quality.

[0095] Step 8:

[0096] Terminal: Sends identification data to the server. Collected agricultural product data is sent to the server.

[0097] Step 9:

[0098] Server: Cross-checks inventory data. The server collects real-time inventory data from each sales facility and cross-checks it with the identified produce.

[0099] Step 10:

[0100] Server: Determines the appropriate sales facility. The server determines the optimal sales facility based on inventory data and agricultural product data. This information is sent to the autonomous transport vehicle.

[0101] Step 11:

[0102] Terminal: The truck handles label and brand design. AI generates labels based on themes and messages set by the user inside the truck and attaches them to the produce.

[0103] Step 12:

[0104] Terminal: Initiate delivery to the appropriate sales facility. The autonomous delivery vehicle departs for the designated sales facility.

[0105] Step 13:

[0106] Terminal: Arrives at the sales facility and delivers the produce. When the truck arrives at the sales facility, it automatically unloads the produce and completes the delivery process.

[0107] Step 14:

[0108] Server: Generates sales promotion data. The server generates sales promotion data about delivered agricultural products and distributes it to the information display device in the sales facility.

[0109] Step 15:

[0110] Server: Display promotional messages. Display promotional messages such as "Fresh produce in stock!" on the information display devices of the sales facility.

[0111] This process automates the collection, identification, distribution, labeling, branding, and promotion of produce.

[0112] Example 1

[0113] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0114] The traditional process of collecting and delivering agricultural products requires a lot of manual work, making it difficult to operate efficiently. In particular, managing harvest schedules, collecting produce on-site, identifying them, inspecting their quality, labeling them, designing their brands, and delivering them to the appropriate sales facilities all require manual work, which is time-consuming and labor-intensive. It is also difficult to ensure the quality of the produce while quickly shipping them to market. There is a need to solve these problems and automate the process from produce collection to sales, streamlining it.

[0115] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0116] In this invention, the server includes: means for inputting a harvest plan for agricultural produce; means for generating a collection schedule based on the harvest plan; means for directing agricultural machinery to each producer based on the generated schedule; means for collecting the agricultural produce when the agricultural machinery arrives at the producer; means for performing image analysis to identify the collected agricultural produce; means for comparing data on the identified agricultural produce with inventory data at sales facilities; means for determining an appropriate sales facility based on the inventory data at the sales facility; means for transmitting information about the sales facility to the agricultural machine; means for the agricultural machine to deliver the agricultural produce to the sales facility; means for affixing labels to the agricultural produce during delivery; means for applying a brand design to the agricultural produce; means for delivering the agricultural produce at the sales facility; means for generating sales promotion data for the delivered agricultural produce; and means for distributing the sales promotion data to an information display device at the sales facility. This automates the entire process of collecting, identifying, delivering, branding, and promoting agricultural produce, significantly reducing the workload of producers and sales facilities and enabling agricultural products to be shipped to market quickly while maintaining their quality.

[0117] "Agricultural machinery" refers generally to any equipment used to automate or mechanize agricultural operations, including specifically collection and delivery equipment such as autonomous transport vehicles.

[0118] "Harvest schedule" refers to information such as the type, quantity, and location of agricultural produce that is scheduled to be harvested on a specific date and time.

[0119] A "collection schedule" refers to the planned operation of agricultural machinery, with optimal routes and times planned based on the harvest schedule.

[0120] "Producers" refers to farmers and agricultural managers who cultivate and harvest crops.

[0121] "Image analysis" refers to the technology of analyzing image data collected using cameras and sensors to identify the type and quality of agricultural products.

[0122] "Inventory data" refers to information such as the types and quantities of agricultural products currently stored at sales facilities.

[0123] "Sales facility" refers to the point or place where agricultural products are sold to consumers, including farm shops and supermarkets.

[0124] A "label" is an information tag attached to agricultural products and is used to display the product's name, characteristics, brand message, etc.

[0125] "Brand design" refers to the designs and marketing messages used to enhance the brand value of specific agricultural products or producers.

[0126] "Promotional data" refers to information intended to promote the sale of agricultural products, and refers to digital content including features and recommended points.

[0127] "Information display device" refers to a device used to provide information to customers, such as a display or signage used in a sales facility.

[0128] The present invention relates to a system for collecting and delivering agricultural produce to sales facilities using autonomous transport vehicles. The system is designed to improve the efficiency of agricultural operations and operates using specific hardware and software.

[0129] Hardware and software used

[0130] Hardware:

[0131] Self-driving transport vehicles (agricultural machinery)

[0132] Smartphone or tablet (for inputting harvest schedule)

[0133] Sensors and cameras (for collecting and identifying produce)

[0134] Image analysis equipment and quality inspection equipment (located inside agricultural machinery)

[0135] software:

[0136] Harvest schedule input application

[0137] Collection Schedule Generation Algorithm

[0138] GPS navigation system

[0139] Image and data analysis software

[0140] Label Creation and Brand Design Software

[0141] Promotional data generation and distribution software

[0142] System Operation

[0143] The system operates in the following steps.

[0144] 1. Input harvest schedule

[0145] The user uses a smartphone or tablet to input harvest schedule data (date and time, type of produce, quantity, etc.) into a harvest schedule input application. This data is automatically sent to the server.

[0146] 2. Generate a pickup schedule

[0147] The server analyzes the collected harvest schedule data and generates an optimal collection schedule. The collection schedule is based on the farmer's location information and calculates the most efficient route. This schedule is then sent to the autonomous transport vehicle.

[0148] 3. Setting up autonomous driving routes

[0149] A terminal is installed inside the autonomous transport vehicle and sets the optimal route based on the schedule information received from the server. The autonomous transport vehicle then begins operating according to the set route.

[0150] 4. Collecting agricultural products

[0151] The terminal controls sensors and cameras inside the autonomous transport vehicle, and collects produce upon arrival at the farm, which is then placed in a collection container inside the truck.

[0152] 5. Produce Identification

[0153] The terminal uses the truck's in-vehicle image analysis system to identify the type and quality of the collected produce, and this identification data is then sent back to the server.

[0154] 6. Decision on sales facilities

[0155] The server matches the identification data with the store's inventory data to determine the appropriate store, and sends the results to the autonomous transport vehicle.

[0156] 7. Label and brand design

[0157] The device generates labels and designs the brand based on themes and messages preset by the user, and the generated labels are automatically affixed to the produce.

[0158] 8. Produce Delivery

[0159] The autonomous vehicle will navigate to the sales facility based on the navigation route set by the device, and upon arrival, it will automatically unload the produce and complete the delivery.

[0160] 9. Providing promotional data

[0161] The server generates promotional data based on the delivery completion data and distributes it to the information display device at the sales facility. This promotional data includes the characteristics and recommended points of the agricultural products.

[0162] Specific examples

[0163] A user enters into their smartphone that they plan to harvest tomatoes on May 1st. This input data is sent to a server, which generates an optimal collection schedule and sends it to an autonomous transport vehicle. The device sets the route to arrive at Farm A at 9:00 a.m. When the transport vehicle arrives at Farm A, it automatically collects the tomatoes and stores them in the truck. The tomato identification data is sent to the server, which checks it against Farm Store B and decides to deliver the tomatoes to Farm Store B, and sends this information to the transport vehicle. On the way to Farm Store B, an "organic fresh" label is affixed to the transport vehicle, and the tomatoes are delivered after arrival. The server displays a promotional message on the digital signage at Farm Store B saying, "Fresh organic tomatoes from Farm A have arrived!"

[0164] The system streamlines and automates the entire process of agricultural produce, from collection to distribution, identification, branding and promotion.

[0165] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0166] Program processing steps

[0167] Step 1: Enter your harvest plan

[0168] A user uses a smartphone or tablet to input data about planned harvesting (date and time, type of produce, quantity, etc.) into a harvest plan input application.

[0169] Input: Data such as planned harvest date and time, type of produce, and quantity.

[0170] Output: Harvest forecast data is sent to the server.

[0171] How it works: A user opens the application, enters their harvest schedule, and presses the "Submit" button.

[0172] Step 2: Generate a collection schedule

[0173] The server analyzes the collected harvest schedule data and generates an optimal harvest schedule.

[0174] Input: Harvest schedule data, location information of each producer.

[0175] Data processing: Harvest forecast data is analyzed and combined with each producer's location information.

[0176] Output: A collection schedule is generated and sent to the autonomous transport vehicle.

[0177] How it works: Using harvest schedule data collected by the server, it calculates the optimal visit sequence and sets an efficient route.

[0178] Step 3: Set up your self-driving route

[0179] The terminal is installed inside the autonomous transport vehicle and sets the optimal route based on the schedule information received from the server.

[0180] Input: Collection schedule sent from the server.

[0181] Data calculation: Based on the received schedule data, the navigation system calculates the optimal route.

[0182] Output: The automated driving route is set.

[0183] Operation: The device inputs schedule data into the navigation system and sets up an automated driving route.

[0184] Step 4: Collect produce

[0185] The terminal controls sensors and cameras inside the autonomous transport vehicle and collects agricultural products when it arrives at the farm.

[0186] Input: Farmer location information, crop location data from sensors and cameras.

[0187] Data processing: Analyze data from sensors and cameras to identify the location for collecting produce.

[0188] Output: The collected produce is stored in a collection container inside the truck.

[0189] How it works: The transport vehicle arrives at the farm and the collector activates to collect the produce.

[0190] Step 5: Identify the produce

[0191] The terminal uses an image analysis system inside the truck to identify the type and quality of the produce collected.

[0192] Input: Collected image data of agricultural products.

[0193] Data analysis: Image analysis systems identify the type and quality of agricultural products.

[0194] Output: The identified produce data is sent to the server.

[0195] How it works: The device takes images of the collected produce, and the image analysis system analyzes the data.

[0196] Step 6: Determine your sales facility

[0197] The server matches the identification data with the sales establishment's inventory data to determine the appropriate sales establishment.

[0198] Input: Identified produce data, sales facility inventory data.

[0199] Data calculation: Matching identification data with inventory data to determine the best sales facility.

[0200] Output: The appropriate sales facility is determined and the information is sent to the autonomous transport vehicle.

[0201] How it works: The server scans all inventory data it has access to and determines which sales facility to deliver the produce to.

[0202] Step 7: Label and brand design

[0203] The device generates labels and designs the brand based on themes and messages preset by the user.

[0204] Input: User-defined themes, messages, and identification data.

[0205] Data Processing: Generate label and brand designs based on user settings and identification data.

[0206] Output: The generated label is attached to the produce.

[0207] How it works: The device designs labels based on a theme and automatically applies them to produce.

[0208] Step 8: Deliver your produce

[0209] An autonomous transport vehicle will operate to the sales facility based on the navigation route set on the terminal.

[0210] Input: Sales facility information, navigation route.

[0211] Data calculation: The navigation system recalculates the route and heads towards the destination.

[0212] Output: The autonomous transport vehicle arrives at the sales facility and delivers the produce.

[0213] How it works: The transport vehicle follows a designated route to the sales facility and automatically unloads the produce upon arrival.

[0214] Step 9: Provide promotional data

[0215] The server generates sales promotion data based on the delivery completion data and distributes it to the information display device of the sales facility.

[0216] Input: Delivery completion data, agricultural product characteristics information.

[0217] Data processing: Generate promotional data based on delivery completion data and agricultural product characteristics information.

[0218] Output: The generated sales promotion data is delivered to an information display device in the sales facility.

[0219] Operation: The server analyzes the data after delivery is completed, generates promotional messages, and distributes them to digital signage.

[0220] (Application example 1)

[0221] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0222] Current agricultural produce collection and delivery systems face many challenges in terms of efficiency and accuracy. In particular, farmers must manage their harvest schedules individually, making it difficult for collection vehicles to set efficient routes for each farm. Quality control of collected produce also relies heavily on manual labor, making it difficult to accurately grasp quality data and deliver it to the appropriate sales facility. Furthermore, the creation and display of sales promotion data is also done manually, resulting in a lack of real-time response. To solve these problems, a system is needed that automates the entire process, from inputting harvest schedules to sales promotion at sales facilities.

[0223] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0224] In this invention, the server includes means for inputting planned harvesting of agricultural products, means for generating a collection schedule based on the planned harvesting, means for directing an autonomous transport vehicle to each farm based on the generated schedule, means for collecting the agricultural products when the autonomous transport vehicle arrives at the farm, means for performing image analysis to identify the collected agricultural products, means for comparing data on the identified agricultural products with inventory data at the sales facility, means for determining an appropriate sales facility based on the inventory data at the sales facility, means for transmitting information about the sales facility to the autonomous transport vehicle, means for the autonomous transport vehicle to deliver the agricultural products to the sales facility, means for affixing labels to the agricultural products during delivery, means for applying brand designs to the agricultural products, means for delivering the agricultural products at the sales facility, means for generating promotional data regarding the delivered agricultural products, means for distributing the promotional data to an information display device at the sales facility, means for inputting the harvest schedule using a smart device, means for transmitting quality data to the server, and means for generating a prompt message for the information display device. This enables the entire process of harvesting, collecting, identifying, delivering, labeling, and generating delivery and promotional data for agricultural products to be carried out efficiently and accurately.

[0225] The "means for inputting planned harvesting of agricultural produce" is a device that provides an interface that allows farmers to input the planned harvest date, type, and quantity using a smart device.

[0226] The "means for generating a collection schedule based on the harvest schedule" is a device that collects data on the harvest schedule and automatically generates an optimal collection schedule based on the location information of each farmer.

[0227] The "means for directing autonomous transport vehicles to each farm based on the generated schedule" is a device that receives schedule information from the server and instructs the autonomous transport vehicles to move according to that information.

[0228] "Means for collecting agricultural produce when an autonomous transport vehicle arrives at a farm" refers to a device that uses sensors and cameras installed inside the transport vehicle to recognize and automatically collect agricultural produce.

[0229] "Means for performing image analysis to identify collected produce" means a device that uses an image analysis system located within the truck to identify the type and quality of collected produce.

[0230] The "means for checking data on identified agricultural products against inventory data at the sales facility" is a device that transmits data on identified agricultural products to a server and checks the data against inventory data at the sales facility in real time.

[0231] The "means for determining an appropriate sales facility based on inventory data of the sales facility" is a device in which the server analyzes inventory data and automatically determines to which sales facility each agricultural product should be delivered.

[0232] The "means for transmitting information about the sales facility to the autonomously driven transport vehicle" is a device that transmits information about the determined sales facility to the autonomously driven transport vehicle and instructs the transport vehicle to move based on that information.

[0233] "Means for an autonomous transport vehicle to deliver agricultural produce to a sales facility" refers to a device for an autonomous transport vehicle to deliver agricultural produce to a sales facility according to a determined route.

[0234] The "means for labeling produce during delivery" refers to a device that automatically generates and applies labels to collected produce.

[0235] The "means for applying brand design to agricultural products" is a device that automatically applies brand design to labels based on a theme or message set by the user.

[0236] The "means for delivering agricultural produce at the sales facility" is a device that allows an autonomous transport vehicle to arrive at the sales facility and automatically unload and deliver the agricultural produce.

[0237] The "means for generating sales promotion data relating to delivered agricultural products" is a device that automatically generates sales promotion data including the characteristics and recommended points of the agricultural products delivered at the sales facility on a server.

[0238] The "means for distributing promotional data to an information display device in a sales facility" is a device that distributes the generated promotional data to an information display device such as digital signage in a sales facility.

[0239] "Means for inputting harvest plans using a smart device" refers to an interface for inputting harvest plans using a device such as a smartphone or tablet.

[0240] The "means for transmitting quality data to the server" is a device that transmits quality data of agricultural products identified by the image analysis system to the server in real time.

[0241] The "means for generating a prompt sentence on the information display device" is a device that automatically generates a prompt sentence based on sales promotion data and displays it on the information display device.

[0242] The present invention is a system for collecting agricultural produce and delivering it to a sales facility using an autonomous transport vehicle. This system automates a series of operations using specific means, from the user inputting the harvest schedule to the generation and display of sales promotion data at the sales facility. Specific embodiments are described below.

[0243] First, the user (farmer) uses a smart device (e.g., smartphone or tablet) to input the planned harvesting of agricultural produce. The input data is sent to the server. Based on this harvest plan data, the server generates an optimal collection schedule that reflects the location information of each farmer. The generated schedule is then sent to the autonomous transport vehicle.

[0244] Next, a terminal installed in the autonomous transport vehicle sets the optimal route based on the schedule information received from the server. This allows the autonomous transport vehicle to visit farms efficiently. When the transport vehicle arrives at the farm, the terminal uses sensors and cameras to recognize the produce and automatically collects it. The collected produce is stored in a collection container inside the truck.

[0245] The image analysis system inside the truck then identifies the type and quality of the collected produce, and the identified data is sent to a server. The server compares the identified produce data with the inventory data of the sales facility and determines which sales facility each produce should be delivered to. This delivery information is sent to the terminal of the autonomous transport vehicle.

[0246] Additionally, the terminals handle labeling and branding while the produce is being delivered. Labels are automatically generated and applied to the produce based on a theme or message predefined by the user. When the truck arrives at the sales facility, the produce is automatically unloaded and delivered.

[0247] Once delivery is complete, the server generates promotional data for the delivered produce, including the produce's features and recommended points. The generated promotional data is distributed to information display devices (such as digital signage) at the sales facility, providing consumers with real-time visual information.

[0248] As an example, the following process is performed:

[0249] 1. User Input:

[0250] A user enters "Harvest 200 kg of tomatoes on May 1st" into a smartphone app.

[0251] 2. Server processing:

[0252] Based on the harvest schedule data received by the server, the optimal collection route is generated and sent to the autonomous transport vehicle.

[0253] 3. Collection by vehicle:

[0254] The autonomous transport vehicle arrives at the farm at the designated time and collects the tomatoes. At the time of collection, an image analysis system acquires the quality data of the tomatoes and sends it to a server.

[0255] 4.Delivery destination determination:

[0256] The server determines the best sales facility based on the quality data and transmits this information to the autonomous transport vehicle.

[0257] 5. Label and brand design:

[0258] Labels are generated on board the truck and attached to the tomatoes, with designs based on the theme "organic fresh."

[0259] 6. Delivery and promotional data generation:

[0260] A truck arrives at the sales facility to deliver the tomatoes. A promotional message is generated and displayed on the digital signage: "Fresh farm-fresh organic tomatoes in stock!"

[0261] An example of a prompt sentence would be, "Enter data as a farmer who plans to harvest tomatoes on May 1st. The route is set so that an autonomous vehicle will visit at 9:00, and the collected data on the quality of the agricultural products will be sent to the server in real time. Delivery destination determination and label generation are also automated."

[0262] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0263] Step 1:

[0264] Users use a smartphone or tablet to input their planned harvesting schedule. Specifically, they input data through an interface that allows them to input the planned harvest date, type, and quantity. This input data is then sent to the server. The input data includes the user ID, type of produce, planned harvest date, and harvest quantity.

[0265] Step 2:

[0266] Based on the harvest schedule data it receives, the server generates an optimal collection schedule that reflects the location information of each farmer. The server combines GPS data and harvest schedule data to calculate the most efficient route. The generated schedule is sent to the autonomous transport vehicle's terminal. The input data is the harvest schedule data and GPS data, and the output is the optimal collection schedule.

[0267] Step 3:

[0268] The terminal sets the optimal route for the autonomous transport vehicle based on the schedule information received from the server. The terminal analyzes the route information and gives instructions to the autonomous transport vehicle. Specifically, it calculates the order of farms to visit and the shortest route, and reflects this in the autonomous transport vehicle. The input data is the collection schedule, and the output is route setting information.

[0269] Step 4:

[0270] An autonomous transport vehicle visits farms according to a designated route. When the transport vehicle arrives at a farm, a terminal uses sensors and cameras to recognize the produce and automatically collects it. The collected produce is stored in a collection container inside the truck. The data collected by the sensors and cameras is used to confirm whether the produce has been collected correctly. The input data is route setting information, and the output is information about the collected produce.

[0271] Step 5:

[0272] The collected produce is identified by an image analysis system inside the truck. The terminal sends the data obtained from the image analysis system to a server. The image analysis system identifies the type and quality of the collected produce and sends the data to the server. The input data is image data of the collected produce, and the output is data on the identified produce.

[0273] Step 6:

[0274] The server compares the identified produce data with the sales facility inventory data and determines which sales facility each produce should be delivered to. The server analyzes the inventory data and produce data and selects the most suitable sales facility. This information is sent to the autonomous transport vehicle's terminal. The input data is the identified produce data and inventory data, and the output is information about the sales facility to which the produce should be delivered.

[0275] Step 7:

[0276] The server sends information about the sales facility to the autonomous vehicle. Based on this information, the terminal issues instructions for the autonomous vehicle to head to the designated sales facility. The input data is the sales facility information, and the output is delivery instructions.

[0277] Step 8:

[0278] During delivery, the terminal automatically generates and affixes labels to the produce. The labels are generated using themes and messages preset by the user. The brand design is also applied to the produce. The input data is the user's label settings information, and the output is the affixed label and brand design.

[0279] Step 9:

[0280] When the autonomous transport vehicle arrives at the sales facility, the terminal automatically unloads and delivers the produce. Once delivery is complete, the terminal sends delivery completion data to the server. The input data is delivery instructions, and the output is delivery completion data.

[0281] Step 10:

[0282] The server generates promotional data based on the delivery completion data. The generated promotional data includes the characteristics and recommended points of the agricultural products. This automatically generates the promotional data to be displayed on the information display device of the sales facility. The input data is the delivery completion data, and the output is the promotional data.

[0283] Step 11:

[0284] The server distributes the generated sales promotion data to the information display device in the sales facility, allowing consumers to check the characteristics and recommended points of agricultural products in real time. The input data is the sales promotion data, and the output is the distribution data to the information display device.

[0285] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0286] The present invention combines a system that uses autonomous transport vehicles to collect agricultural produce and deliver it to sales facilities with an emotion engine that recognizes user emotions, allowing the system to optimize its operation based on the user's emotions and provide more personalized services.

[0287] 1. Input harvest schedule

[0288] User: Enters planned harvesting of produce. As the user uses a smartphone or tablet to input the planned harvest date, type of produce, and quantity, the emotion engine recognizes the user's emotions and optimizes the system's settings and information provision based on the input.

[0289] 2. Generate a pickup schedule

[0290] Server: Receives harvest schedule data and aggregates harvest schedule information from all farmers. Based on the emotion engine, generates an optimal collection schedule that reflects the user's emotions. For example, if a user is feeling anxious about harvesting, the system provides a function to flexibly adjust the schedule.

[0291] 3. Setting up autonomous driving routes

[0292] Terminal: The terminal installed in the autonomous transport vehicle sets the optimal route based on the schedule information received from the server. At this time, the emotion engine prioritizes routes that reduce stress as much as possible based on the user's emotions.

[0293] 4. Collecting agricultural products

[0294] Terminal: When the autonomous transport vehicle arrives at the farm, the terminal uses sensors and cameras to recognize the produce and automatically collect it. The emotion engine is sensitive to the user's emotions, and if the user is in a hurry, for example, the terminal will collect the produce quickly.

[0295] 5. Produce Identification

[0296] Terminal: An image analysis system inside the truck identifies the type and quality of the produce collected. This information is sent to a server.

[0297] 6. Decision on sales facilities

[0298] Server: Using the identified product data, it compares it with the inventory data of each sales facility and decides which sales facility to deliver each product to. The emotion engine optimizes the selection of sales facility to improve user satisfaction.

[0299] 7. Label and brand design

[0300] Terminal: Labeling and branding is done inside the truck. Based on themes and emotions predefined by the user, an emotion engine generates personalized labels and branding to be applied to produce.

[0301] 8. Produce Delivery

[0302] Terminal: The autonomous transport vehicle will make the delivery to the selected sales facility. When the truck arrives at the sales facility, it will automatically unload and deliver the produce.

[0303] 9. Providing promotional data

[0304] Server: When agricultural products are delivered to a sales facility, the server generates promotional data based on the emotion engine. This data includes the characteristics and recommended points of the agricultural products, and is distributed to information display devices (such as digital signage) at the sales facility.

[0305] Specific examples

[0306] User: Farmer A enters his / her tomato harvesting plans for May 1st into the application. The emotion engine analyzes the user's facial expressions and tone of voice when entering data and recognizes that he / she is feeling anxious. Based on this, the system flexibly adjusts the harvesting schedule.

[0307] Server: Receives harvest schedule data, generates the optimal collection route, and sends it to the autonomous transport vehicle.

[0308] Terminal: The autonomous transport vehicle sets a route to arrive at Farm A at 9:00 a.m. and departs. When the truck arrives at Farm A, it quickly collects the tomatoes and stores them inside the truck. Based on the emotion engine, collection is fast and efficient.

[0309] Terminal: The image analysis system identifies the tomato and sends the data to the server.

[0310] Server: Checks the inventory information of the sales facility and decides to deliver the tomatoes to Direct Sales Store B. This information is sent to the truck.

[0311] Device: Label and brand design, labeling tomatoes based on the theme "organic fresh," incorporating design elements that respond to user emotions.

[0312] Terminal: Departs for the farm shop B and delivers the tomatoes after arriving. The delivery process is optimized based on the emotion engine.

[0313] Server: The server generates a promotional message saying, "Fresh organic tomatoes from Farm A have arrived!" and displays it on the digital signage at Farm B's farm store.

[0314] The integrated system provides a personalized service that is sensitive to the user's emotions, automating the collection, identification, delivery, labeling, branding, and promotion of agricultural products.

[0315] The processing flow will be explained below.

[0316] Step 1:

[0317] User: Entering planned harvesting of produce. Using a smartphone or tablet, the user enters the planned harvest date, type of produce, and quantity into the application. The emotion engine analyzes the user's facial expressions and voice tone to assess their emotional state.

[0318] Step 2:

[0319] Server: Receives harvest schedule data and emotion data. The server saves the input harvest schedule data, analyzes the user's emotion data, and aggregates the harvest schedule information of all farmers.

[0320] Step 3:

[0321] Server: Generates a collection schedule. The server calculates the optimal collection route based on each farmer's location information and the expected harvest date, and creates a schedule. If the user's emotions are unstable, it provides a flexible schedule. This schedule information is sent to the autonomous transport vehicle.

[0322] Step 4:

[0323] Terminal: Sets the autonomous driving route. The terminal installed in the autonomous transport vehicle sets the autonomous driving route based on the schedule information received from the server. The emotion engine prioritizes routes that reduce stress based on the user's emotions.

[0324] Step 5:

[0325] Terminal: Start automatic driving. The automatic transport vehicle departs according to the set route and heads towards the farm.

[0326] Step 6:

[0327] Terminal: After arriving at the farm, the farmer collects the produce. The terminal uses sensors and cameras to recognize the produce and automatically collects it. If the user is in a hurry, the emotion engine speeds up the collection process.

[0328] Step 7:

[0329] Terminal: Identifies agricultural products. The image analysis system inside the truck identifies the type and quality of the collected agricultural products and sends the data to a server.

[0330] Step 8:

[0331] Server: Cross-checks inventory data. The server collects real-time inventory data from each sales facility and cross-checks it with the identified produce.

[0332] Step 9:

[0333] Server: Determines the appropriate sales facility. The server determines the optimal sales facility based on inventory data and agricultural product data. The emotion engine optimizes the delivery destination selection based on the user's emotions. This information is sent to the terminal of the autonomous transport vehicle.

[0334] Step 10:

[0335] Terminal: The truck generates the label and brand design. Based on the theme and message set by the user in the truck, AI generates the label and attaches it to the produce. The emotion engine optimizes the design according to the user's emotions.

[0336] Step 11:

[0337] Terminal: Start delivery to the sales facility. The autonomous transport vehicle departs for the designated sales facility.

[0338] Step 12:

[0339] Terminal: Arrives at the sales facility and delivers the produce. When the truck arrives at the sales facility, it automatically unloads the produce and completes the delivery process.

[0340] Step 13:

[0341] Server: Generates sales promotion data. The server generates sales promotion data about delivered agricultural products and distributes it to the information display device of the sales facility. Based on the emotion engine, it creates promotional messages that match the user's emotions.

[0342] Step 14:

[0343] Server: Display promotional messages. Promotional messages that take into account emotions, such as "Fresh produce in stock!", are displayed on the information display devices of sales facilities.

[0344] This process provides a personalized and responsive service to users, automating the collection, identification, delivery, labeling, branding, and promotion of produce.

[0345] Example 2

[0346] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0347] In a system that uses autonomous transport vehicles to collect and deliver agricultural produce to sales facilities, conventional technology sets uniform schedules and routes without considering the user's feelings, which leads to problems of low user satisfaction and efficiency.In addition, the process from collecting agricultural produce to delivery and sales promotion is not effectively automated, resulting in wasted effort and time.

[0348] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0349] In this invention, the server includes means for analyzing a user's emotions using an emotion engine and inputting a harvest schedule for agricultural produce, means for generating a collection schedule according to the harvest schedule based on the emotion engine, and means for transmitting the generated schedule information to a terminal of the autonomous transport vehicle and setting a route, thereby enabling efficient and personalized collection, delivery, and sales of agricultural produce that takes into consideration the user's emotions.

[0350] An "emotion engine" is software or hardware for analyzing a user's emotions and generating emotion data from facial expressions and voice.

[0351] "Harvest schedule" is data including information such as the harvest date, type, and quantity of agricultural produce, and is entered into the system by the user.

[0352] The "collection schedule" is a plan that determines the order and timing of visits by autonomous transport vehicles based on the harvest schedule.

[0353] An "autonomous delivery vehicle" is a vehicle that has the ability to drive autonomously and collect and deliver agricultural produce.

[0354] A "sensor" is a device that detects environmental information or the state of an object, and is used when collecting agricultural products.

[0355] "Camera" means a device that captures images and is used to identify agricultural products and inspect their quality.

[0356] "Image analysis" is a technology that identifies the type and quality of agricultural products from photographed images.

[0357] "Inventory data" refers to data that indicates the current inventory status of agricultural products at a sales facility.

[0358] A "label" is an information sheet that is affixed to agricultural products and includes the product name and producer information.

[0359] "Brand design" refers to the design applied to the packaging and labels of agricultural products, and is used to increase purchasing desire.

[0360] "Sales promotion data" refers to data generated for sales promotion purposes, and includes product features and recommended points.

[0361] An "information display device" is a digital signage or display device installed in a sales facility for displaying sales promotion data.

[0362] This invention is a system that uses autonomous transport vehicles to collect agricultural products and deliver them to sales facilities, and by combining it with an emotion engine, provides optimal services that meet the individual needs of users. This invention is composed of users, a server, and terminals.

[0363] First, the user uses a smartphone or tablet to input their planned harvesting schedule (date, type, and quantity). The system is equipped with an emotion engine that analyzes emotional data from the user's facial expressions and voice, and optimizes system settings and information provision based on this. Specifically, if the user is feeling anxious, the emotion engine detects this and flexibly adjusts the harvesting schedule to reduce the user's stress.

[0364] The server aggregates harvest schedule data received from users and analyzes the harvest schedule information of all farmers. Based on the emotion engine, it generates an optimal collection schedule and sends it to the autonomous transport vehicle's terminal. This schedule includes an efficient and user-friendly visit sequence and timing.

[0365] Next, the autonomous vehicle's terminal receives the schedule information and uses the navigation system to set the optimal route. This route is selected with consideration for the user's emotions, with priority given to routes that cause as little stress as possible. The vehicle then travels along the set route and arrives at each farm.

[0366] When the transport vehicle arrives at the farm, the terminal's sensors and cameras scan the produce and take appropriate collection action. The collected produce is identified by an image analysis system for type and quality, and this data is sent to a server. The server compares this data with inventory information from sales facilities and determines the appropriate sales facility.

[0367] Once a sales facility is determined, that information is sent to the autonomous vehicle, which reroutes it. During delivery, labeling and branding are performed, and personalized labels are applied to the produce. Design elements are incorporated based on the user's emotions and themes.

[0368] Finally, when the autonomous vehicle arrives at the sales facility, it automatically unloads the produce and delivers it to the facility. After delivery, the server generates promotional data based on the emotion engine and distributes it to information display devices such as digital signage at the sales facility. This allows for effective promotion of the produce at the sales facility.

[0369] Examples:

[0370] The user, a farmer, opens the app on their smartphone and inputs their harvest schedule. For example, they might input "I plan to harvest tomatoes on May 1st." The emotion engine analyzes the user's facial expressions and voice when they input their data, and if the user seems anxious, the server will flexibly adjust the harvest schedule.

[0371] An example of a prompt using a generative AI model could be, "Describe a new produce collection system. Include a process where an emotion engine analyzes user emotions, and autonomous vehicles collect and deliver produce to sales facilities."

[0372] This system enables efficient and personalized collection, delivery, and sales of agricultural products that take into consideration the user's feelings.

[0373] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0374] Step 1:

[0375] User: Uses a smartphone or tablet to input planned harvest information (date, type, and quantity).

[0376] Input: The user enters details of the planned harvest into the application.

[0377] Data processing: The emotion engine uses the camera and microphone to analyze the user's facial expressions and voice in real time and generate emotion data.

[0378] Output: Harvest schedule data and emotion data are sent to the server.

[0379] How it works: A user opens the application and fills in a form with details of their harvest. The emotion engine analyzes facial expressions and tone of voice in real time to obtain emotional data. Finally, this data is sent to the server.

[0380] Step 2:

[0381] Server: Aggregates harvest schedule data and emotion data, and analyzes the harvest schedule information of all farmers.

[0382] Input: Harvest schedule data and emotion data.

[0383] Data processing: Based on the emotion engine, the optimal pickup schedule is generated taking into account the user's emotions.

[0384] Output: The generated collection schedule is sent to the autonomous transport vehicle terminal.

[0385] Specific operation: The server receives harvest plan data and emotion data sent from each farmer, and uses an algorithm to determine a collection schedule that takes into account efficiency and user emotions, and sends it to the transport vehicle.

[0386] Step 3:

[0387] Terminal: The terminal inside the autonomous transport vehicle receives the schedule information and uses the navigation system to plan the optimal route.

[0388] Input:Pickup Schedule.

[0389] Data processing: The navigation system calculates the optimal route taking into account the data from the emotion engine.

[0390] Output: The transport vehicle starts moving based on the set route.

[0391] Specific operation: The terminal receives the collection schedule, calculates the optimal route with the least stress, and moves the autonomous delivery vehicle.

[0392] Step 4:

[0393] Terminal: When the self-driving transport vehicle arrives at the farm, it uses sensors and cameras to recognize the produce and automatically collects it.

[0394] Input: Sensor and camera data.

[0395] Data processing: Real-time image analysis data is used to identify agricultural products and perform collection operations.

[0396] Output: Collected produce.

[0397] Specific operation: The terminal's sensors and camera scan the produce, and an automatic collection mechanism collects the produce and stores it in a truck.

[0398] Step 5:

[0399] Terminal: The image analysis system identifies the type and quality of the collected produce and sends this information to the server.

[0400] Input: Collected image data of agricultural products.

[0401] Data processing: Image analysis system identifies type and quality.

[0402] Output: The identified data is sent to the server.

[0403] Specific operation: The device's image analysis system takes a photo of the produce, and the AI ​​model analyzes the type and quality, then sends the data to a server.

[0404] Step 6:

[0405] Server: Matches the data of identified agricultural products with the inventory data of the sales facility and determines the delivery destination.

[0406] Input: Produce data and inventory data.

[0407] Data processing: AI algorithms compare inventory data and determine the appropriate delivery destination.

[0408] Output: Delivery information is sent to the autonomous delivery vehicle.

[0409] Specific operation: The server compares agricultural product data with inventory data from each sales facility, determines the appropriate delivery destination, and sends that information to the autonomous transport vehicle.

[0410] Step 7:

[0411] Terminal: The autonomous delivery vehicle performs label and branding during delivery, generating personalized labels to apply to produce.

[0412] Input: Shipping information and emotion data.

[0413] Data processing: Generate labels and designs based on the emotion engine, then print and paste them.

[0414] Output: Labeled produce.

[0415] Specific operation: The device generates labels and designs based on the user's set theme and emotion, automatically prints them, and attaches the labels to the produce.

[0416] Step 8:

[0417] Terminal: An autonomous transport vehicle arrives at the sales facility and automatically unloads and delivers the produce.

[0418] Input: Shipping information.

[0419] Data Processing: Optimize the delivery process.

[0420] Output: Delivery complete.

[0421] Specific operation: After the terminal arrives at the sales facility, it automatically unloads the produce from the autonomous transport vehicle and completes the delivery process.

[0422] Step 9:

[0423] Server: Generates sales promotion data about delivered agricultural products and distributes it to the information display devices at the sales facility.

[0424] Input: Delivery data and sentiment data.

[0425] Data processing: Generate promotional data based on the emotion engine.

[0426] Output: Promotional data is displayed on an information display device.

[0427] Specific operation: The server checks the delivery data, works with the emotion engine to generate promotional data, and distributes it to digital signage and display devices at the sales facility.

[0428] (Application example 2)

[0429] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0430] Agricultural produce collection and delivery systems using autonomous transport vehicles can improve efficiency, but ignoring the user's emotional state can affect the quality of the work and user satisfaction. Personalized design that reflects emotions is also required for detailed tasks such as branding and labeling of agricultural products. A system that automates these tasks while optimizing them according to the user's emotional state is needed.

[0431] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server includes: means for inputting planned harvesting of agricultural products; means for generating a collection schedule based on the planned harvesting; means for directing an autonomous transport vehicle to each farm based on the generated schedule; means for collecting the agricultural products when the autonomous transport vehicle arrives at the farm; means for performing image analysis to identify the collected agricultural products; means for comparing data on the identified agricultural products with inventory data of sales facilities; means for determining an appropriate sales facility based on the inventory data of the sales facility; means for transmitting information on the sales facility to the autonomous transport vehicle; means for the autonomous transport vehicle to deliver the agricultural products to the sales facility; means for attaching labels to the agricultural products during delivery; means for applying brand designs to the agricultural products; means for delivering the agricultural products at the sales facility; means for generating promotional data regarding the delivered agricultural products; means for distributing the promotional data to an information display device of the sales facility; means including an emotion engine that recognizes user emotions and optimizes work; means for a factory robot to adjust work speed based on the emotions of a worker; and means for monitoring the emotions of a worker in real time using smart glasses. This will enable a personalized and efficient agricultural produce collection and delivery system that responds to user emotions.

[0432] An "autonomous transport vehicle" is a vehicle that has the ability to autonomously collect and deliver agricultural products without the need for a driver.

[0433] "Agricultural products" are food such as crops and fruits produced by agriculture.

[0434] "Harvest schedule" is information that predicts and plans the harvest of agricultural products at a specific date and time.

[0435] A "collection schedule" is a timetable or route planned to efficiently collect agricultural produce.

[0436] "Image analysis" is a technology in which a computer processes images taken with a camera to extract and identify specific information.

[0437] A "sales facility" is a place or building used to sell agricultural products to consumers.

[0438] "Inventory data" refers to information about the quantity and type of produce currently stored at a particular location.

[0439] A "label" is a display tag or sticker attached to a product that provides information such as the product name or brand name.

[0440] "Brand design" refers to the visual design elements and architecture associated with a particular brand.

[0441] An "emotion engine" is a technology that recognizes the user's emotional state and optimizes the system's operation based on that emotion.

[0442] A "factory robot" is a device that automatically performs tasks such as picking and packing within a factory.

[0443] "Smart glasses" are wearable devices equipped with functions such as a camera and a display, and can monitor the user's emotions and surrounding conditions in real time.

[0444] "Monitoring" is the act of continuously observing and recording a particular condition or environment.

[0445] The system that realizes this invention is composed of multiple elements such as smart glasses, an emotion engine, a factory robot, an autonomous transport vehicle, and a server.

[0446] Hardware and software used

[0447] Hardware

[0448] 1. Smart glasses: A wearable device equipped with an emotion-recognition camera for monitoring workers' emotions in real time.

[0449] 2. Factory robots: Robots that pick and pack products in the workplace.

[0450] 3. Autonomous transport vehicles: Vehicles that automatically collect and deliver agricultural produce.

[0451] software

[0452] 1. Emotion engine: An algorithm for analyzing the user's emotional state and optimizing the system's behavior.

[0453] 2. Server: Processes data, aggregates information, and manages it.

[0454] 3. Image analysis system: A system that analyzes images taken with a camera and identifies agricultural products and work environments.

[0455] Operation explanation

[0456] Smart Glasses Monitoring

[0457] The user wears the smart glasses, and the camera captures the user's facial expressions and tone of voice in real time. This data is sent to the emotion engine, which analyzes the user's emotional state. For example, if a worker is feeling stressed, the emotion engine will interpret the data as "high stress level."

[0458] Emotion Engine Operation

[0459] The emotion engine receives user emotional data and optimizes the behavior of factory robots and autonomous delivery vehicles based on that data. If stress levels are high, the robots' picking speed will be adjusted and their behavior will be changed to reduce the burden on workers.

[0460] Server Processing

[0461] The server receives harvest schedule data and emotion data, and generates optimal work schedules and routes based on that data. The server also compares this data with inventory information at sales facilities to optimize delivery destinations.

[0462] Specific examples

[0463] Imagine a factory worker wearing smart glasses picking produce. The smart glasses capture the worker's facial expressions, and the emotion engine analyzes them to determine that the worker is feeling a little stressed. Based on this data, the factory robot's working speed is set slightly slower, allowing the worker to continue working comfortably. This process reduces the worker's stress and enables efficient and safe work.

[0464] Prompt Sentence Examples

[0465] text

[0466] In this scenario, a factory worker wears smart glasses while a robot picks products. The robot works at an optimal speed depending on the worker's emotional state. Explain the algorithm that uses emotion-recognition cameras to monitor the worker's stress level and adjust the robot's behavior accordingly.

[0467] This will enable the realization of a personalized and efficient agricultural produce collection and delivery system that responds to user emotions.

[0468] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0469] Step 1:

[0470] A user puts on smart glasses and inputs their harvest schedule into a smartphone or tablet. At this time, the emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotional state. The input data (harvesting schedule and user's emotional data) is sent to the server. For example, if a user inputs "I will harvest tomatoes next Wednesday," the emotion engine will analyze that the user is feeling anxious based on their tone of voice and facial expression.

[0471] Step 2:

[0472] The server receives the harvest schedule data and emotion data. The server's collection schedule generation algorithm generates an optimal collection schedule based on the harvest schedule data and emotion data. At this time, the schedule is flexibly adjusted to reflect the user's anxiety. For example, consideration is given to avoiding early evening harvest times for users with high anxiety.

[0473] Step 3:

[0474] The collection schedule is sent to the autonomous transport vehicle, which then heads to each farm. A terminal inside the autonomous transport vehicle sets the optimal route based on the schedule data and departs. The vehicle also references the user's emotional data to select the least stressful route. For example, it prioritizes routes with less traffic.

[0475] Step 4:

[0476] When the autonomous vehicle arrives at the farm, it uses sensors and cameras to recognize the produce and automatically collects it. If the user is in a hurry, an algorithm is applied to expedite the collection process. For example, emotional data about a sense of urgency can speed up the collection process.

[0477] Step 5:

[0478] The image analysis system inside the autonomous transport vehicle identifies the type and quality of the collected produce and sends this identification data to a server. For example, after tomatoes are collected, the quality is quickly checked and the data is sent to the server.

[0479] Step 6:

[0480] The server compares the inventory data and identification data of the sales facilities to determine the most suitable sales facility. It also uses an emotion engine to select a sales facility that will improve user satisfaction. For example, it selects a sales facility with a higher rating than the previous one.

[0481] Step 7:

[0482] The information about the sales facility is sent to the autonomous vehicle, which then heads to the designated sales facility. During delivery, the labeling and branding functions are activated to apply personalized labels and branding to the produce based on emotions, such as a design based on an "organic fresh" theme.

[0483] Step 8:

[0484] The autonomous vehicle arrives at the sales facility and delivers the produce. During delivery, it uses an emotion engine to ensure a fast and efficient delivery process. For example, it delivers quickly during busy times and carefully during busy times.

[0485] Step 9:

[0486] The server generates promotional data about agricultural products delivered to the sales facility and distributes it to the facility's information display device (such as digital signage). Promotional messages incorporating personalized elements based on an emotion engine are generated. For example, a message such as "Fresh organic tomatoes have arrived!" can be set.

[0487] This will enable a personalized and efficient agricultural produce collection and delivery system that responds to user emotions.

[0488] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0489] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0490] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0491] [Second embodiment]

[0492] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0493] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0494] 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 a "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. The database 24 and the communication I / F 26 are also 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).

[0495] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, 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. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0496] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0497] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0498] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0499] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0500] The specific processing program 56 is an example of a "program" according to the technology of the present 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 in accordance with the specific processing program 56 executed on the RAM 30.

[0501] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0502] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0503] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0504] The present invention relates to a system for collecting agricultural produce using autonomous transport vehicles and delivering it to sales facilities. To implement the present invention, several key elements must function in combination. Each element and its specific function are described below.

[0505] 1. Input harvest schedule

[0506] User: Provides an interface for inputting planned harvesting of agricultural produce. Specifically, farmers can use their smartphones or tablets to input the planned harvest date, type, and quantity.

[0507] 2. Generate a pickup schedule

[0508] Server: Collects harvest schedule data and generates an optimal collection schedule based on each farmer's location information. The generated schedule is sent to the autonomous transport vehicle.

[0509] 3. Setting up autonomous driving routes

[0510] Terminal: The terminal installed in the autonomous transport vehicle sets the optimal route based on the schedule information received from the server, allowing the autonomous transport vehicle to visit farms efficiently.

[0511] 4. Collecting agricultural products

[0512] Terminal: When the autonomous transport vehicle arrives at the farm, the terminal uses sensors and cameras to recognize the produce and automatically collects it, which is then placed in a collection container inside the truck.

[0513] 5. Produce Identification

[0514] Terminal: An image analysis system inside the truck identifies the type and quality of the produce collected. This information is sent to a server.

[0515] 6. Decision on sales facilities

[0516] Server: Using the identified product data, the server compares it with the inventory data of each sales facility and determines which sales facility each product should be delivered to. The server sends this information to the terminal of the autonomous transport vehicle.

[0517] 7. Label and brand design

[0518] Terminal: Labeling and branding is done in the truck. Labels are automatically generated and applied to produce based on a theme or message predefined by the user.

[0519] 8. Produce Delivery

[0520] Terminal: The autonomous transport vehicle will make the delivery to the selected sales facility. When the truck arrives at the sales facility, it will automatically unload and deliver the produce.

[0521] 9. Providing promotional data

[0522] Server: When agricultural products are delivered to a sales facility, the server generates promotional data, which includes the characteristics and recommended points of the agricultural products, and distributes it to information display devices (such as digital signage) at the sales facility.

[0523] Specific examples

[0524] User: Farmer A enters his / her tomato harvesting plan for May 1st into the application. The harvest plan data is sent to the server.

[0525] Server: Based on the received harvest schedule data, it generates the optimal collection route and sends it to the autonomous transport vehicle.

[0526] Terminal: The autonomous transport vehicle sets a route to arrive at Farm A at 9:00 a.m. and departs. When the truck arrives at Farm A, it automatically collects the tomatoes and stores them inside the truck.

[0527] Terminal: The image analysis system identifies the tomato and sends the data to the server.

[0528] Server: Checks the inventory information of farm shop B and decides to deliver the tomatoes to farm shop B. This information is sent to the truck.

[0529] Terminal: A label based on the theme "Organic Fresh" is generated in the truck and attached to the tomatoes. The truck then departs for Farm Shop B.

[0530] Terminal B arrives at the direct sales store and automatically unloads and delivers the tomatoes.

[0531] Server: Generates a promotional message saying, "Fresh organic tomatoes from Farm A have arrived!" and displays it on the digital signage at Farm B's farm store.

[0532] The integrated system will efficiently and automatically carry out a series of processes, from collecting, identifying, delivering, branding and promoting agricultural products.

[0533] The processing flow will be explained below.

[0534] Step 1:

[0535] User: Enters the planned harvest date for agricultural produce. Specifically, the user uses a smartphone or tablet to enter the planned harvest date, type of produce, and amount.

[0536] Step 2:

[0537] Server: Receives harvest schedule data. The server saves the input data and aggregates harvest schedule information for all farmers.

[0538] Step 3:

[0539] Server: Generates a collection schedule. The server calculates the optimal collection route based on each farmer's location information and the planned harvest date, and creates a schedule. The generated schedule is sent to the autonomous transport vehicle.

[0540] Step 4:

[0541] Terminal: Sets the autonomous driving route. The terminal inside the truck sets the autonomous driving route based on the schedule information received from the server.

[0542] Step 5:

[0543] Terminal: Start automatic driving. The automatic transport vehicle heads to the farm according to the set route.

[0544] Step 6:

[0545] Terminal: After arriving at the farm, the terminal collects the produce. Using sensors and cameras, the terminal recognizes the produce and automatically loads it onto the truck.

[0546] Step 7:

[0547] Terminal: Identifies agricultural products. An image analysis system inside the truck identifies the collected produce and assesses its type and quality.

[0548] Step 8:

[0549] Terminal: Sends identification data to the server. Collected agricultural product data is sent to the server.

[0550] Step 9:

[0551] Server: Cross-checks inventory data. The server collects real-time inventory data from each sales facility and cross-checks it with the identified produce.

[0552] Step 10:

[0553] Server: Determines the appropriate sales facility. The server determines the optimal sales facility based on inventory data and agricultural product data. This information is sent to the autonomous transport vehicle.

[0554] Step 11:

[0555] Terminal: The truck handles label and brand design. AI generates labels based on themes and messages set by the user inside the truck and attaches them to the produce.

[0556] Step 12:

[0557] Terminal: Initiate delivery to the appropriate sales facility. The autonomous delivery vehicle departs for the designated sales facility.

[0558] Step 13:

[0559] Terminal: Arrives at the sales facility and delivers the produce. When the truck arrives at the sales facility, it automatically unloads the produce and completes the delivery process.

[0560] Step 14:

[0561] Server: Generates sales promotion data. The server generates sales promotion data about delivered agricultural products and distributes it to the information display device in the sales facility.

[0562] Step 15:

[0563] Server: Display promotional messages. Display promotional messages such as "Fresh produce in stock!" on the information display devices of the sales facility.

[0564] This process automates the collection, identification, distribution, labeling, branding, and promotion of produce.

[0565] Example 1

[0566] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0567] The traditional process of collecting and delivering agricultural products requires a lot of manual work, making it difficult to operate efficiently. In particular, managing harvest schedules, collecting produce on-site, identifying them, inspecting their quality, labeling them, designing their brands, and delivering them to the appropriate sales facilities all require manual work, which is time-consuming and labor-intensive. It is also difficult to ensure the quality of the produce while quickly shipping them to market. There is a need to solve these problems and automate the process from produce collection to sales, streamlining it.

[0568] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0569] In this invention, the server includes: means for inputting a harvest plan for agricultural produce; means for generating a collection schedule based on the harvest plan; means for directing agricultural machinery to each producer based on the generated schedule; means for collecting the agricultural produce when the agricultural machinery arrives at the producer; means for performing image analysis to identify the collected agricultural produce; means for comparing data on the identified agricultural produce with inventory data at sales facilities; means for determining an appropriate sales facility based on the inventory data at the sales facility; means for transmitting information about the sales facility to the agricultural machine; means for the agricultural machine to deliver the agricultural produce to the sales facility; means for affixing labels to the agricultural produce during delivery; means for applying a brand design to the agricultural produce; means for delivering the agricultural produce at the sales facility; means for generating sales promotion data for the delivered agricultural produce; and means for distributing the sales promotion data to an information display device at the sales facility. This automates the entire process of collecting, identifying, delivering, branding, and promoting agricultural produce, significantly reducing the workload of producers and sales facilities and enabling agricultural products to be shipped to market quickly while maintaining their quality.

[0570] "Agricultural machinery" refers generally to any equipment used to automate or mechanize agricultural operations, including specifically collection and delivery equipment such as autonomous transport vehicles.

[0571] "Harvest schedule" refers to information such as the type, quantity, and location of agricultural produce that is scheduled to be harvested on a specific date and time.

[0572] A "collection schedule" refers to the planned operation of agricultural machinery, with optimal routes and times planned based on the harvest schedule.

[0573] "Producers" refers to farmers and agricultural managers who cultivate and harvest crops.

[0574] "Image analysis" refers to the technology of analyzing image data collected using cameras and sensors to identify the type and quality of agricultural products.

[0575] "Inventory data" refers to information such as the types and quantities of agricultural products currently stored at sales facilities.

[0576] "Sales facility" refers to the point or place where agricultural products are sold to consumers, including farm shops and supermarkets.

[0577] A "label" is an information tag attached to agricultural products and is used to display the product's name, characteristics, brand message, etc.

[0578] "Brand design" refers to the designs and marketing messages used to enhance the brand value of specific agricultural products or producers.

[0579] "Promotional data" refers to information intended to promote the sale of agricultural products, and refers to digital content including features and recommended points.

[0580] "Information display device" refers to a device used to provide information to customers, such as a display or signage used in a sales facility.

[0581] The present invention relates to a system for collecting and delivering agricultural produce to sales facilities using autonomous transport vehicles. The system is designed to improve the efficiency of agricultural operations and operates using specific hardware and software.

[0582] Hardware and software used

[0583] Hardware:

[0584] Self-driving transport vehicles (agricultural machinery)

[0585] Smartphone or tablet (for inputting harvest schedule)

[0586] Sensors and cameras (for collecting and identifying produce)

[0587] Image analysis equipment and quality inspection equipment (located inside agricultural machinery)

[0588] software:

[0589] Harvest schedule input application

[0590] Collection Schedule Generation Algorithm

[0591] GPS navigation system

[0592] Image and data analysis software

[0593] Label Creation and Brand Design Software

[0594] Promotional data generation and distribution software

[0595] System Operation

[0596] The system operates in the following steps.

[0597] 1. Input harvest schedule

[0598] The user uses a smartphone or tablet to input harvest schedule data (date and time, type of produce, quantity, etc.) into a harvest schedule input application. This data is automatically sent to the server.

[0599] 2. Generate a pickup schedule

[0600] The server analyzes the collected harvest schedule data and generates an optimal collection schedule. The collection schedule is based on the farmer's location information and calculates the most efficient route. This schedule is then sent to the autonomous transport vehicle.

[0601] 3. Setting up autonomous driving routes

[0602] A terminal is installed inside the autonomous transport vehicle and sets the optimal route based on the schedule information received from the server. The autonomous transport vehicle then begins operating according to the set route.

[0603] 4. Collecting agricultural products

[0604] The terminal controls sensors and cameras inside the autonomous transport vehicle, and collects produce upon arrival at the farm, which is then placed in a collection container inside the truck.

[0605] 5. Produce Identification

[0606] The terminal uses the truck's in-vehicle image analysis system to identify the type and quality of the collected produce, and this identification data is then sent back to the server.

[0607] 6. Decision on sales facilities

[0608] The server matches the identification data with the store's inventory data to determine the appropriate store, and sends the results to the autonomous transport vehicle.

[0609] 7. Label and brand design

[0610] The device generates labels and designs the brand based on themes and messages preset by the user, and the generated labels are automatically affixed to the produce.

[0611] 8. Produce Delivery

[0612] The autonomous vehicle will navigate to the sales facility based on the navigation route set by the device, and upon arrival, it will automatically unload the produce and complete the delivery.

[0613] 9. Providing promotional data

[0614] The server generates promotional data based on the delivery completion data and distributes it to the information display device at the sales facility. This promotional data includes the characteristics and recommended points of the agricultural products.

[0615] Specific examples

[0616] A user enters into their smartphone that they plan to harvest tomatoes on May 1st. This input data is sent to a server, which generates an optimal collection schedule and sends it to an autonomous transport vehicle. The device sets the route to arrive at Farm A at 9:00 a.m. When the transport vehicle arrives at Farm A, it automatically collects the tomatoes and stores them in the truck. The tomato identification data is sent to the server, which checks it against Farm Store B and decides to deliver the tomatoes to Farm Store B, and sends this information to the transport vehicle. On the way to Farm Store B, an "organic fresh" label is affixed to the transport vehicle, and the tomatoes are delivered after arrival. The server displays a promotional message on the digital signage at Farm Store B saying, "Fresh organic tomatoes from Farm A have arrived!"

[0617] The system streamlines and automates the entire process of agricultural produce, from collection to distribution, identification, branding and promotion.

[0618] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0619] Program processing steps

[0620] Step 1: Enter your harvest plan

[0621] A user uses a smartphone or tablet to input data about planned harvesting (date and time, type of produce, quantity, etc.) into a harvest plan input application.

[0622] Input: Data such as planned harvest date and time, type of produce, and quantity.

[0623] Output: Harvest forecast data is sent to the server.

[0624] How it works: A user opens the application, enters their harvest schedule, and presses the "Submit" button.

[0625] Step 2: Generate a collection schedule

[0626] The server analyzes the collected harvest schedule data and generates an optimal harvest schedule.

[0627] Input: Harvest schedule data, location information of each producer.

[0628] Data processing: Harvest forecast data is analyzed and combined with each producer's location information.

[0629] Output: A collection schedule is generated and sent to the autonomous transport vehicle.

[0630] How it works: Using harvest schedule data collected by the server, it calculates the optimal visit sequence and sets an efficient route.

[0631] Step 3: Set up your self-driving route

[0632] The terminal is installed inside the autonomous transport vehicle and sets the optimal route based on the schedule information received from the server.

[0633] Input: Collection schedule sent from the server.

[0634] Data calculation: Based on the received schedule data, the navigation system calculates the optimal route.

[0635] Output: The automated driving route is set.

[0636] Operation: The device inputs schedule data into the navigation system and sets up an automated driving route.

[0637] Step 4: Collect produce

[0638] The terminal controls sensors and cameras inside the autonomous transport vehicle and collects agricultural products when it arrives at the farm.

[0639] Input: Farmer location information, crop location data from sensors and cameras.

[0640] Data processing: Analyze data from sensors and cameras to identify the location for collecting produce.

[0641] Output: The collected produce is stored in a collection container inside the truck.

[0642] How it works: The transport vehicle arrives at the farm and the collector activates to collect the produce.

[0643] Step 5: Identify the produce

[0644] The terminal uses an image analysis system inside the truck to identify the type and quality of the produce collected.

[0645] Input: Collected image data of agricultural products.

[0646] Data analysis: Image analysis systems identify the type and quality of agricultural products.

[0647] Output: The identified produce data is sent to the server.

[0648] How it works: The device takes images of the collected produce, and the image analysis system analyzes the data.

[0649] Step 6: Determine your sales facility

[0650] The server matches the identification data with the sales establishment's inventory data to determine the appropriate sales establishment.

[0651] Input: Identified produce data, sales facility inventory data.

[0652] Data calculation: Matching identification data with inventory data to determine the best sales facility.

[0653] Output: The appropriate sales facility is determined and the information is sent to the autonomous transport vehicle.

[0654] How it works: The server scans all inventory data it has access to and determines which sales facility to deliver the produce to.

[0655] Step 7: Label and brand design

[0656] The device generates labels and designs the brand based on themes and messages preset by the user.

[0657] Input: User-defined themes, messages, and identification data.

[0658] Data Processing: Generate label and brand designs based on user settings and identification data.

[0659] Output: The generated label is attached to the produce.

[0660] How it works: The device designs labels based on a theme and automatically applies them to produce.

[0661] Step 8: Deliver your produce

[0662] An autonomous transport vehicle will operate to the sales facility based on the navigation route set on the terminal.

[0663] Input: Sales facility information, navigation route.

[0664] Data calculation: The navigation system recalculates the route and heads towards the destination.

[0665] Output: The autonomous transport vehicle arrives at the sales facility and delivers the produce.

[0666] How it works: The transport vehicle follows a designated route to the sales facility and automatically unloads the produce upon arrival.

[0667] Step 9: Provide promotional data

[0668] The server generates sales promotion data based on the delivery completion data and distributes it to the information display device of the sales facility.

[0669] Input: Delivery completion data, agricultural product characteristics information.

[0670] Data processing: Generate promotional data based on delivery completion data and agricultural product characteristics information.

[0671] Output: The generated sales promotion data is delivered to an information display device in the sales facility.

[0672] Operation: The server analyzes the data after delivery is completed, generates promotional messages, and distributes them to digital signage.

[0673] (Application example 1)

[0674] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0675] Current agricultural produce collection and delivery systems face many challenges in terms of efficiency and accuracy. In particular, farmers must manage their harvest schedules individually, making it difficult for collection vehicles to set efficient routes for each farm. Quality control of collected produce also relies heavily on manual labor, making it difficult to accurately grasp quality data and deliver it to the appropriate sales facility. Furthermore, the creation and display of sales promotion data is also done manually, resulting in a lack of real-time response. To solve these problems, a system is needed that automates the entire process, from inputting harvest schedules to sales promotion at sales facilities.

[0676] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0677] In this invention, the server includes means for inputting planned harvesting of agricultural products, means for generating a collection schedule based on the planned harvesting, means for directing an autonomous transport vehicle to each farm based on the generated schedule, means for collecting the agricultural products when the autonomous transport vehicle arrives at the farm, means for performing image analysis to identify the collected agricultural products, means for comparing data on the identified agricultural products with inventory data at the sales facility, means for determining an appropriate sales facility based on the inventory data at the sales facility, means for transmitting information about the sales facility to the autonomous transport vehicle, means for the autonomous transport vehicle to deliver the agricultural products to the sales facility, means for affixing labels to the agricultural products during delivery, means for applying brand designs to the agricultural products, means for delivering the agricultural products at the sales facility, means for generating promotional data regarding the delivered agricultural products, means for distributing the promotional data to an information display device at the sales facility, means for inputting the harvest schedule using a smart device, means for transmitting quality data to the server, and means for generating a prompt message for the information display device. This enables the entire process of harvesting, collecting, identifying, delivering, labeling, and generating delivery and promotional data for agricultural products to be carried out efficiently and accurately.

[0678] The "means for inputting planned harvesting of agricultural produce" is a device that provides an interface that allows farmers to input the planned harvest date, type, and quantity using a smart device.

[0679] The "means for generating a collection schedule based on the harvest schedule" is a device that collects data on the harvest schedule and automatically generates an optimal collection schedule based on the location information of each farmer.

[0680] The "means for directing autonomous transport vehicles to each farm based on the generated schedule" is a device that receives schedule information from the server and instructs the autonomous transport vehicles to move according to that information.

[0681] "Means for collecting agricultural produce when an autonomous transport vehicle arrives at a farm" refers to a device that uses sensors and cameras installed inside the transport vehicle to recognize and automatically collect agricultural produce.

[0682] "Means for performing image analysis to identify collected produce" means a device that uses an image analysis system located within the truck to identify the type and quality of collected produce.

[0683] The "means for checking data on identified agricultural products against inventory data at the sales facility" is a device that transmits data on identified agricultural products to a server and checks the data against inventory data at the sales facility in real time.

[0684] The "means for determining an appropriate sales facility based on inventory data of the sales facility" is a device in which the server analyzes inventory data and automatically determines to which sales facility each agricultural product should be delivered.

[0685] The "means for transmitting information about the sales facility to the autonomously driven transport vehicle" is a device that transmits information about the determined sales facility to the autonomously driven transport vehicle and instructs the transport vehicle to move based on that information.

[0686] "Means for an autonomous transport vehicle to deliver agricultural produce to a sales facility" refers to a device for an autonomous transport vehicle to deliver agricultural produce to a sales facility according to a determined route.

[0687] The "means for labeling produce during delivery" refers to a device that automatically generates and applies labels to collected produce.

[0688] The "means for applying brand design to agricultural products" is a device that automatically applies brand design to labels based on a theme or message set by the user.

[0689] The "means for delivering agricultural produce at the sales facility" is a device that allows an autonomous transport vehicle to arrive at the sales facility and automatically unload and deliver the agricultural produce.

[0690] The "means for generating sales promotion data relating to delivered agricultural products" is a device that automatically generates sales promotion data including the characteristics and recommended points of the agricultural products delivered at the sales facility on a server.

[0691] The "means for distributing promotional data to an information display device in a sales facility" is a device that distributes the generated promotional data to an information display device such as digital signage in a sales facility.

[0692] "Means for inputting harvest plans using a smart device" refers to an interface for inputting harvest plans using a device such as a smartphone or tablet.

[0693] The "means for transmitting quality data to the server" is a device that transmits quality data of agricultural products identified by the image analysis system to the server in real time.

[0694] The "means for generating a prompt sentence on the information display device" is a device that automatically generates a prompt sentence based on sales promotion data and displays it on the information display device.

[0695] The present invention is a system for collecting agricultural produce and delivering it to a sales facility using an autonomous transport vehicle. This system automates a series of operations using specific means, from the user inputting the harvest schedule to the generation and display of sales promotion data at the sales facility. Specific embodiments are described below.

[0696] First, the user (farmer) uses a smart device (e.g., smartphone or tablet) to input the planned harvesting of agricultural produce. The input data is sent to the server. Based on this harvest plan data, the server generates an optimal collection schedule that reflects the location information of each farmer. The generated schedule is then sent to the autonomous transport vehicle.

[0697] Next, a terminal installed in the autonomous transport vehicle sets the optimal route based on the schedule information received from the server. This allows the autonomous transport vehicle to visit farms efficiently. When the transport vehicle arrives at the farm, the terminal uses sensors and cameras to recognize the produce and automatically collects it. The collected produce is stored in a collection container inside the truck.

[0698] The image analysis system inside the truck then identifies the type and quality of the collected produce, and the identified data is sent to a server. The server compares the identified produce data with the inventory data of the sales facility and determines which sales facility each produce should be delivered to. This delivery information is sent to the terminal of the autonomous transport vehicle.

[0699] Additionally, the terminals handle labeling and branding while the produce is being delivered. Labels are automatically generated and applied to the produce based on a theme or message predefined by the user. When the truck arrives at the sales facility, the produce is automatically unloaded and delivered.

[0700] Once delivery is complete, the server generates promotional data for the delivered produce, including the produce's features and recommended points. The generated promotional data is distributed to information display devices (such as digital signage) at the sales facility, providing consumers with real-time visual information.

[0701] As an example, the following process is performed:

[0702] 1. User Input:

[0703] A user enters "Harvest 200 kg of tomatoes on May 1st" into a smartphone app.

[0704] 2. Server processing:

[0705] Based on the harvest schedule data received by the server, the optimal collection route is generated and sent to the autonomous transport vehicle.

[0706] 3. Collection by vehicle:

[0707] The autonomous transport vehicle arrives at the farm at the designated time and collects the tomatoes. At the time of collection, an image analysis system acquires the quality data of the tomatoes and sends it to a server.

[0708] 4.Delivery destination determination:

[0709] The server determines the best sales facility based on the quality data and transmits this information to the autonomous transport vehicle.

[0710] 5. Label and brand design:

[0711] Labels are generated on board the truck and attached to the tomatoes, with designs based on the theme "organic fresh."

[0712] 6. Delivery and promotional data generation:

[0713] A truck arrives at the sales facility to deliver the tomatoes. A promotional message is generated and displayed on the digital signage: "Fresh farm-fresh organic tomatoes in stock!"

[0714] An example of a prompt sentence would be, "Enter data as a farmer who plans to harvest tomatoes on May 1st. The route is set so that an autonomous vehicle will visit at 9:00, and the collected data on the quality of the agricultural products will be sent to the server in real time. Delivery destination determination and label generation are also automated."

[0715] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0716] Step 1:

[0717] Users use a smartphone or tablet to input their planned harvesting schedule. Specifically, they input data through an interface that allows them to input the planned harvest date, type, and quantity. This input data is then sent to the server. The input data includes the user ID, type of produce, planned harvest date, and harvest quantity.

[0718] Step 2:

[0719] Based on the harvest schedule data it receives, the server generates an optimal collection schedule that reflects the location information of each farmer. The server combines GPS data and harvest schedule data to calculate the most efficient route. The generated schedule is sent to the autonomous transport vehicle's terminal. The input data is the harvest schedule data and GPS data, and the output is the optimal collection schedule.

[0720] Step 3:

[0721] The terminal sets the optimal route for the autonomous transport vehicle based on the schedule information received from the server. The terminal analyzes the route information and gives instructions to the autonomous transport vehicle. Specifically, it calculates the order of farms to visit and the shortest route, and reflects this in the autonomous transport vehicle. The input data is the collection schedule, and the output is route setting information.

[0722] Step 4:

[0723] An autonomous transport vehicle visits farms according to a designated route. When the transport vehicle arrives at a farm, a terminal uses sensors and cameras to recognize the produce and automatically collects it. The collected produce is stored in a collection container inside the truck. The data collected by the sensors and cameras is used to confirm whether the produce has been collected correctly. The input data is route setting information, and the output is information about the collected produce.

[0724] Step 5:

[0725] The collected produce is identified by an image analysis system inside the truck. The terminal sends the data obtained from the image analysis system to a server. The image analysis system identifies the type and quality of the collected produce and sends the data to the server. The input data is image data of the collected produce, and the output is data on the identified produce.

[0726] Step 6:

[0727] The server compares the identified produce data with the sales facility inventory data and determines which sales facility each produce should be delivered to. The server analyzes the inventory data and produce data and selects the most suitable sales facility. This information is sent to the autonomous transport vehicle's terminal. The input data is the identified produce data and inventory data, and the output is information about the sales facility to which the produce should be delivered.

[0728] Step 7:

[0729] The server sends information about the sales facility to the autonomous vehicle. Based on this information, the terminal issues instructions for the autonomous vehicle to head to the designated sales facility. The input data is the sales facility information, and the output is delivery instructions.

[0730] Step 8:

[0731] During delivery, the terminal automatically generates and affixes labels to the produce. The labels are generated using themes and messages preset by the user. The brand design is also applied to the produce. The input data is the user's label settings information, and the output is the affixed label and brand design.

[0732] Step 9:

[0733] When the autonomous transport vehicle arrives at the sales facility, the terminal automatically unloads and delivers the produce. Once delivery is complete, the terminal sends delivery completion data to the server. The input data is delivery instructions, and the output is delivery completion data.

[0734] Step 10:

[0735] The server generates promotional data based on the delivery completion data. The generated promotional data includes the characteristics and recommended points of the agricultural products. This automatically generates the promotional data to be displayed on the information display device of the sales facility. The input data is the delivery completion data, and the output is the promotional data.

[0736] Step 11:

[0737] The server distributes the generated sales promotion data to the information display device in the sales facility, allowing consumers to check the characteristics and recommended points of agricultural products in real time. The input data is the sales promotion data, and the output is the distribution data to the information display device.

[0738] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0739] The present invention combines a system that uses autonomous transport vehicles to collect agricultural produce and deliver it to sales facilities with an emotion engine that recognizes user emotions, allowing the system to optimize its operation based on the user's emotions and provide more personalized services.

[0740] 1. Input harvest schedule

[0741] User: Enters planned harvesting of produce. As the user uses a smartphone or tablet to input the planned harvest date, type of produce, and quantity, the emotion engine recognizes the user's emotions and optimizes the system's settings and information provision based on the input.

[0742] 2. Generate a pickup schedule

[0743] Server: Receives harvest schedule data and aggregates harvest schedule information from all farmers. Based on the emotion engine, generates an optimal collection schedule that reflects the user's emotions. For example, if a user is feeling anxious about harvesting, the system provides a function to flexibly adjust the schedule.

[0744] 3. Setting up autonomous driving routes

[0745] Terminal: The terminal installed in the autonomous transport vehicle sets the optimal route based on the schedule information received from the server. At this time, the emotion engine prioritizes routes that reduce stress as much as possible based on the user's emotions.

[0746] 4. Collecting agricultural products

[0747] Terminal: When the autonomous transport vehicle arrives at the farm, the terminal uses sensors and cameras to recognize the produce and automatically collect it. The emotion engine is sensitive to the user's emotions, and if the user is in a hurry, for example, the terminal will collect the produce quickly.

[0748] 5. Produce Identification

[0749] Terminal: An image analysis system inside the truck identifies the type and quality of the produce collected. This information is sent to a server.

[0750] 6. Decision on sales facilities

[0751] Server: Using the identified product data, it compares it with the inventory data of each sales facility and decides which sales facility to deliver each product to. The emotion engine optimizes the selection of sales facility to improve user satisfaction.

[0752] 7. Label and brand design

[0753] Terminal: Labeling and branding is done inside the truck. Based on themes and emotions predefined by the user, an emotion engine generates personalized labels and branding to be applied to produce.

[0754] 8. Produce Delivery

[0755] Terminal: The autonomous transport vehicle will make the delivery to the selected sales facility. When the truck arrives at the sales facility, it will automatically unload and deliver the produce.

[0756] 9. Providing promotional data

[0757] Server: When agricultural products are delivered to a sales facility, the server generates promotional data based on the emotion engine. This data includes the characteristics and recommended points of the agricultural products, and is distributed to information display devices (such as digital signage) at the sales facility.

[0758] Specific examples

[0759] User: Farmer A enters his / her tomato harvesting plans for May 1st into the application. The emotion engine analyzes the user's facial expressions and tone of voice when entering data and recognizes that he / she is feeling anxious. Based on this, the system flexibly adjusts the harvesting schedule.

[0760] Server: Receives harvest schedule data, generates the optimal collection route, and sends it to the autonomous transport vehicle.

[0761] Terminal: The autonomous transport vehicle sets a route to arrive at Farm A at 9:00 a.m. and departs. When the truck arrives at Farm A, it quickly collects the tomatoes and stores them inside the truck. Based on the emotion engine, collection is fast and efficient.

[0762] Terminal: The image analysis system identifies the tomato and sends the data to the server.

[0763] Server: Checks the inventory information of the sales facility and decides to deliver the tomatoes to Direct Sales Store B. This information is sent to the truck.

[0764] Device: Label and brand design, labeling tomatoes based on the theme "organic fresh," incorporating design elements that respond to user emotions.

[0765] Terminal: Departs for the farm shop B and delivers the tomatoes after arriving. The delivery process is optimized based on the emotion engine.

[0766] Server: The server generates a promotional message saying, "Fresh organic tomatoes from Farm A have arrived!" and displays it on the digital signage at Farm B's farm store.

[0767] The integrated system provides a personalized service that is sensitive to the user's emotions, automating the collection, identification, delivery, labeling, branding, and promotion of agricultural products.

[0768] The processing flow will be explained below.

[0769] Step 1:

[0770] User: Entering planned harvesting of produce. Using a smartphone or tablet, the user enters the planned harvest date, type of produce, and quantity into the application. The emotion engine analyzes the user's facial expressions and voice tone to assess their emotional state.

[0771] Step 2:

[0772] Server: Receives harvest schedule data and emotion data. The server saves the input harvest schedule data, analyzes the user's emotion data, and aggregates the harvest schedule information of all farmers.

[0773] Step 3:

[0774] Server: Generates a collection schedule. The server calculates the optimal collection route based on each farmer's location information and the expected harvest date, and creates a schedule. If the user's emotions are unstable, it provides a flexible schedule. This schedule information is sent to the autonomous transport vehicle.

[0775] Step 4:

[0776] Terminal: Sets the autonomous driving route. The terminal installed in the autonomous transport vehicle sets the autonomous driving route based on the schedule information received from the server. The emotion engine prioritizes routes that reduce stress based on the user's emotions.

[0777] Step 5:

[0778] Terminal: Start automatic driving. The automatic transport vehicle departs according to the set route and heads towards the farm.

[0779] Step 6:

[0780] Terminal: After arriving at the farm, the farmer collects the produce. The terminal uses sensors and cameras to recognize the produce and automatically collects it. If the user is in a hurry, the emotion engine speeds up the collection process.

[0781] Step 7:

[0782] Terminal: Identifies agricultural products. The image analysis system inside the truck identifies the type and quality of the collected agricultural products and sends the data to a server.

[0783] Step 8:

[0784] Server: Cross-checks inventory data. The server collects real-time inventory data from each sales facility and cross-checks it with the identified produce.

[0785] Step 9:

[0786] Server: Determines the appropriate sales facility. The server determines the optimal sales facility based on inventory data and agricultural product data. The emotion engine optimizes the delivery destination selection based on the user's emotions. This information is sent to the terminal of the autonomous transport vehicle.

[0787] Step 10:

[0788] Terminal: The truck generates the label and brand design. Based on the theme and message set by the user in the truck, AI generates the label and attaches it to the produce. The emotion engine optimizes the design according to the user's emotions.

[0789] Step 11:

[0790] Terminal: Start delivery to the sales facility. The autonomous transport vehicle departs for the designated sales facility.

[0791] Step 12:

[0792] Terminal: Arrives at the sales facility and delivers the produce. When the truck arrives at the sales facility, it automatically unloads the produce and completes the delivery process.

[0793] Step 13:

[0794] Server: Generates sales promotion data. The server generates sales promotion data about delivered agricultural products and distributes it to the information display device of the sales facility. Based on the emotion engine, it creates promotional messages that match the user's emotions.

[0795] Step 14:

[0796] Server: Display promotional messages. Promotional messages that take into account emotions, such as "Fresh produce in stock!", are displayed on the information display devices of sales facilities.

[0797] This process provides a personalized and responsive service to users, automating the collection, identification, delivery, labeling, branding, and promotion of produce.

[0798] Example 2

[0799] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0800] In a system that uses autonomous transport vehicles to collect and deliver agricultural produce to sales facilities, conventional technology sets uniform schedules and routes without considering the user's feelings, which leads to problems of low user satisfaction and efficiency.In addition, the process from collecting agricultural produce to delivery and sales promotion is not effectively automated, resulting in wasted effort and time.

[0801] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0802] In this invention, the server includes means for analyzing a user's emotions using an emotion engine and inputting a harvest schedule for agricultural produce, means for generating a collection schedule according to the harvest schedule based on the emotion engine, and means for transmitting the generated schedule information to a terminal of the autonomous transport vehicle and setting a route, thereby enabling efficient and personalized collection, delivery, and sales of agricultural produce that takes into consideration the user's emotions.

[0803] An "emotion engine" is software or hardware for analyzing a user's emotions and generating emotion data from facial expressions and voice.

[0804] "Harvest schedule" is data including information such as the harvest date, type, and quantity of agricultural produce, and is entered into the system by the user.

[0805] The "collection schedule" is a plan that determines the order and timing of visits by autonomous transport vehicles based on the harvest schedule.

[0806] An "autonomous delivery vehicle" is a vehicle that has the ability to drive autonomously and collect and deliver agricultural produce.

[0807] A "sensor" is a device that detects environmental information or the state of an object, and is used when collecting agricultural products.

[0808] "Camera" means a device that captures images and is used to identify agricultural products and inspect their quality.

[0809] "Image analysis" is a technology that identifies the type and quality of agricultural products from photographed images.

[0810] "Inventory data" refers to data that indicates the current inventory status of agricultural products at a sales facility.

[0811] A "label" is an information sheet that is affixed to agricultural products and includes the product name and producer information.

[0812] "Brand design" refers to the design applied to the packaging and labels of agricultural products, and is used to increase purchasing desire.

[0813] "Sales promotion data" refers to data generated for sales promotion purposes, and includes product features and recommended points.

[0814] An "information display device" is a digital signage or display device installed in a sales facility for displaying sales promotion data.

[0815] This invention is a system that uses autonomous transport vehicles to collect agricultural products and deliver them to sales facilities, and by combining it with an emotion engine, provides optimal services that meet the individual needs of users. This invention is composed of users, a server, and terminals.

[0816] First, the user uses a smartphone or tablet to input their planned harvesting schedule (date, type, and quantity). The system is equipped with an emotion engine that analyzes emotional data from the user's facial expressions and voice, and optimizes system settings and information provision based on this. Specifically, if the user is feeling anxious, the emotion engine detects this and flexibly adjusts the harvesting schedule to reduce the user's stress.

[0817] The server aggregates harvest schedule data received from users and analyzes the harvest schedule information of all farmers. Based on the emotion engine, it generates an optimal collection schedule and sends it to the autonomous transport vehicle's terminal. This schedule includes an efficient and user-friendly visit sequence and timing.

[0818] Next, the autonomous vehicle's terminal receives the schedule information and uses the navigation system to set the optimal route. This route is selected with consideration for the user's emotions, with priority given to routes that cause as little stress as possible. The vehicle then travels along the set route and arrives at each farm.

[0819] When the transport vehicle arrives at the farm, the terminal's sensors and cameras scan the produce and take appropriate collection action. The collected produce is identified by an image analysis system for type and quality, and this data is sent to a server. The server compares this data with inventory information from sales facilities and determines the appropriate sales facility.

[0820] Once a sales facility is determined, that information is sent to the autonomous vehicle, which reroutes it. During delivery, labeling and branding are performed, and personalized labels are applied to the produce. Design elements are incorporated based on the user's emotions and themes.

[0821] Finally, when the autonomous vehicle arrives at the sales facility, it automatically unloads the produce and delivers it to the facility. After delivery, the server generates promotional data based on the emotion engine and distributes it to information display devices such as digital signage at the sales facility. This allows for effective promotion of the produce at the sales facility.

[0822] Examples:

[0823] The user, a farmer, opens the app on their smartphone and inputs their harvest schedule. For example, they might input "I plan to harvest tomatoes on May 1st." The emotion engine analyzes the user's facial expressions and voice when they input their data, and if the user seems anxious, the server will flexibly adjust the harvest schedule.

[0824] An example of a prompt using a generative AI model could be, "Describe a new produce collection system. Include a process where an emotion engine analyzes user emotions, and autonomous vehicles collect and deliver produce to sales facilities."

[0825] This system enables efficient and personalized collection, delivery, and sales of agricultural products that take into consideration the user's feelings.

[0826] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0827] Step 1:

[0828] User: Uses a smartphone or tablet to input planned harvest information (date, type, and quantity).

[0829] Input: The user enters details of the planned harvest into the application.

[0830] Data processing: The emotion engine uses the camera and microphone to analyze the user's facial expressions and voice in real time and generate emotion data.

[0831] Output: Harvest schedule data and emotion data are sent to the server.

[0832] How it works: A user opens the application and fills in a form with details of their harvest. The emotion engine analyzes facial expressions and tone of voice in real time to obtain emotional data. Finally, this data is sent to the server.

[0833] Step 2:

[0834] Server: Aggregates harvest schedule data and emotion data, and analyzes the harvest schedule information of all farmers.

[0835] Input: Harvest schedule data and emotion data.

[0836] Data processing: Based on the emotion engine, the optimal pickup schedule is generated taking into account the user's emotions.

[0837] Output: The generated collection schedule is sent to the autonomous transport vehicle terminal.

[0838] Specific operation: The server receives harvest plan data and emotion data sent from each farmer, and uses an algorithm to determine a collection schedule that takes into account efficiency and user emotions, and sends it to the transport vehicle.

[0839] Step 3:

[0840] Terminal: The terminal inside the autonomous transport vehicle receives the schedule information and uses the navigation system to plan the optimal route.

[0841] Input:Pickup Schedule.

[0842] Data processing: The navigation system calculates the optimal route taking into account the data from the emotion engine.

[0843] Output: The transport vehicle starts moving based on the set route.

[0844] Specific operation: The terminal receives the collection schedule, calculates the optimal route with the least stress, and moves the autonomous delivery vehicle.

[0845] Step 4:

[0846] Terminal: When the self-driving transport vehicle arrives at the farm, it uses sensors and cameras to recognize the produce and automatically collects it.

[0847] Input: Sensor and camera data.

[0848] Data processing: Real-time image analysis data is used to identify agricultural products and perform collection operations.

[0849] Output: Collected produce.

[0850] Specific operation: The terminal's sensors and camera scan the produce, and an automatic collection mechanism collects the produce and stores it in a truck.

[0851] Step 5:

[0852] Terminal: The image analysis system identifies the type and quality of the collected produce and sends this information to the server.

[0853] Input: Collected image data of agricultural products.

[0854] Data processing: Image analysis system identifies type and quality.

[0855] Output: The identified data is sent to the server.

[0856] Specific operation: The device's image analysis system takes a photo of the produce, and the AI ​​model analyzes the type and quality, then sends the data to a server.

[0857] Step 6:

[0858] Server: Matches the data of identified agricultural products with the inventory data of the sales facility and determines the delivery destination.

[0859] Input: Produce data and inventory data.

[0860] Data processing: AI algorithms compare inventory data and determine the appropriate delivery destination.

[0861] Output: Delivery information is sent to the autonomous delivery vehicle.

[0862] Specific operation: The server compares agricultural product data with inventory data from each sales facility, determines the appropriate delivery destination, and sends that information to the autonomous transport vehicle.

[0863] Step 7:

[0864] Terminal: The autonomous delivery vehicle performs label and branding during delivery, generating personalized labels to apply to produce.

[0865] Input: Shipping information and emotion data.

[0866] Data processing: Generate labels and designs based on the emotion engine, then print and paste them.

[0867] Output: Labeled produce.

[0868] Specific operation: The device generates labels and designs based on the user's set theme and emotion, automatically prints them, and attaches the labels to the produce.

[0869] Step 8:

[0870] Terminal: An autonomous transport vehicle arrives at the sales facility and automatically unloads and delivers the produce.

[0871] Input: Shipping information.

[0872] Data Processing: Optimize the delivery process.

[0873] Output: Delivery complete.

[0874] Specific operation: After the terminal arrives at the sales facility, it automatically unloads the produce from the autonomous transport vehicle and completes the delivery process.

[0875] Step 9:

[0876] Server: Generates sales promotion data about delivered agricultural products and distributes it to the information display devices at the sales facility.

[0877] Input: Delivery data and sentiment data.

[0878] Data processing: Generate promotional data based on the emotion engine.

[0879] Output: Promotional data is displayed on an information display device.

[0880] Specific operation: The server checks the delivery data, works with the emotion engine to generate promotional data, and distributes it to digital signage and display devices at the sales facility.

[0881] (Application example 2)

[0882] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0883] Agricultural produce collection and delivery systems using autonomous transport vehicles can improve efficiency, but ignoring the user's emotional state can affect the quality of the work and user satisfaction. Personalized design that reflects emotions is also required for detailed tasks such as branding and labeling of agricultural products. A system that automates these tasks while optimizing them according to the user's emotional state is needed.

[0884] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server includes: means for inputting planned harvesting of agricultural products; means for generating a collection schedule based on the planned harvesting; means for directing an autonomous transport vehicle to each farm based on the generated schedule; means for collecting the agricultural products when the autonomous transport vehicle arrives at the farm; means for performing image analysis to identify the collected agricultural products; means for comparing data on the identified agricultural products with inventory data of sales facilities; means for determining an appropriate sales facility based on the inventory data of the sales facility; means for transmitting information on the sales facility to the autonomous transport vehicle; means for the autonomous transport vehicle to deliver the agricultural products to the sales facility; means for attaching labels to the agricultural products during delivery; means for applying brand designs to the agricultural products; means for delivering the agricultural products at the sales facility; means for generating promotional data regarding the delivered agricultural products; means for distributing the promotional data to an information display device of the sales facility; means including an emotion engine that recognizes user emotions and optimizes work; means for a factory robot to adjust work speed based on the emotions of a worker; and means for monitoring the emotions of a worker in real time using smart glasses. This will enable a personalized and efficient agricultural produce collection and delivery system that responds to user emotions.

[0885] An "autonomous transport vehicle" is a vehicle that has the ability to autonomously collect and deliver agricultural products without the need for a driver.

[0886] "Agricultural products" are food such as crops and fruits produced by agriculture.

[0887] "Harvest schedule" is information that predicts and plans the harvest of agricultural products at a specific date and time.

[0888] A "collection schedule" is a timetable or route planned to efficiently collect agricultural produce.

[0889] "Image analysis" is a technology in which a computer processes images taken with a camera to extract and identify specific information.

[0890] A "sales facility" is a place or building used to sell agricultural products to consumers.

[0891] "Inventory data" refers to information about the quantity and type of produce currently stored at a particular location.

[0892] A "label" is a display tag or sticker attached to a product that provides information such as the product name or brand name.

[0893] "Brand design" refers to the visual design elements and architecture associated with a particular brand.

[0894] An "emotion engine" is a technology that recognizes the user's emotional state and optimizes the system's operation based on that emotion.

[0895] A "factory robot" is a device that automatically performs tasks such as picking and packing within a factory.

[0896] "Smart glasses" are wearable devices equipped with functions such as a camera and a display, and can monitor the user's emotions and surrounding conditions in real time.

[0897] "Monitoring" is the act of continuously observing and recording a particular condition or environment.

[0898] The system that realizes this invention is composed of multiple elements such as smart glasses, an emotion engine, a factory robot, an autonomous transport vehicle, and a server.

[0899] Hardware and software used

[0900] Hardware

[0901] 1. Smart glasses: A wearable device equipped with an emotion-recognition camera for monitoring workers' emotions in real time.

[0902] 2. Factory robots: Robots that pick and pack products in the workplace.

[0903] 3. Autonomous transport vehicles: Vehicles that automatically collect and deliver agricultural produce.

[0904] software

[0905] 1. Emotion engine: An algorithm for analyzing the user's emotional state and optimizing the system's behavior.

[0906] 2. Server: Processes data, aggregates information, and manages it.

[0907] 3. Image analysis system: A system that analyzes images taken with a camera and identifies agricultural products and work environments.

[0908] Operation explanation

[0909] Smart Glasses Monitoring

[0910] The user wears the smart glasses, and the camera captures the user's facial expressions and tone of voice in real time. This data is sent to the emotion engine, which analyzes the user's emotional state. For example, if a worker is feeling stressed, the emotion engine will interpret the data as "high stress level."

[0911] Emotion Engine Operation

[0912] The emotion engine receives user emotional data and optimizes the behavior of factory robots and autonomous delivery vehicles based on that data. If stress levels are high, the robots' picking speed will be adjusted and their behavior will be changed to reduce the burden on workers.

[0913] Server Processing

[0914] The server receives harvest schedule data and emotion data, and generates optimal work schedules and routes based on that data. The server also compares this data with inventory information at sales facilities to optimize delivery destinations.

[0915] Specific examples

[0916] Imagine a factory worker wearing smart glasses picking produce. The smart glasses capture the worker's facial expressions, and the emotion engine analyzes them to determine that the worker is feeling a little stressed. Based on this data, the factory robot's working speed is set slightly slower, allowing the worker to continue working comfortably. This process reduces the worker's stress and enables efficient and safe work.

[0917] Prompt Sentence Examples

[0918] text

[0919] In this scenario, a factory worker wears smart glasses while a robot picks products. The robot works at an optimal speed depending on the worker's emotional state. Explain the algorithm that uses emotion-recognition cameras to monitor the worker's stress level and adjust the robot's behavior accordingly.

[0920] This will enable the realization of a personalized and efficient agricultural produce collection and delivery system that responds to user emotions.

[0921] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0922] Step 1:

[0923] A user puts on smart glasses and inputs their harvest schedule into a smartphone or tablet. At this time, the emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotional state. The input data (harvesting schedule and user's emotional data) is sent to the server. For example, if a user inputs "I will harvest tomatoes next Wednesday," the emotion engine will analyze that the user is feeling anxious based on their tone of voice and facial expression.

[0924] Step 2:

[0925] The server receives the harvest schedule data and emotion data. The server's collection schedule generation algorithm generates an optimal collection schedule based on the harvest schedule data and emotion data. At this time, the schedule is flexibly adjusted to reflect the user's anxiety. For example, consideration is given to avoiding early evening harvest times for users with high anxiety.

[0926] Step 3:

[0927] The collection schedule is sent to the autonomous transport vehicle, which then heads to each farm. A terminal inside the autonomous transport vehicle sets the optimal route based on the schedule data and departs. The vehicle also references the user's emotional data to select the least stressful route. For example, it prioritizes routes with less traffic.

[0928] Step 4:

[0929] When the autonomous vehicle arrives at the farm, it uses sensors and cameras to recognize the produce and automatically collects it. If the user is in a hurry, an algorithm is applied to expedite the collection process. For example, emotional data about a sense of urgency can speed up the collection process.

[0930] Step 5:

[0931] The image analysis system inside the autonomous transport vehicle identifies the type and quality of the collected produce and sends this identification data to a server. For example, after tomatoes are collected, the quality is quickly checked and the data is sent to the server.

[0932] Step 6:

[0933] The server compares the inventory data and identification data of the sales facilities to determine the most suitable sales facility. It also uses an emotion engine to select a sales facility that will improve user satisfaction. For example, it selects a sales facility with a higher rating than the previous one.

[0934] Step 7:

[0935] The information about the sales facility is sent to the autonomous vehicle, which then heads to the designated sales facility. During delivery, the labeling and branding functions are activated to apply personalized labels and branding to the produce based on emotions, such as a design based on an "organic fresh" theme.

[0936] Step 8:

[0937] The autonomous vehicle arrives at the sales facility and delivers the produce. During delivery, it uses an emotion engine to ensure a fast and efficient delivery process. For example, it delivers quickly during busy times and carefully during busy times.

[0938] Step 9:

[0939] The server generates promotional data about agricultural products delivered to the sales facility and distributes it to the facility's information display device (such as digital signage). Promotional messages incorporating personalized elements based on an emotion engine are generated. For example, a message such as "Fresh organic tomatoes have arrived!" can be set.

[0940] This will enable a personalized and efficient agricultural produce collection and delivery system that responds to user emotions.

[0941] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0942] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0943] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0944] [Third embodiment]

[0945] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0946] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0947] 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 a "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. The database 24 and the communication I / F 26 are also 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).

[0948] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. 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. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0949] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0950] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0951] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0952] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0953] The specific processing program 56 is an example of a "program" according to the technology of the present 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 in accordance with the specific processing program 56 executed on the RAM 30.

[0954] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0955] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0956] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0957] The present invention relates to a system for collecting agricultural produce using autonomous transport vehicles and delivering it to sales facilities. To implement the present invention, several key elements must function in combination. Each element and its specific function are described below.

[0958] 1. Input harvest schedule

[0959] User: Provides an interface for inputting planned harvesting of agricultural produce. Specifically, farmers can use their smartphones or tablets to input the planned harvest date, type, and quantity.

[0960] 2. Generate a pickup schedule

[0961] Server: Collects harvest schedule data and generates an optimal collection schedule based on each farmer's location information. The generated schedule is sent to the autonomous transport vehicle.

[0962] 3. Setting up autonomous driving routes

[0963] Terminal: The terminal installed in the autonomous transport vehicle sets the optimal route based on the schedule information received from the server, allowing the autonomous transport vehicle to visit farms efficiently.

[0964] 4. Collecting agricultural products

[0965] Terminal: When the autonomous transport vehicle arrives at the farm, the terminal uses sensors and cameras to recognize the produce and automatically collects it, which is then placed in a collection container inside the truck.

[0966] 5. Produce Identification

[0967] Terminal: An image analysis system inside the truck identifies the type and quality of the produce collected. This information is sent to a server.

[0968] 6. Decision on sales facilities

[0969] Server: Using the identified product data, the server compares it with the inventory data of each sales facility and determines which sales facility each product should be delivered to. The server sends this information to the terminal of the autonomous transport vehicle.

[0970] 7. Label and brand design

[0971] Terminal: Labeling and branding is done in the truck. Labels are automatically generated and applied to produce based on a theme or message predefined by the user.

[0972] 8. Produce Delivery

[0973] Terminal: The autonomous transport vehicle will make the delivery to the selected sales facility. When the truck arrives at the sales facility, it will automatically unload and deliver the produce.

[0974] 9. Providing promotional data

[0975] Server: When agricultural products are delivered to a sales facility, the server generates promotional data, which includes the characteristics and recommended points of the agricultural products, and distributes it to information display devices (such as digital signage) at the sales facility.

[0976] Specific examples

[0977] User: Farmer A enters his / her tomato harvesting plan for May 1st into the application. The harvest plan data is sent to the server.

[0978] Server: Based on the received harvest schedule data, it generates the optimal collection route and sends it to the autonomous transport vehicle.

[0979] Terminal: The autonomous transport vehicle sets a route to arrive at Farm A at 9:00 a.m. and departs. When the truck arrives at Farm A, it automatically collects the tomatoes and stores them inside the truck.

[0980] Terminal: The image analysis system identifies the tomato and sends the data to the server.

[0981] Server: Checks the inventory information of farm shop B and decides to deliver the tomatoes to farm shop B. This information is sent to the truck.

[0982] Terminal: A label based on the theme "Organic Fresh" is generated in the truck and attached to the tomatoes. The truck then departs for Farm Shop B.

[0983] Terminal B arrives at the direct sales store and automatically unloads and delivers the tomatoes.

[0984] Server: Generates a promotional message saying, "Fresh organic tomatoes from Farm A have arrived!" and displays it on the digital signage at Farm B's farm store.

[0985] The integrated system will efficiently and automatically carry out a series of processes, from collecting, identifying, delivering, branding and promoting agricultural products.

[0986] The processing flow will be explained below.

[0987] Step 1:

[0988] User: Enters the planned harvest date for agricultural produce. Specifically, the user uses a smartphone or tablet to enter the planned harvest date, type of produce, and amount.

[0989] Step 2:

[0990] Server: Receives harvest schedule data. The server saves the input data and aggregates harvest schedule information for all farmers.

[0991] Step 3:

[0992] Server: Generates a collection schedule. The server calculates the optimal collection route based on each farmer's location information and the planned harvest date, and creates a schedule. The generated schedule is sent to the autonomous transport vehicle.

[0993] Step 4:

[0994] Terminal: Sets the autonomous driving route. The terminal inside the truck sets the autonomous driving route based on the schedule information received from the server.

[0995] Step 5:

[0996] Terminal: Start automatic driving. The automatic transport vehicle heads to the farm according to the set route.

[0997] Step 6:

[0998] Terminal: After arriving at the farm, the terminal collects the produce. Using sensors and cameras, the terminal recognizes the produce and automatically loads it onto the truck.

[0999] Step 7:

[1000] Terminal: Identifies agricultural products. An image analysis system inside the truck identifies the collected produce and assesses its type and quality.

[1001] Step 8:

[1002] Terminal: Sends identification data to the server. Collected agricultural product data is sent to the server.

[1003] Step 9:

[1004] Server: Cross-checks inventory data. The server collects real-time inventory data from each sales facility and cross-checks it with the identified produce.

[1005] Step 10:

[1006] Server: Determines the appropriate sales facility. The server determines the optimal sales facility based on inventory data and agricultural product data. This information is sent to the autonomous transport vehicle.

[1007] Step 11:

[1008] Terminal: The truck handles label and brand design. AI generates labels based on themes and messages set by the user inside the truck and attaches them to the produce.

[1009] Step 12:

[1010] Terminal: Initiate delivery to the appropriate sales facility. The autonomous delivery vehicle departs for the designated sales facility.

[1011] Step 13:

[1012] Terminal: Arrives at the sales facility and delivers the produce. When the truck arrives at the sales facility, it automatically unloads the produce and completes the delivery process.

[1013] Step 14:

[1014] Server: Generates sales promotion data. The server generates sales promotion data about delivered agricultural products and distributes it to the information display device in the sales facility.

[1015] Step 15:

[1016] Server: Display promotional messages. Display promotional messages such as "Fresh produce in stock!" on the information display devices of the sales facility.

[1017] This process automates the collection, identification, distribution, labeling, branding, and promotion of produce.

[1018] Example 1

[1019] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1020] The traditional process of collecting and delivering agricultural products requires a lot of manual work, making it difficult to operate efficiently. In particular, managing harvest schedules, collecting produce on-site, identifying them, inspecting their quality, labeling them, designing their brands, and delivering them to the appropriate sales facilities all require manual work, which is time-consuming and labor-intensive. It is also difficult to ensure the quality of the produce while quickly shipping them to market. There is a need to solve these problems and automate the process from produce collection to sales, streamlining it.

[1021] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1022] In this invention, the server includes: means for inputting a harvest plan for agricultural produce; means for generating a collection schedule based on the harvest plan; means for directing agricultural machinery to each producer based on the generated schedule; means for collecting the agricultural produce when the agricultural machinery arrives at the producer; means for performing image analysis to identify the collected agricultural produce; means for comparing data on the identified agricultural produce with inventory data at sales facilities; means for determining an appropriate sales facility based on the inventory data at the sales facility; means for transmitting information about the sales facility to the agricultural machine; means for the agricultural machine to deliver the agricultural produce to the sales facility; means for affixing labels to the agricultural produce during delivery; means for applying a brand design to the agricultural produce; means for delivering the agricultural produce at the sales facility; means for generating sales promotion data for the delivered agricultural produce; and means for distributing the sales promotion data to an information display device at the sales facility. This automates the entire process of collecting, identifying, delivering, branding, and promoting agricultural produce, significantly reducing the workload of producers and sales facilities and enabling agricultural products to be shipped to market quickly while maintaining their quality.

[1023] "Agricultural machinery" refers generally to any equipment used to automate or mechanize agricultural operations, including specifically collection and delivery equipment such as autonomous transport vehicles.

[1024] "Harvest schedule" refers to information such as the type, quantity, and location of agricultural produce that is scheduled to be harvested on a specific date and time.

[1025] A "collection schedule" refers to the planned operation of agricultural machinery, with optimal routes and times planned based on the harvest schedule.

[1026] "Producers" refers to farmers and agricultural managers who cultivate and harvest crops.

[1027] "Image analysis" refers to the technology of analyzing image data collected using cameras and sensors to identify the type and quality of agricultural products.

[1028] "Inventory data" refers to information such as the types and quantities of agricultural products currently stored at sales facilities.

[1029] "Sales facility" refers to the point or place where agricultural products are sold to consumers, including farm shops and supermarkets.

[1030] A "label" is an information tag attached to agricultural products and is used to display the product's name, characteristics, brand message, etc.

[1031] "Brand design" refers to the designs and marketing messages used to enhance the brand value of specific agricultural products or producers.

[1032] "Promotional data" refers to information intended to promote the sale of agricultural products, and refers to digital content including features and recommended points.

[1033] "Information display device" refers to a device used to provide information to customers, such as a display or signage used in a sales facility.

[1034] The present invention relates to a system for collecting and delivering agricultural produce to sales facilities using autonomous transport vehicles. The system is designed to improve the efficiency of agricultural operations and operates using specific hardware and software.

[1035] Hardware and software used

[1036] Hardware:

[1037] Self-driving transport vehicles (agricultural machinery)

[1038] Smartphone or tablet (for inputting harvest schedule)

[1039] Sensors and cameras (for collecting and identifying produce)

[1040] Image analysis equipment and quality inspection equipment (located inside agricultural machinery)

[1041] software:

[1042] Harvest schedule input application

[1043] Collection Schedule Generation Algorithm

[1044] GPS navigation system

[1045] Image and data analysis software

[1046] Label Creation and Brand Design Software

[1047] Promotional data generation and distribution software

[1048] System Operation

[1049] The system operates in the following steps.

[1050] 1. Input harvest schedule

[1051] The user uses a smartphone or tablet to input harvest schedule data (date and time, type of produce, quantity, etc.) into a harvest schedule input application. This data is automatically sent to the server.

[1052] 2. Generate a pickup schedule

[1053] The server analyzes the collected harvest schedule data and generates an optimal collection schedule. The collection schedule is based on the farmer's location information and calculates the most efficient route. This schedule is then sent to the autonomous transport vehicle.

[1054] 3. Setting up autonomous driving routes

[1055] A terminal is installed inside the autonomous transport vehicle and sets the optimal route based on the schedule information received from the server. The autonomous transport vehicle then begins operating according to the set route.

[1056] 4. Collecting agricultural products

[1057] The terminal controls sensors and cameras inside the autonomous transport vehicle, and collects produce upon arrival at the farm, which is then placed in a collection container inside the truck.

[1058] 5. Produce Identification

[1059] The terminal uses the truck's in-vehicle image analysis system to identify the type and quality of the collected produce, and this identification data is then sent back to the server.

[1060] 6. Decision on sales facilities

[1061] The server matches the identification data with the store's inventory data to determine the appropriate store, and sends the results to the autonomous transport vehicle.

[1062] 7. Label and brand design

[1063] The device generates labels and designs the brand based on themes and messages preset by the user, and the generated labels are automatically affixed to the produce.

[1064] 8. Produce Delivery

[1065] The autonomous vehicle will navigate to the sales facility based on the navigation route set by the device, and upon arrival, it will automatically unload the produce and complete the delivery.

[1066] 9. Providing promotional data

[1067] The server generates promotional data based on the delivery completion data and distributes it to the information display device at the sales facility. This promotional data includes the characteristics and recommended points of the agricultural products.

[1068] Specific examples

[1069] A user enters into their smartphone that they plan to harvest tomatoes on May 1st. This input data is sent to a server, which generates an optimal collection schedule and sends it to an autonomous transport vehicle. The device sets the route to arrive at Farm A at 9:00 a.m. When the transport vehicle arrives at Farm A, it automatically collects the tomatoes and stores them in the truck. The tomato identification data is sent to the server, which checks it against Farm Store B and decides to deliver the tomatoes to Farm Store B, and sends this information to the transport vehicle. On the way to Farm Store B, an "organic fresh" label is affixed to the transport vehicle, and the tomatoes are delivered after arrival. The server displays a promotional message on the digital signage at Farm Store B saying, "Fresh organic tomatoes from Farm A have arrived!"

[1070] The system streamlines and automates the entire process of agricultural produce, from collection to distribution, identification, branding and promotion.

[1071] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1072] Program processing steps

[1073] Step 1: Enter your harvest plan

[1074] A user uses a smartphone or tablet to input data about planned harvesting (date and time, type of produce, quantity, etc.) into a harvest plan input application.

[1075] Input: Data such as planned harvest date and time, type of produce, and quantity.

[1076] Output: Harvest forecast data is sent to the server.

[1077] How it works: A user opens the application, enters their harvest schedule, and presses the "Submit" button.

[1078] Step 2: Generate a collection schedule

[1079] The server analyzes the collected harvest schedule data and generates an optimal harvest schedule.

[1080] Input: Harvest schedule data, location information of each producer.

[1081] Data processing: Harvest forecast data is analyzed and combined with each producer's location information.

[1082] Output: A collection schedule is generated and sent to the autonomous transport vehicle.

[1083] How it works: Using harvest schedule data collected by the server, it calculates the optimal visit sequence and sets an efficient route.

[1084] Step 3: Set up your self-driving route

[1085] The terminal is installed inside the autonomous transport vehicle and sets the optimal route based on the schedule information received from the server.

[1086] Input: Collection schedule sent from the server.

[1087] Data calculation: Based on the received schedule data, the navigation system calculates the optimal route.

[1088] Output: The automated driving route is set.

[1089] Operation: The device inputs schedule data into the navigation system and sets up an automated driving route.

[1090] Step 4: Collect produce

[1091] The terminal controls sensors and cameras inside the autonomous transport vehicle and collects agricultural products when it arrives at the farm.

[1092] Input: Farmer location information, crop location data from sensors and cameras.

[1093] Data processing: Analyze data from sensors and cameras to identify the location for collecting produce.

[1094] Output: The collected produce is stored in a collection container inside the truck.

[1095] How it works: The transport vehicle arrives at the farm and the collector activates to collect the produce.

[1096] Step 5: Identify the produce

[1097] The terminal uses an image analysis system inside the truck to identify the type and quality of the produce collected.

[1098] Input: Collected image data of agricultural products.

[1099] Data analysis: Image analysis systems identify the type and quality of agricultural products.

[1100] Output: The identified produce data is sent to the server.

[1101] How it works: The device takes images of the collected produce, and the image analysis system analyzes the data.

[1102] Step 6: Determine your sales facility

[1103] The server matches the identification data with the sales establishment's inventory data to determine the appropriate sales establishment.

[1104] Input: Identified produce data, sales facility inventory data.

[1105] Data calculation: Matching identification data with inventory data to determine the best sales facility.

[1106] Output: The appropriate sales facility is determined and the information is sent to the autonomous transport vehicle.

[1107] How it works: The server scans all inventory data it has access to and determines which sales facility to deliver the produce to.

[1108] Step 7: Label and brand design

[1109] The device generates labels and designs the brand based on themes and messages preset by the user.

[1110] Input: User-defined themes, messages, and identification data.

[1111] Data Processing: Generate label and brand designs based on user settings and identification data.

[1112] Output: The generated label is attached to the produce.

[1113] How it works: The device designs labels based on a theme and automatically applies them to produce.

[1114] Step 8: Deliver your produce

[1115] An autonomous transport vehicle will operate to the sales facility based on the navigation route set on the terminal.

[1116] Input: Sales facility information, navigation route.

[1117] Data calculation: The navigation system recalculates the route and heads towards the destination.

[1118] Output: The autonomous transport vehicle arrives at the sales facility and delivers the produce.

[1119] How it works: The transport vehicle follows a designated route to the sales facility and automatically unloads the produce upon arrival.

[1120] Step 9: Provide promotional data

[1121] The server generates sales promotion data based on the delivery completion data and distributes it to the information display device of the sales facility.

[1122] Input: Delivery completion data, agricultural product characteristics information.

[1123] Data processing: Generate promotional data based on delivery completion data and agricultural product characteristics information.

[1124] Output: The generated sales promotion data is delivered to an information display device in the sales facility.

[1125] Operation: The server analyzes the data after delivery is completed, generates promotional messages, and distributes them to digital signage.

[1126] (Application example 1)

[1127] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1128] Current agricultural produce collection and delivery systems face many challenges in terms of efficiency and accuracy. In particular, farmers must manage their harvest schedules individually, making it difficult for collection vehicles to set efficient routes for each farm. Quality control of collected produce also relies heavily on manual labor, making it difficult to accurately grasp quality data and deliver it to the appropriate sales facility. Furthermore, the creation and display of sales promotion data is also done manually, resulting in a lack of real-time response. To solve these problems, a system is needed that automates the entire process, from inputting harvest schedules to sales promotion at sales facilities.

[1129] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1130] In this invention, the server includes means for inputting planned harvesting of agricultural products, means for generating a collection schedule based on the planned harvesting, means for directing an autonomous transport vehicle to each farm based on the generated schedule, means for collecting the agricultural products when the autonomous transport vehicle arrives at the farm, means for performing image analysis to identify the collected agricultural products, means for comparing data on the identified agricultural products with inventory data at the sales facility, means for determining an appropriate sales facility based on the inventory data at the sales facility, means for transmitting information about the sales facility to the autonomous transport vehicle, means for the autonomous transport vehicle to deliver the agricultural products to the sales facility, means for affixing labels to the agricultural products during delivery, means for applying brand designs to the agricultural products, means for delivering the agricultural products at the sales facility, means for generating promotional data regarding the delivered agricultural products, means for distributing the promotional data to an information display device at the sales facility, means for inputting the harvest schedule using a smart device, means for transmitting quality data to the server, and means for generating a prompt message for the information display device. This enables the entire process of harvesting, collecting, identifying, delivering, labeling, and generating delivery and promotional data for agricultural products to be carried out efficiently and accurately.

[1131] The "means for inputting planned harvesting of agricultural produce" is a device that provides an interface that allows farmers to input the planned harvest date, type, and quantity using a smart device.

[1132] The "means for generating a collection schedule based on the harvest schedule" is a device that collects data on the harvest schedule and automatically generates an optimal collection schedule based on the location information of each farmer.

[1133] The "means for directing autonomous transport vehicles to each farm based on the generated schedule" is a device that receives schedule information from the server and instructs the autonomous transport vehicles to move according to that information.

[1134] "Means for collecting agricultural produce when an autonomous transport vehicle arrives at a farm" refers to a device that uses sensors and cameras installed inside the transport vehicle to recognize and automatically collect agricultural produce.

[1135] "Means for performing image analysis to identify collected produce" means a device that uses an image analysis system located within the truck to identify the type and quality of collected produce.

[1136] The "means for checking data on identified agricultural products against inventory data at the sales facility" is a device that transmits data on identified agricultural products to a server and checks the data against inventory data at the sales facility in real time.

[1137] The "means for determining an appropriate sales facility based on inventory data of the sales facility" is a device in which the server analyzes inventory data and automatically determines to which sales facility each agricultural product should be delivered.

[1138] The "means for transmitting information about the sales facility to the autonomously driven transport vehicle" is a device that transmits information about the determined sales facility to the autonomously driven transport vehicle and instructs the transport vehicle to move based on that information.

[1139] "Means for an autonomous transport vehicle to deliver agricultural produce to a sales facility" refers to a device for an autonomous transport vehicle to deliver agricultural produce to a sales facility according to a determined route.

[1140] The "means for labeling produce during delivery" refers to a device that automatically generates and applies labels to collected produce.

[1141] The "means for applying brand design to agricultural products" is a device that automatically applies brand design to labels based on a theme or message set by the user.

[1142] The "means for delivering agricultural produce at the sales facility" is a device that allows an autonomous transport vehicle to arrive at the sales facility and automatically unload and deliver the agricultural produce.

[1143] The "means for generating sales promotion data relating to delivered agricultural products" is a device that automatically generates sales promotion data including the characteristics and recommended points of the agricultural products delivered at the sales facility on a server.

[1144] The "means for distributing promotional data to an information display device in a sales facility" is a device that distributes the generated promotional data to an information display device such as digital signage in a sales facility.

[1145] "Means for inputting harvest plans using a smart device" refers to an interface for inputting harvest plans using a device such as a smartphone or tablet.

[1146] The "means for transmitting quality data to the server" is a device that transmits quality data of agricultural products identified by the image analysis system to the server in real time.

[1147] The "means for generating a prompt sentence on the information display device" is a device that automatically generates a prompt sentence based on sales promotion data and displays it on the information display device.

[1148] The present invention is a system for collecting agricultural produce and delivering it to a sales facility using an autonomous transport vehicle. This system automates a series of operations using specific means, from the user inputting the harvest schedule to the generation and display of sales promotion data at the sales facility. Specific embodiments are described below.

[1149] First, the user (farmer) uses a smart device (e.g., smartphone or tablet) to input the planned harvesting of agricultural produce. The input data is sent to the server. Based on this harvest plan data, the server generates an optimal collection schedule that reflects the location information of each farmer. The generated schedule is then sent to the autonomous transport vehicle.

[1150] Next, a terminal installed in the autonomous transport vehicle sets the optimal route based on the schedule information received from the server. This allows the autonomous transport vehicle to visit farms efficiently. When the transport vehicle arrives at the farm, the terminal uses sensors and cameras to recognize the produce and automatically collects it. The collected produce is stored in a collection container inside the truck.

[1151] The image analysis system inside the truck then identifies the type and quality of the collected produce, and the identified data is sent to a server. The server compares the identified produce data with the inventory data of the sales facility and determines which sales facility each produce should be delivered to. This delivery information is sent to the terminal of the autonomous transport vehicle.

[1152] Additionally, the terminals handle labeling and branding while the produce is being delivered. Labels are automatically generated and applied to the produce based on a theme or message predefined by the user. When the truck arrives at the sales facility, the produce is automatically unloaded and delivered.

[1153] Once delivery is complete, the server generates promotional data for the delivered produce, including the produce's features and recommended points. The generated promotional data is distributed to information display devices (such as digital signage) at the sales facility, providing consumers with real-time visual information.

[1154] As an example, the following process is performed:

[1155] 1. User Input:

[1156] A user enters "Harvest 200 kg of tomatoes on May 1st" into a smartphone app.

[1157] 2. Server processing:

[1158] Based on the harvest schedule data received by the server, the optimal collection route is generated and sent to the autonomous transport vehicle.

[1159] 3. Collection by vehicle:

[1160] The autonomous transport vehicle arrives at the farm at the designated time and collects the tomatoes. At the time of collection, an image analysis system acquires the quality data of the tomatoes and sends it to a server.

[1161] 4.Delivery destination determination:

[1162] The server determines the best sales facility based on the quality data and transmits this information to the autonomous transport vehicle.

[1163] 5. Label and brand design:

[1164] Labels are generated on board the truck and attached to the tomatoes, with designs based on the theme "organic fresh."

[1165] 6. Delivery and promotional data generation:

[1166] A truck arrives at the sales facility to deliver the tomatoes. A promotional message is generated and displayed on the digital signage: "Fresh farm-fresh organic tomatoes in stock!"

[1167] An example of a prompt sentence would be, "Enter data as a farmer who plans to harvest tomatoes on May 1st. The route is set so that an autonomous vehicle will visit at 9:00, and the collected data on the quality of the agricultural products will be sent to the server in real time. Delivery destination determination and label generation are also automated."

[1168] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1169] Step 1:

[1170] Users use a smartphone or tablet to input their planned harvesting schedule. Specifically, they input data through an interface that allows them to input the planned harvest date, type, and quantity. This input data is then sent to the server. The input data includes the user ID, type of produce, planned harvest date, and harvest quantity.

[1171] Step 2:

[1172] Based on the harvest schedule data it receives, the server generates an optimal collection schedule that reflects the location information of each farmer. The server combines GPS data and harvest schedule data to calculate the most efficient route. The generated schedule is sent to the autonomous transport vehicle's terminal. The input data is the harvest schedule data and GPS data, and the output is the optimal collection schedule.

[1173] Step 3:

[1174] The terminal sets the optimal route for the autonomous transport vehicle based on the schedule information received from the server. The terminal analyzes the route information and gives instructions to the autonomous transport vehicle. Specifically, it calculates the order of farms to visit and the shortest route, and reflects this in the autonomous transport vehicle. The input data is the collection schedule, and the output is route setting information.

[1175] Step 4:

[1176] An autonomous transport vehicle visits farms according to a designated route. When the transport vehicle arrives at a farm, a terminal uses sensors and cameras to recognize the produce and automatically collects it. The collected produce is stored in a collection container inside the truck. The data collected by the sensors and cameras is used to confirm whether the produce has been collected correctly. The input data is route setting information, and the output is information about the collected produce.

[1177] Step 5:

[1178] The collected produce is identified by an image analysis system inside the truck. The terminal sends the data obtained from the image analysis system to a server. The image analysis system identifies the type and quality of the collected produce and sends the data to the server. The input data is image data of the collected produce, and the output is data on the identified produce.

[1179] Step 6:

[1180] The server compares the identified produce data with the sales facility inventory data and determines which sales facility each produce should be delivered to. The server analyzes the inventory data and produce data and selects the most suitable sales facility. This information is sent to the autonomous transport vehicle's terminal. The input data is the identified produce data and inventory data, and the output is information about the sales facility to which the produce should be delivered.

[1181] Step 7:

[1182] The server sends information about the sales facility to the autonomous vehicle. Based on this information, the terminal issues instructions for the autonomous vehicle to head to the designated sales facility. The input data is the sales facility information, and the output is delivery instructions.

[1183] Step 8:

[1184] During delivery, the terminal automatically generates and affixes labels to the produce. The labels are generated using themes and messages preset by the user. The brand design is also applied to the produce. The input data is the user's label settings information, and the output is the affixed label and brand design.

[1185] Step 9:

[1186] When the autonomous transport vehicle arrives at the sales facility, the terminal automatically unloads and delivers the produce. Once delivery is complete, the terminal sends delivery completion data to the server. The input data is delivery instructions, and the output is delivery completion data.

[1187] Step 10:

[1188] The server generates promotional data based on the delivery completion data. The generated promotional data includes the characteristics and recommended points of the agricultural products. This automatically generates the promotional data to be displayed on the information display device of the sales facility. The input data is the delivery completion data, and the output is the promotional data.

[1189] Step 11:

[1190] The server distributes the generated sales promotion data to the information display device in the sales facility, allowing consumers to check the characteristics and recommended points of agricultural products in real time. The input data is the sales promotion data, and the output is the distribution data to the information display device.

[1191] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1192] The present invention combines a system that uses autonomous transport vehicles to collect agricultural produce and deliver it to sales facilities with an emotion engine that recognizes user emotions, allowing the system to optimize its operation based on the user's emotions and provide more personalized services.

[1193] 1. Input harvest schedule

[1194] User: Enters planned harvesting of produce. As the user uses a smartphone or tablet to input the planned harvest date, type of produce, and quantity, the emotion engine recognizes the user's emotions and optimizes the system's settings and information provision based on the input.

[1195] 2. Generate a pickup schedule

[1196] Server: Receives harvest schedule data and aggregates harvest schedule information from all farmers. Based on the emotion engine, generates an optimal collection schedule that reflects the user's emotions. For example, if a user is feeling anxious about harvesting, the system provides a function to flexibly adjust the schedule.

[1197] 3. Setting up autonomous driving routes

[1198] Terminal: The terminal installed in the autonomous transport vehicle sets the optimal route based on the schedule information received from the server. At this time, the emotion engine prioritizes routes that reduce stress as much as possible based on the user's emotions.

[1199] 4. Collecting agricultural products

[1200] Terminal: When the autonomous transport vehicle arrives at the farm, the terminal uses sensors and cameras to recognize the produce and automatically collect it. The emotion engine is sensitive to the user's emotions, and if the user is in a hurry, for example, the terminal will collect the produce quickly.

[1201] 5. Produce Identification

[1202] Terminal: An image analysis system inside the truck identifies the type and quality of the produce collected. This information is sent to a server.

[1203] 6. Decision on sales facilities

[1204] Server: Using the identified product data, it compares it with the inventory data of each sales facility and decides which sales facility to deliver each product to. The emotion engine optimizes the selection of sales facility to improve user satisfaction.

[1205] 7. Label and brand design

[1206] Terminal: Labeling and branding is done inside the truck. Based on themes and emotions predefined by the user, an emotion engine generates personalized labels and branding to be applied to produce.

[1207] 8. Produce Delivery

[1208] Terminal: The autonomous transport vehicle will make the delivery to the selected sales facility. When the truck arrives at the sales facility, it will automatically unload and deliver the produce.

[1209] 9. Providing promotional data

[1210] Server: When agricultural products are delivered to a sales facility, the server generates promotional data based on the emotion engine. This data includes the characteristics and recommended points of the agricultural products, and is distributed to information display devices (such as digital signage) at the sales facility.

[1211] Specific examples

[1212] User: Farmer A enters his / her tomato harvesting plans for May 1st into the application. The emotion engine analyzes the user's facial expressions and tone of voice when entering data and recognizes that he / she is feeling anxious. Based on this, the system flexibly adjusts the harvesting schedule.

[1213] Server: Receives harvest schedule data, generates the optimal collection route, and sends it to the autonomous transport vehicle.

[1214] Terminal: The autonomous transport vehicle sets a route to arrive at Farm A at 9:00 a.m. and departs. When the truck arrives at Farm A, it quickly collects the tomatoes and stores them inside the truck. Based on the emotion engine, collection is fast and efficient.

[1215] Terminal: The image analysis system identifies the tomato and sends the data to the server.

[1216] Server: Checks the inventory information of the sales facility and decides to deliver the tomatoes to Direct Sales Store B. This information is sent to the truck.

[1217] Device: Label and brand design, labeling tomatoes based on the theme "organic fresh," incorporating design elements that respond to user emotions.

[1218] Terminal: Departs for the farm shop B and delivers the tomatoes after arriving. The delivery process is optimized based on the emotion engine.

[1219] Server: The server generates a promotional message saying, "Fresh organic tomatoes from Farm A have arrived!" and displays it on the digital signage at Farm B's farm store.

[1220] The integrated system provides a personalized service that is sensitive to the user's emotions, automating the collection, identification, delivery, labeling, branding, and promotion of agricultural products.

[1221] The processing flow will be explained below.

[1222] Step 1:

[1223] User: Entering planned harvesting of produce. Using a smartphone or tablet, the user enters the planned harvest date, type of produce, and quantity into the application. The emotion engine analyzes the user's facial expressions and voice tone to assess their emotional state.

[1224] Step 2:

[1225] Server: Receives harvest schedule data and emotion data. The server saves the input harvest schedule data, analyzes the user's emotion data, and aggregates the harvest schedule information of all farmers.

[1226] Step 3:

[1227] Server: Generates a collection schedule. The server calculates the optimal collection route based on each farmer's location information and the expected harvest date, and creates a schedule. If the user's emotions are unstable, it provides a flexible schedule. This schedule information is sent to the autonomous transport vehicle.

[1228] Step 4:

[1229] Terminal: Sets the autonomous driving route. The terminal installed in the autonomous transport vehicle sets the autonomous driving route based on the schedule information received from the server. The emotion engine prioritizes routes that reduce stress based on the user's emotions.

[1230] Step 5:

[1231] Terminal: Start automatic driving. The automatic transport vehicle departs according to the set route and heads towards the farm.

[1232] Step 6:

[1233] Terminal: After arriving at the farm, the farmer collects the produce. The terminal uses sensors and cameras to recognize the produce and automatically collects it. If the user is in a hurry, the emotion engine speeds up the collection process.

[1234] Step 7:

[1235] Terminal: Identifies agricultural products. The image analysis system inside the truck identifies the type and quality of the collected agricultural products and sends the data to a server.

[1236] Step 8:

[1237] Server: Cross-checks inventory data. The server collects real-time inventory data from each sales facility and cross-checks it with the identified produce.

[1238] Step 9:

[1239] Server: Determines the appropriate sales facility. The server determines the optimal sales facility based on inventory data and agricultural product data. The emotion engine optimizes the delivery destination selection based on the user's emotions. This information is sent to the terminal of the autonomous transport vehicle.

[1240] Step 10:

[1241] Terminal: The truck generates the label and brand design. Based on the theme and message set by the user in the truck, AI generates the label and attaches it to the produce. The emotion engine optimizes the design according to the user's emotions.

[1242] Step 11:

[1243] Terminal: Start delivery to the sales facility. The autonomous transport vehicle departs for the designated sales facility.

[1244] Step 12:

[1245] Terminal: Arrives at the sales facility and delivers the produce. When the truck arrives at the sales facility, it automatically unloads the produce and completes the delivery process.

[1246] Step 13:

[1247] Server: Generates sales promotion data. The server generates sales promotion data about delivered agricultural products and distributes it to the information display device of the sales facility. Based on the emotion engine, it creates promotional messages that match the user's emotions.

[1248] Step 14:

[1249] Server: Display promotional messages. Promotional messages that take into account emotions, such as "Fresh produce in stock!", are displayed on the information display devices of sales facilities.

[1250] This process provides a personalized and responsive service to users, automating the collection, identification, delivery, labeling, branding, and promotion of produce.

[1251] Example 2

[1252] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1253] In a system that uses autonomous transport vehicles to collect and deliver agricultural produce to sales facilities, conventional technology sets uniform schedules and routes without considering the user's feelings, which leads to problems of low user satisfaction and efficiency.In addition, the process from collecting agricultural produce to delivery and sales promotion is not effectively automated, resulting in wasted effort and time.

[1254] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1255] In this invention, the server includes means for analyzing a user's emotions using an emotion engine and inputting a harvest schedule for agricultural produce, means for generating a collection schedule according to the harvest schedule based on the emotion engine, and means for transmitting the generated schedule information to a terminal of the autonomous transport vehicle and setting a route, thereby enabling efficient and personalized collection, delivery, and sales of agricultural produce that takes into consideration the user's emotions.

[1256] An "emotion engine" is software or hardware for analyzing a user's emotions and generating emotion data from facial expressions and voice.

[1257] "Harvest schedule" is data including information such as the harvest date, type, and quantity of agricultural produce, and is entered into the system by the user.

[1258] The "collection schedule" is a plan that determines the order and timing of visits by autonomous transport vehicles based on the harvest schedule.

[1259] An "autonomous delivery vehicle" is a vehicle that has the ability to drive autonomously and collect and deliver agricultural produce.

[1260] A "sensor" is a device that detects environmental information or the state of an object, and is used when collecting agricultural products.

[1261] "Camera" means a device that captures images and is used to identify agricultural products and inspect their quality.

[1262] "Image analysis" is a technology that identifies the type and quality of agricultural products from photographed images.

[1263] "Inventory data" refers to data that indicates the current inventory status of agricultural products at a sales facility.

[1264] A "label" is an information sheet that is affixed to agricultural products and includes the product name and producer information.

[1265] "Brand design" refers to the design applied to the packaging and labels of agricultural products, and is used to increase purchasing desire.

[1266] "Sales promotion data" refers to data generated for sales promotion purposes, and includes product features and recommended points.

[1267] An "information display device" is a digital signage or display device installed in a sales facility for displaying sales promotion data.

[1268] This invention is a system that uses autonomous transport vehicles to collect agricultural products and deliver them to sales facilities, and by combining it with an emotion engine, provides optimal services that meet the individual needs of users. This invention is composed of users, a server, and terminals.

[1269] First, the user uses a smartphone or tablet to input their planned harvesting schedule (date, type, and quantity). The system is equipped with an emotion engine that analyzes emotional data from the user's facial expressions and voice, and optimizes system settings and information provision based on this. Specifically, if the user is feeling anxious, the emotion engine detects this and flexibly adjusts the harvesting schedule to reduce the user's stress.

[1270] The server aggregates harvest schedule data received from users and analyzes the harvest schedule information of all farmers. Based on the emotion engine, it generates an optimal collection schedule and sends it to the autonomous transport vehicle's terminal. This schedule includes an efficient and user-friendly visit sequence and timing.

[1271] Next, the autonomous vehicle's terminal receives the schedule information and uses the navigation system to set the optimal route. This route is selected with consideration for the user's emotions, with priority given to routes that cause as little stress as possible. The vehicle then travels along the set route and arrives at each farm.

[1272] When the transport vehicle arrives at the farm, the terminal's sensors and cameras scan the produce and take appropriate collection action. The collected produce is identified by an image analysis system for type and quality, and this data is sent to a server. The server compares this data with inventory information from sales facilities and determines the appropriate sales facility.

[1273] Once a sales facility is determined, that information is sent to the autonomous vehicle, which reroutes it. During delivery, labeling and branding are performed, and personalized labels are applied to the produce. Design elements are incorporated based on the user's emotions and themes.

[1274] Finally, when the autonomous vehicle arrives at the sales facility, it automatically unloads the produce and delivers it to the facility. After delivery, the server generates promotional data based on the emotion engine and distributes it to information display devices such as digital signage at the sales facility. This allows for effective promotion of the produce at the sales facility.

[1275] Examples:

[1276] The user, a farmer, opens the app on their smartphone and inputs their harvest schedule. For example, they might input "I plan to harvest tomatoes on May 1st." The emotion engine analyzes the user's facial expressions and voice when they input their data, and if the user seems anxious, the server will flexibly adjust the harvest schedule.

[1277] An example of a prompt using a generative AI model could be, "Describe a new produce collection system. Include a process where an emotion engine analyzes user emotions, and autonomous vehicles collect and deliver produce to sales facilities."

[1278] This system enables efficient and personalized collection, delivery, and sales of agricultural products that take into consideration the user's feelings.

[1279] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1280] Step 1:

[1281] User: Uses a smartphone or tablet to input planned harvest information (date, type, and quantity).

[1282] Input: The user enters details of the planned harvest into the application.

[1283] Data processing: The emotion engine uses the camera and microphone to analyze the user's facial expressions and voice in real time and generate emotion data.

[1284] Output: Harvest schedule data and emotion data are sent to the server.

[1285] How it works: A user opens the application and fills in a form with details of their harvest. The emotion engine analyzes facial expressions and tone of voice in real time to obtain emotional data. Finally, this data is sent to the server.

[1286] Step 2:

[1287] Server: Aggregates harvest schedule data and emotion data, and analyzes the harvest schedule information of all farmers.

[1288] Input: Harvest schedule data and emotion data.

[1289] Data processing: Based on the emotion engine, the optimal pickup schedule is generated taking into account the user's emotions.

[1290] Output: The generated collection schedule is sent to the autonomous transport vehicle terminal.

[1291] Specific operation: The server receives harvest plan data and emotion data sent from each farmer, and uses an algorithm to determine a collection schedule that takes into account efficiency and user emotions, and sends it to the transport vehicle.

[1292] Step 3:

[1293] Terminal: The terminal inside the autonomous transport vehicle receives the schedule information and uses the navigation system to plan the optimal route.

[1294] Input:Pickup Schedule.

[1295] Data processing: The navigation system calculates the optimal route taking into account the data from the emotion engine.

[1296] Output: The transport vehicle starts moving based on the set route.

[1297] Specific operation: The terminal receives the collection schedule, calculates the optimal route with the least stress, and moves the autonomous delivery vehicle.

[1298] Step 4:

[1299] Terminal: When the self-driving transport vehicle arrives at the farm, it uses sensors and cameras to recognize the produce and automatically collects it.

[1300] Input: Sensor and camera data.

[1301] Data processing: Real-time image analysis data is used to identify agricultural products and perform collection operations.

[1302] Output: Collected produce.

[1303] Specific operation: The terminal's sensors and camera scan the produce, and an automatic collection mechanism collects the produce and stores it in a truck.

[1304] Step 5:

[1305] Terminal: The image analysis system identifies the type and quality of the collected produce and sends this information to the server.

[1306] Input: Collected image data of agricultural products.

[1307] Data processing: Image analysis system identifies type and quality.

[1308] Output: The identified data is sent to the server.

[1309] Specific operation: The device's image analysis system takes a photo of the produce, and the AI ​​model analyzes the type and quality, then sends the data to a server.

[1310] Step 6:

[1311] Server: Matches the data of identified agricultural products with the inventory data of the sales facility and determines the delivery destination.

[1312] Input: Produce data and inventory data.

[1313] Data processing: AI algorithms compare inventory data and determine the appropriate delivery destination.

[1314] Output: Delivery information is sent to the autonomous delivery vehicle.

[1315] Specific operation: The server compares agricultural product data with inventory data from each sales facility, determines the appropriate delivery destination, and sends that information to the autonomous transport vehicle.

[1316] Step 7:

[1317] Terminal: The autonomous delivery vehicle performs label and branding during delivery, generating personalized labels to apply to produce.

[1318] Input: Shipping information and emotion data.

[1319] Data processing: Generate labels and designs based on the emotion engine, then print and paste them.

[1320] Output: Labeled produce.

[1321] Specific operation: The device generates labels and designs based on the user's set theme and emotion, automatically prints them, and attaches the labels to the produce.

[1322] Step 8:

[1323] Terminal: An autonomous transport vehicle arrives at the sales facility and automatically unloads and delivers the produce.

[1324] Input: Shipping information.

[1325] Data Processing: Optimize the delivery process.

[1326] Output: Delivery complete.

[1327] Specific operation: After the terminal arrives at the sales facility, it automatically unloads the produce from the autonomous transport vehicle and completes the delivery process.

[1328] Step 9:

[1329] Server: Generates sales promotion data about delivered agricultural products and distributes it to the information display devices at the sales facility.

[1330] Input: Delivery data and sentiment data.

[1331] Data processing: Generate promotional data based on the emotion engine.

[1332] Output: Promotional data is displayed on an information display device.

[1333] Specific operation: The server checks the delivery data, works with the emotion engine to generate promotional data, and distributes it to digital signage and display devices at the sales facility.

[1334] (Application example 2)

[1335] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1336] Agricultural produce collection and delivery systems using autonomous transport vehicles can improve efficiency, but ignoring the user's emotional state can affect the quality of the work and user satisfaction. Personalized design that reflects emotions is also required for detailed tasks such as branding and labeling of agricultural products. A system that automates these tasks while optimizing them according to the user's emotional state is needed.

[1337] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server includes: means for inputting planned harvesting of agricultural products; means for generating a collection schedule based on the planned harvesting; means for directing an autonomous transport vehicle to each farm based on the generated schedule; means for collecting the agricultural products when the autonomous transport vehicle arrives at the farm; means for performing image analysis to identify the collected agricultural products; means for comparing data on the identified agricultural products with inventory data of sales facilities; means for determining an appropriate sales facility based on the inventory data of the sales facility; means for transmitting information on the sales facility to the autonomous transport vehicle; means for the autonomous transport vehicle to deliver the agricultural products to the sales facility; means for attaching labels to the agricultural products during delivery; means for applying brand designs to the agricultural products; means for delivering the agricultural products at the sales facility; means for generating promotional data regarding the delivered agricultural products; means for distributing the promotional data to an information display device of the sales facility; means including an emotion engine that recognizes user emotions and optimizes work; means for a factory robot to adjust work speed based on the emotions of a worker; and means for monitoring the emotions of a worker in real time using smart glasses. This will enable a personalized and efficient agricultural produce collection and delivery system that responds to user emotions.

[1338] An "autonomous transport vehicle" is a vehicle that has the ability to autonomously collect and deliver agricultural products without the need for a driver.

[1339] "Agricultural products" are food such as crops and fruits produced by agriculture.

[1340] "Harvest schedule" is information that predicts and plans the harvest of agricultural products at a specific date and time.

[1341] A "collection schedule" is a timetable or route planned to efficiently collect agricultural produce.

[1342] "Image analysis" is a technology in which a computer processes images taken with a camera to extract and identify specific information.

[1343] A "sales facility" is a place or building used to sell agricultural products to consumers.

[1344] "Inventory data" refers to information about the quantity and type of produce currently stored at a particular location.

[1345] A "label" is a display tag or sticker attached to a product that provides information such as the product name or brand name.

[1346] "Brand design" refers to the visual design elements and architecture associated with a particular brand.

[1347] An "emotion engine" is a technology that recognizes the user's emotional state and optimizes the system's operation based on that emotion.

[1348] A "factory robot" is a device that automatically performs tasks such as picking and packing within a factory.

[1349] "Smart glasses" are wearable devices equipped with functions such as a camera and a display, and can monitor the user's emotions and surrounding conditions in real time.

[1350] "Monitoring" is the act of continuously observing and recording a particular condition or environment.

[1351] The system that realizes this invention is composed of multiple elements such as smart glasses, an emotion engine, a factory robot, an autonomous transport vehicle, and a server.

[1352] Hardware and software used

[1353] Hardware

[1354] 1. Smart glasses: A wearable device equipped with an emotion-recognition camera for monitoring workers' emotions in real time.

[1355] 2. Factory robots: Robots that pick and pack products in the workplace.

[1356] 3. Autonomous transport vehicles: Vehicles that automatically collect and deliver agricultural produce.

[1357] software

[1358] 1. Emotion engine: An algorithm for analyzing the user's emotional state and optimizing the system's behavior.

[1359] 2. Server: Processes data, aggregates information, and manages it.

[1360] 3. Image analysis system: A system that analyzes images taken with a camera and identifies agricultural products and work environments.

[1361] Operation explanation

[1362] Smart Glasses Monitoring

[1363] The user wears the smart glasses, and the camera captures the user's facial expressions and tone of voice in real time. This data is sent to the emotion engine, which analyzes the user's emotional state. For example, if a worker is feeling stressed, the emotion engine will interpret the data as "high stress level."

[1364] Emotion Engine Operation

[1365] The emotion engine receives user emotional data and optimizes the behavior of factory robots and autonomous delivery vehicles based on that data. If stress levels are high, the robots' picking speed will be adjusted and their behavior will be changed to reduce the burden on workers.

[1366] Server Processing

[1367] The server receives harvest schedule data and emotion data, and generates optimal work schedules and routes based on that data. The server also compares this data with inventory information at sales facilities to optimize delivery destinations.

[1368] Specific examples

[1369] Imagine a factory worker wearing smart glasses picking produce. The smart glasses capture the worker's facial expressions, and the emotion engine analyzes them to determine that the worker is feeling a little stressed. Based on this data, the factory robot's working speed is set slightly slower, allowing the worker to continue working comfortably. This process reduces the worker's stress and enables efficient and safe work.

[1370] Prompt Sentence Examples

[1371] text

[1372] In this scenario, a factory worker wears smart glasses while a robot picks products. The robot works at an optimal speed depending on the worker's emotional state. Explain the algorithm that uses emotion-recognition cameras to monitor the worker's stress level and adjust the robot's behavior accordingly.

[1373] This will enable the realization of a personalized and efficient agricultural produce collection and delivery system that responds to user emotions.

[1374] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1375] Step 1:

[1376] A user puts on smart glasses and inputs their harvest schedule into a smartphone or tablet. At this time, the emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotional state. The input data (harvesting schedule and user's emotional data) is sent to the server. For example, if a user inputs "I will harvest tomatoes next Wednesday," the emotion engine will analyze that the user is feeling anxious based on their tone of voice and facial expression.

[1377] Step 2:

[1378] The server receives the harvest schedule data and emotion data. The server's collection schedule generation algorithm generates an optimal collection schedule based on the harvest schedule data and emotion data. At this time, the schedule is flexibly adjusted to reflect the user's anxiety. For example, consideration is given to avoiding early evening harvest times for users with high anxiety.

[1379] Step 3:

[1380] The collection schedule is sent to the autonomous transport vehicle, which then heads to each farm. A terminal inside the autonomous transport vehicle sets the optimal route based on the schedule data and departs. The vehicle also references the user's emotional data to select the least stressful route. For example, it prioritizes routes with less traffic.

[1381] Step 4:

[1382] When the autonomous vehicle arrives at the farm, it uses sensors and cameras to recognize the produce and automatically collects it. If the user is in a hurry, an algorithm is applied to expedite the collection process. For example, emotional data about a sense of urgency can speed up the collection process.

[1383] Step 5:

[1384] The image analysis system inside the autonomous transport vehicle identifies the type and quality of the collected produce and sends this identification data to a server. For example, after tomatoes are collected, the quality is quickly checked and the data is sent to the server.

[1385] Step 6:

[1386] The server compares the inventory data and identification data of the sales facilities to determine the most suitable sales facility. It also uses an emotion engine to select a sales facility that will improve user satisfaction. For example, it selects a sales facility with a higher rating than the previous one.

[1387] Step 7:

[1388] The information about the sales facility is sent to the autonomous vehicle, which then heads to the designated sales facility. During delivery, the labeling and branding functions are activated to apply personalized labels and branding to the produce based on emotions, such as a design based on an "organic fresh" theme.

[1389] Step 8:

[1390] The autonomous vehicle arrives at the sales facility and delivers the produce. During delivery, it uses an emotion engine to ensure a fast and efficient delivery process. For example, it delivers quickly during busy times and carefully during busy times.

[1391] Step 9:

[1392] The server generates promotional data about agricultural products delivered to the sales facility and distributes it to the facility's information display device (such as digital signage). Promotional messages incorporating personalized elements based on an emotion engine are generated. For example, a message such as "Fresh organic tomatoes have arrived!" can be set.

[1393] This will enable a personalized and efficient agricultural produce collection and delivery system that responds to user emotions.

[1394] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1395] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1396] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1397] [Fourth embodiment]

[1398] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1399] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1400] 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 a "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. The database 24 and the communication I / F 26 are also 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).

[1401] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. 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. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1402] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1403] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1404] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1405] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1406] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1407] The specific processing program 56 is an example of a "program" according to the technology of the present 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 in accordance with the specific processing program 56 executed on the RAM 30.

[1408] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1409] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1410] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1411] The present invention relates to a system for collecting agricultural produce using autonomous transport vehicles and delivering it to sales facilities. To implement the present invention, several key elements must function in combination. Each element and its specific function are described below.

[1412] 1. Input harvest schedule

[1413] User: Provides an interface for inputting planned harvesting of agricultural produce. Specifically, farmers can use their smartphones or tablets to input the planned harvest date, type, and quantity.

[1414] 2. Generate a pickup schedule

[1415] Server: Collects harvest schedule data and generates an optimal collection schedule based on each farmer's location information. The generated schedule is sent to the autonomous transport vehicle.

[1416] 3. Setting up autonomous driving routes

[1417] Terminal: The terminal installed in the autonomous transport vehicle sets the optimal route based on the schedule information received from the server, allowing the autonomous transport vehicle to visit farms efficiently.

[1418] 4. Collecting agricultural products

[1419] Terminal: When the autonomous transport vehicle arrives at the farm, the terminal uses sensors and cameras to recognize the produce and automatically collects it, which is then placed in a collection container inside the truck.

[1420] 5. Produce Identification

[1421] Terminal: An image analysis system inside the truck identifies the type and quality of the produce collected. This information is sent to a server.

[1422] 6. Decision on sales facilities

[1423] Server: Using the identified product data, the server compares it with the inventory data of each sales facility and determines which sales facility each product should be delivered to. The server sends this information to the terminal of the autonomous transport vehicle.

[1424] 7. Label and brand design

[1425] Terminal: Labeling and branding is done in the truck. Labels are automatically generated and applied to produce based on a theme or message predefined by the user.

[1426] 8. Produce Delivery

[1427] Terminal: The autonomous transport vehicle will make the delivery to the selected sales facility. When the truck arrives at the sales facility, it will automatically unload and deliver the produce.

[1428] 9. Providing promotional data

[1429] Server: When agricultural products are delivered to a sales facility, the server generates promotional data, which includes the characteristics and recommended points of the agricultural products, and distributes it to information display devices (such as digital signage) at the sales facility.

[1430] Specific examples

[1431] User: Farmer A enters his / her tomato harvesting plan for May 1st into the application. The harvest plan data is sent to the server.

[1432] Server: Based on the received harvest schedule data, it generates the optimal collection route and sends it to the autonomous transport vehicle.

[1433] Terminal: The autonomous transport vehicle sets a route to arrive at Farm A at 9:00 a.m. and departs. When the truck arrives at Farm A, it automatically collects the tomatoes and stores them inside the truck.

[1434] Terminal: The image analysis system identifies the tomato and sends the data to the server.

[1435] Server: Checks the inventory information of farm shop B and decides to deliver the tomatoes to farm shop B. This information is sent to the truck.

[1436] Terminal: A label based on the theme "Organic Fresh" is generated in the truck and attached to the tomatoes. The truck then departs for Farm Shop B.

[1437] Terminal B arrives at the direct sales store and automatically unloads and delivers the tomatoes.

[1438] Server: Generates a promotional message saying, "Fresh organic tomatoes from Farm A have arrived!" and displays it on the digital signage at Farm B's farm store.

[1439] The integrated system will efficiently and automatically carry out a series of processes, from collecting, identifying, delivering, branding and promoting agricultural products.

[1440] The processing flow will be explained below.

[1441] Step 1:

[1442] User: Enters the planned harvest date for agricultural produce. Specifically, the user uses a smartphone or tablet to enter the planned harvest date, type of produce, and amount.

[1443] Step 2:

[1444] Server: Receives harvest schedule data. The server saves the input data and aggregates harvest schedule information for all farmers.

[1445] Step 3:

[1446] Server: Generates a collection schedule. The server calculates the optimal collection route based on each farmer's location information and the planned harvest date, and creates a schedule. The generated schedule is sent to the autonomous transport vehicle.

[1447] Step 4:

[1448] Terminal: Sets the autonomous driving route. The terminal inside the truck sets the autonomous driving route based on the schedule information received from the server.

[1449] Step 5:

[1450] Terminal: Start automatic driving. The automatic transport vehicle heads to the farm according to the set route.

[1451] Step 6:

[1452] Terminal: After arriving at the farm, the terminal collects the produce. Using sensors and cameras, the terminal recognizes the produce and automatically loads it onto the truck.

[1453] Step 7:

[1454] Terminal: Identifies agricultural products. An image analysis system inside the truck identifies the collected produce and assesses its type and quality.

[1455] Step 8:

[1456] Terminal: Sends identification data to the server. Collected agricultural product data is sent to the server.

[1457] Step 9:

[1458] Server: Cross-checks inventory data. The server collects real-time inventory data from each sales facility and cross-checks it with the identified produce.

[1459] Step 10:

[1460] Server: Determines the appropriate sales facility. The server determines the optimal sales facility based on inventory data and agricultural product data. This information is sent to the autonomous transport vehicle.

[1461] Step 11:

[1462] Terminal: The truck handles label and brand design. AI generates labels based on themes and messages set by the user inside the truck and attaches them to the produce.

[1463] Step 12:

[1464] Terminal: Initiate delivery to the appropriate sales facility. The autonomous delivery vehicle departs for the designated sales facility.

[1465] Step 13:

[1466] Terminal: Arrives at the sales facility and delivers the produce. When the truck arrives at the sales facility, it automatically unloads the produce and completes the delivery process.

[1467] Step 14:

[1468] Server: Generates sales promotion data. The server generates sales promotion data about delivered agricultural products and distributes it to the information display device in the sales facility.

[1469] Step 15:

[1470] Server: Display promotional messages. Display promotional messages such as "Fresh produce in stock!" on the information display devices of the sales facility.

[1471] This process automates the collection, identification, distribution, labeling, branding, and promotion of produce.

[1472] Example 1

[1473] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1474] The traditional process of collecting and delivering agricultural products requires a lot of manual work, making it difficult to operate efficiently. In particular, managing harvest schedules, collecting produce on-site, identifying them, inspecting their quality, labeling them, designing their brands, and delivering them to the appropriate sales facilities all require manual work, which is time-consuming and labor-intensive. It is also difficult to ensure the quality of the produce while quickly shipping them to market. There is a need to solve these problems and automate the process from produce collection to sales, streamlining it.

[1475] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1476] In this invention, the server includes: means for inputting a harvest plan for agricultural produce; means for generating a collection schedule based on the harvest plan; means for directing agricultural machinery to each producer based on the generated schedule; means for collecting the agricultural produce when the agricultural machinery arrives at the producer; means for performing image analysis to identify the collected agricultural produce; means for comparing data on the identified agricultural produce with inventory data at sales facilities; means for determining an appropriate sales facility based on the inventory data at the sales facility; means for transmitting information about the sales facility to the agricultural machine; means for the agricultural machine to deliver the agricultural produce to the sales facility; means for affixing labels to the agricultural produce during delivery; means for applying a brand design to the agricultural produce; means for delivering the agricultural produce at the sales facility; means for generating sales promotion data related to the delivered agricultural produce; and means for distributing the sales promotion data to an information display device at the sales facility. This automates the entire process of collecting, identifying, delivering, branding, and promoting agricultural produce, significantly reducing the workload of producers and sales facilities and enabling agricultural products to be shipped to market quickly while maintaining their quality.

[1477] "Agricultural machinery" refers generally to any equipment used to automate or mechanize agricultural operations, including specifically collection and delivery equipment such as autonomous transport vehicles.

[1478] "Harvest schedule" refers to information such as the type, quantity, and location of agricultural produce that is scheduled to be harvested on a specific date and time.

[1479] A "collection schedule" refers to the planned operation of agricultural machinery, with optimal routes and times planned based on the harvest schedule.

[1480] "Producers" refers to farmers and agricultural managers who cultivate and harvest crops.

[1481] "Image analysis" refers to the technology of analyzing image data collected using cameras and sensors to identify the type and quality of agricultural products.

[1482] "Inventory data" refers to information such as the types and quantities of agricultural products currently stored at sales facilities.

[1483] "Sales facility" refers to the point or place where agricultural products are sold to consumers, including farm shops and supermarkets.

[1484] A "label" is an information tag attached to agricultural products and is used to display the product's name, characteristics, brand message, etc.

[1485] "Brand design" refers to the designs and marketing messages used to enhance the brand value of specific agricultural products or producers.

[1486] "Promotional data" refers to information intended to promote the sale of agricultural products, and refers to digital content including features and recommended points.

[1487] "Information display device" refers to a device used to provide information to customers, such as a display or signage used in a sales facility.

[1488] The present invention relates to a system for collecting and delivering agricultural produce to sales facilities using autonomous transport vehicles. The system is designed to improve the efficiency of agricultural operations and operates using specific hardware and software.

[1489] Hardware and software used

[1490] Hardware:

[1491] Self-driving transport vehicles (agricultural machinery)

[1492] Smartphone or tablet (for inputting harvest schedule)

[1493] Sensors and cameras (for collecting and identifying produce)

[1494] Image analysis equipment and quality inspection equipment (located inside agricultural machinery)

[1495] software:

[1496] Harvest schedule input application

[1497] Collection Schedule Generation Algorithm

[1498] GPS navigation system

[1499] Image and data analysis software

[1500] Label Creation and Brand Design Software

[1501] Promotional data generation and distribution software

[1502] System Operation

[1503] The system operates in the following steps.

[1504] 1. Input harvest schedule

[1505] The user uses a smartphone or tablet to input harvest schedule data (date and time, type of produce, quantity, etc.) into a harvest schedule input application. This data is automatically sent to the server.

[1506] 2. Generate a pickup schedule

[1507] The server analyzes the collected harvest schedule data and generates an optimal collection schedule. The collection schedule is based on the farmer's location information and calculates the most efficient route. This schedule is then sent to the autonomous transport vehicle.

[1508] 3. Setting up autonomous driving routes

[1509] A terminal is installed inside the autonomous transport vehicle and sets the optimal route based on the schedule information received from the server. The autonomous transport vehicle then begins operating according to the set route.

[1510] 4. Collecting agricultural products

[1511] The terminal controls sensors and cameras inside the autonomous transport vehicle, and collects produce upon arrival at the farm, which is then placed in a collection container inside the truck.

[1512] 5. Produce Identification

[1513] The terminal uses the truck's in-vehicle image analysis system to identify the type and quality of the collected produce, and this identification data is then sent back to the server.

[1514] 6. Decision on sales facilities

[1515] The server matches the identification data with the store's inventory data to determine the appropriate store, and sends the results to the autonomous transport vehicle.

[1516] 7. Label and brand design

[1517] The device generates labels and designs the brand based on themes and messages preset by the user, and the generated labels are automatically affixed to the produce.

[1518] 8. Produce Delivery

[1519] The autonomous vehicle will navigate to the sales facility based on the navigation route set by the device, and upon arrival, it will automatically unload the produce and complete the delivery.

[1520] 9. Providing promotional data

[1521] The server generates promotional data based on the delivery completion data and distributes it to the information display device at the sales facility. This promotional data includes the characteristics and recommended points of the agricultural products.

[1522] Specific examples

[1523] A user enters into their smartphone that they plan to harvest tomatoes on May 1st. This input data is sent to a server, which generates an optimal collection schedule and sends it to an autonomous transport vehicle. The device sets the route to arrive at Farm A at 9:00 a.m. When the transport vehicle arrives at Farm A, it automatically collects the tomatoes and stores them in the truck. The tomato identification data is sent to the server, which checks it against Farm Store B and decides to deliver the tomatoes to Farm Store B, and sends this information to the transport vehicle. On the way to Farm Store B, an "organic fresh" label is affixed to the transport vehicle, and the tomatoes are delivered after arrival. The server displays a promotional message on the digital signage at Farm Store B saying, "Fresh organic tomatoes from Farm A have arrived!"

[1524] The system streamlines and automates the entire process of agricultural produce, from collection to distribution, identification, branding and promotion.

[1525] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1526] Program processing steps

[1527] Step 1: Enter your harvest plan

[1528] A user uses a smartphone or tablet to input data about planned harvesting (date and time, type of produce, quantity, etc.) into a harvest plan input application.

[1529] Input: Data such as planned harvest date and time, type of produce, and quantity.

[1530] Output: Harvest forecast data is sent to the server.

[1531] How it works: A user opens the application, enters their harvest schedule, and presses the "Submit" button.

[1532] Step 2: Generate a collection schedule

[1533] The server analyzes the collected harvest schedule data and generates an optimal harvest schedule.

[1534] Input: Harvest schedule data, location information of each producer.

[1535] Data processing: Harvest forecast data is analyzed and combined with each producer's location information.

[1536] Output: A collection schedule is generated and sent to the autonomous transport vehicle.

[1537] How it works: Using harvest schedule data collected by the server, it calculates the optimal visit sequence and sets an efficient route.

[1538] Step 3: Set up your self-driving route

[1539] The terminal is installed inside the autonomous transport vehicle and sets the optimal route based on the schedule information received from the server.

[1540] Input: Collection schedule sent from the server.

[1541] Data calculation: Based on the received schedule data, the navigation system calculates the optimal route.

[1542] Output: The automated driving route is set.

[1543] Operation: The device inputs schedule data into the navigation system and sets up an automated driving route.

[1544] Step 4: Collect produce

[1545] The terminal controls sensors and cameras inside the autonomous transport vehicle and collects agricultural products when it arrives at the farm.

[1546] Input: Farmer location information, crop location data from sensors and cameras.

[1547] Data processing: Analyze data from sensors and cameras to identify the location for collecting produce.

[1548] Output: The collected produce is stored in a collection container inside the truck.

[1549] How it works: The transport vehicle arrives at the farm and the collector activates to collect the produce.

[1550] Step 5: Identify the produce

[1551] The terminal uses an image analysis system inside the truck to identify the type and quality of the produce collected.

[1552] Input: Collected image data of agricultural products.

[1553] Data analysis: Image analysis systems identify the type and quality of agricultural products.

[1554] Output: The identified produce data is sent to the server.

[1555] How it works: The device takes images of the collected produce, and the image analysis system analyzes the data.

[1556] Step 6: Determine your sales facility

[1557] The server matches the identification data with the sales establishment's inventory data to determine the appropriate sales establishment.

[1558] Input: Identified produce data, sales facility inventory data.

[1559] Data calculation: Matching identification data with inventory data to determine the best sales facility.

[1560] Output: The appropriate sales facility is determined and the information is sent to the autonomous transport vehicle.

[1561] How it works: The server scans all inventory data it has access to and determines which sales facility to deliver the produce to.

[1562] Step 7: Label and brand design

[1563] The device generates labels and designs the brand based on themes and messages preset by the user.

[1564] Input: User-defined themes, messages, and identification data.

[1565] Data Processing: Generate label and brand designs based on user settings and identification data.

[1566] Output: The generated label is attached to the produce.

[1567] How it works: The device designs labels based on a theme and automatically applies them to produce.

[1568] Step 8: Deliver your produce

[1569] An autonomous transport vehicle will operate to the sales facility based on the navigation route set on the terminal.

[1570] Input: Sales facility information, navigation route.

[1571] Data calculation: The navigation system recalculates the route and heads towards the destination.

[1572] Output: The autonomous transport vehicle arrives at the sales facility and delivers the produce.

[1573] How it works: The transport vehicle follows a designated route to the sales facility and automatically unloads the produce upon arrival.

[1574] Step 9: Provide promotional data

[1575] The server generates sales promotion data based on the delivery completion data and distributes it to the information display device of the sales facility.

[1576] Input: Delivery completion data, agricultural product characteristics information.

[1577] Data processing: Generate promotional data based on delivery completion data and agricultural product characteristics information.

[1578] Output: The generated sales promotion data is delivered to an information display device in the sales facility.

[1579] Operation: The server analyzes the data after delivery is completed, generates promotional messages, and distributes them to digital signage.

[1580] (Application example 1)

[1581] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1582] Current agricultural produce collection and delivery systems face many challenges in terms of efficiency and accuracy. In particular, farmers must manage their harvest schedules individually, making it difficult for collection vehicles to set efficient routes for each farm. Quality control of collected produce also relies heavily on manual labor, making it difficult to accurately grasp quality data and deliver it to the appropriate sales facility. Furthermore, the creation and display of sales promotion data is also done manually, resulting in a lack of real-time response. To solve these problems, a system is needed that automates the entire process, from inputting harvest schedules to sales promotion at sales facilities.

[1583] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1584] In this invention, the server includes means for inputting planned harvesting of agricultural products, means for generating a collection schedule based on the planned harvesting, means for directing an autonomous transport vehicle to each farm based on the generated schedule, means for collecting the agricultural products when the autonomous transport vehicle arrives at the farm, means for performing image analysis to identify the collected agricultural products, means for comparing data on the identified agricultural products with inventory data at the sales facility, means for determining an appropriate sales facility based on the inventory data at the sales facility, means for transmitting information about the sales facility to the autonomous transport vehicle, means for the autonomous transport vehicle to deliver the agricultural products to the sales facility, means for affixing labels to the agricultural products during delivery, means for applying brand designs to the agricultural products, means for delivering the agricultural products at the sales facility, means for generating promotional data regarding the delivered agricultural products, means for distributing the promotional data to an information display device at the sales facility, means for inputting the harvest schedule using a smart device, means for transmitting quality data to the server, and means for generating a prompt message for the information display device. This enables the entire process of harvesting, collecting, identifying, delivering, labeling, and generating delivery and promotional data for agricultural products to be carried out efficiently and accurately.

[1585] The "means for inputting planned harvesting of agricultural produce" is a device that provides an interface that allows farmers to input the planned harvest date, type, and quantity using a smart device.

[1586] The "means for generating a collection schedule based on the harvest schedule" is a device that collects data on the harvest schedule and automatically generates an optimal collection schedule based on the location information of each farmer.

[1587] The "means for directing autonomous transport vehicles to each farm based on the generated schedule" is a device that receives schedule information from the server and instructs the autonomous transport vehicles to move according to that information.

[1588] "Means for collecting agricultural produce when an autonomous transport vehicle arrives at a farm" refers to a device that uses sensors and cameras installed inside the transport vehicle to recognize and automatically collect agricultural produce.

[1589] "Means for performing image analysis to identify collected produce" means a device that uses an image analysis system located within the truck to identify the type and quality of collected produce.

[1590] The "means for checking data on identified agricultural products against inventory data at the sales facility" is a device that transmits data on identified agricultural products to a server and checks the data against inventory data at the sales facility in real time.

[1591] The "means for determining an appropriate sales facility based on inventory data of the sales facility" is a device in which the server analyzes inventory data and automatically determines to which sales facility each agricultural product should be delivered.

[1592] The "means for transmitting information about the sales facility to the autonomously driven transport vehicle" is a device that transmits information about the determined sales facility to the autonomously driven transport vehicle and instructs the transport vehicle to move based on that information.

[1593] "Means for an autonomous transport vehicle to deliver agricultural produce to a sales facility" refers to a device for an autonomous transport vehicle to deliver agricultural produce to a sales facility according to a determined route.

[1594] The "means for labeling produce during delivery" refers to a device that automatically generates and applies labels to collected produce.

[1595] The "means for applying brand design to agricultural products" is a device that automatically applies brand design to labels based on a theme or message set by the user.

[1596] The "means for delivering agricultural produce at the sales facility" is a device that allows an autonomous transport vehicle to arrive at the sales facility and automatically unload and deliver the agricultural produce.

[1597] The "means for generating sales promotion data relating to delivered agricultural products" is a device that automatically generates sales promotion data including the characteristics and recommended points of the agricultural products delivered at the sales facility on a server.

[1598] The "means for distributing promotional data to an information display device in a sales facility" is a device that distributes the generated promotional data to an information display device such as digital signage in a sales facility.

[1599] "Means for inputting harvest plans using a smart device" refers to an interface for inputting harvest plans using a device such as a smartphone or tablet.

[1600] The "means for transmitting quality data to the server" is a device that transmits quality data of agricultural products identified by the image analysis system to the server in real time.

[1601] The "means for generating a prompt sentence on the information display device" is a device that automatically generates a prompt sentence based on sales promotion data and displays it on the information display device.

[1602] The present invention is a system for collecting agricultural produce and delivering it to a sales facility using an autonomous transport vehicle. This system automates a series of operations using specific means, from the user inputting the harvest schedule to the generation and display of sales promotion data at the sales facility. Specific embodiments are described below.

[1603] First, the user (farmer) uses a smart device (e.g., smartphone or tablet) to input the planned harvesting of agricultural produce. The input data is sent to the server. Based on this harvest plan data, the server generates an optimal collection schedule that reflects the location information of each farmer. The generated schedule is then sent to the autonomous transport vehicle.

[1604] Next, a terminal installed in the autonomous transport vehicle sets the optimal route based on the schedule information received from the server. This allows the autonomous transport vehicle to visit farms efficiently. When the transport vehicle arrives at the farm, the terminal uses sensors and cameras to recognize the produce and automatically collects it. The collected produce is stored in a collection container inside the truck.

[1605] The image analysis system inside the truck then identifies the type and quality of the collected produce, and the identified data is sent to a server. The server compares the identified produce data with the inventory data of the sales facility and determines which sales facility each produce should be delivered to. This delivery information is sent to the terminal of the autonomous transport vehicle.

[1606] Additionally, the terminals handle labeling and branding while the produce is being delivered. Labels are automatically generated and applied to the produce based on a theme or message predefined by the user. When the truck arrives at the sales facility, the produce is automatically unloaded and delivered.

[1607] Once delivery is complete, the server generates promotional data for the delivered produce, including the produce's features and recommended points. The generated promotional data is distributed to information display devices (such as digital signage) at the sales facility, providing consumers with real-time visual information.

[1608] As an example, the following process is performed:

[1609] 1. User Input:

[1610] A user enters "Harvest 200 kg of tomatoes on May 1st" into a smartphone app.

[1611] 2. Server processing:

[1612] Based on the harvest schedule data received by the server, the optimal collection route is generated and sent to the autonomous transport vehicle.

[1613] 3. Collection by vehicle:

[1614] The autonomous transport vehicle arrives at the farm at the designated time and collects the tomatoes. At the time of collection, an image analysis system acquires the quality data of the tomatoes and sends it to a server.

[1615] 4.Delivery destination determination:

[1616] The server determines the best sales facility based on the quality data and transmits this information to the autonomous transport vehicle.

[1617] 5. Label and brand design:

[1618] Labels are generated on board the truck and attached to the tomatoes, with designs based on the theme "organic fresh."

[1619] 6. Delivery and promotional data generation:

[1620] A truck arrives at the sales facility to deliver the tomatoes. A promotional message is generated and displayed on the digital signage: "Fresh farm-fresh organic tomatoes in stock!"

[1621] An example of a prompt sentence would be, "Enter data as a farmer who plans to harvest tomatoes on May 1st. The route is set so that an autonomous vehicle will visit at 9:00, and the collected data on the quality of the agricultural products will be sent to the server in real time. Delivery destination determination and label generation are also automated."

[1622] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1623] Step 1:

[1624] Users use a smartphone or tablet to input their planned harvesting schedule. Specifically, they input data through an interface that allows them to input the planned harvest date, type, and quantity. This input data is then sent to the server. The input data includes the user ID, type of produce, planned harvest date, and harvest quantity.

[1625] Step 2:

[1626] Based on the harvest schedule data it receives, the server generates an optimal collection schedule that reflects the location information of each farmer. The server combines GPS data and harvest schedule data to calculate the most efficient route. The generated schedule is sent to the autonomous transport vehicle's terminal. The input data is the harvest schedule data and GPS data, and the output is the optimal collection schedule.

[1627] Step 3:

[1628] The terminal sets the optimal route for the autonomous transport vehicle based on the schedule information received from the server. The terminal analyzes the route information and gives instructions to the autonomous transport vehicle. Specifically, it calculates the order of farms to visit and the shortest route, and reflects this in the autonomous transport vehicle. The input data is the collection schedule, and the output is route setting information.

[1629] Step 4:

[1630] An autonomous transport vehicle visits farms according to a designated route. When the transport vehicle arrives at a farm, a terminal uses sensors and cameras to recognize the produce and automatically collects it. The collected produce is stored in a collection container inside the truck. The data collected by the sensors and cameras is used to confirm whether the produce has been collected correctly. The input data is route setting information, and the output is information about the collected produce.

[1631] Step 5:

[1632] The collected produce is identified by an image analysis system inside the truck. The terminal sends the data obtained from the image analysis system to a server. The image analysis system identifies the type and quality of the collected produce and sends the data to the server. The input data is image data of the collected produce, and the output is data on the identified produce.

[1633] Step 6:

[1634] The server compares the identified produce data with the sales facility inventory data and determines which sales facility each produce should be delivered to. The server analyzes the inventory data and produce data and selects the most suitable sales facility. This information is sent to the autonomous transport vehicle's terminal. The input data is the identified produce data and inventory data, and the output is information about the sales facility to which the produce should be delivered.

[1635] Step 7:

[1636] The server sends information about the sales facility to the autonomous vehicle. Based on this information, the terminal issues instructions for the autonomous vehicle to head to the designated sales facility. The input data is the sales facility information, and the output is delivery instructions.

[1637] Step 8:

[1638] During delivery, the terminal automatically generates and affixes labels to the produce. The labels are generated using themes and messages preset by the user. The brand design is also applied to the produce. The input data is the user's label settings information, and the output is the affixed label and brand design.

[1639] Step 9:

[1640] When the autonomous transport vehicle arrives at the sales facility, the terminal automatically unloads and delivers the produce. Once delivery is complete, the terminal sends delivery completion data to the server. The input data is delivery instructions, and the output is delivery completion data.

[1641] Step 10:

[1642] The server generates promotional data based on the delivery completion data. The generated promotional data includes the characteristics and recommended points of the agricultural products. This automatically generates the promotional data to be displayed on the information display device of the sales facility. The input data is the delivery completion data, and the output is the promotional data.

[1643] Step 11:

[1644] The server distributes the generated sales promotion data to the information display device in the sales facility, allowing consumers to check the characteristics and recommended points of agricultural products in real time. The input data is the sales promotion data, and the output is the distribution data to the information display device.

[1645] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1646] The present invention combines a system that uses autonomous transport vehicles to collect agricultural produce and deliver it to sales facilities with an emotion engine that recognizes user emotions, allowing the system to optimize its operation based on the user's emotions and provide more personalized services.

[1647] 1. Input harvest schedule

[1648] User: Enters planned harvesting of produce. As the user uses a smartphone or tablet to input the planned harvest date, type of produce, and quantity, the emotion engine recognizes the user's emotions and optimizes the system's settings and information provision based on the input.

[1649] 2. Generate a pickup schedule

[1650] Server: Receives harvest schedule data and aggregates harvest schedule information from all farmers. Based on the emotion engine, generates an optimal collection schedule that reflects the user's emotions. For example, if a user is feeling anxious about harvesting, the system provides a function to flexibly adjust the schedule.

[1651] 3. Setting up autonomous driving routes

[1652] Terminal: The terminal installed in the autonomous transport vehicle sets the optimal route based on the schedule information received from the server. At this time, the emotion engine prioritizes routes that reduce stress as much as possible based on the user's emotions.

[1653] 4. Collecting agricultural products

[1654] Terminal: When the autonomous transport vehicle arrives at the farm, the terminal uses sensors and cameras to recognize the produce and automatically collect it. The emotion engine is sensitive to the user's emotions, and if the user is in a hurry, for example, the terminal will collect the produce quickly.

[1655] 5. Produce Identification

[1656] Terminal: An image analysis system inside the truck identifies the type and quality of the produce collected. This information is sent to a server.

[1657] 6. Decision on sales facilities

[1658] Server: Using the identified product data, it compares it with the inventory data of each sales facility and decides which sales facility to deliver each product to. The emotion engine optimizes the selection of sales facility to improve user satisfaction.

[1659] 7. Label and brand design

[1660] Terminal: Labeling and branding is done inside the truck. Based on themes and emotions predefined by the user, an emotion engine generates personalized labels and branding to be applied to produce.

[1661] 8. Produce Delivery

[1662] Terminal: The autonomous transport vehicle will make the delivery to the selected sales facility. When the truck arrives at the sales facility, it will automatically unload and deliver the produce.

[1663] 9. Providing promotional data

[1664] Server: When agricultural products are delivered to a sales facility, the server generates promotional data based on the emotion engine. This data includes the characteristics and recommended points of the agricultural products, and is distributed to information display devices (such as digital signage) at the sales facility.

[1665] Specific examples

[1666] User: Farmer A enters his / her tomato harvesting plans for May 1st into the application. The emotion engine analyzes the user's facial expressions and tone of voice when entering data and recognizes that he / she is feeling anxious. Based on this, the system flexibly adjusts the harvesting schedule.

[1667] Server: Receives harvest schedule data, generates the optimal collection route, and sends it to the autonomous transport vehicle.

[1668] Terminal: The autonomous transport vehicle sets a route to arrive at Farm A at 9:00 a.m. and departs. When the truck arrives at Farm A, it quickly collects the tomatoes and stores them inside the truck. Based on the emotion engine, collection is fast and efficient.

[1669] Terminal: The image analysis system identifies the tomato and sends the data to the server.

[1670] Server: Checks the inventory information of the sales facility and decides to deliver the tomatoes to Direct Sales Store B. This information is sent to the truck.

[1671] Device: Label and brand design, labeling tomatoes based on the theme "organic fresh," incorporating design elements that respond to user emotions.

[1672] Terminal: Departs for the farm shop B and delivers the tomatoes after arriving. The delivery process is optimized based on the emotion engine.

[1673] Server: The server generates a promotional message saying, "Fresh organic tomatoes from Farm A have arrived!" and displays it on the digital signage at Farm B's farm store.

[1674] The integrated system provides a personalized service that is sensitive to the user's emotions, automating the collection, identification, delivery, labeling, branding, and promotion of agricultural products.

[1675] The processing flow will be explained below.

[1676] Step 1:

[1677] User: Entering planned harvesting of produce. Using a smartphone or tablet, the user enters the planned harvest date, type of produce, and quantity into the application. The emotion engine analyzes the user's facial expressions and voice tone to assess their emotional state.

[1678] Step 2:

[1679] Server: Receives harvest schedule data and emotion data. The server saves the input harvest schedule data, analyzes the user's emotion data, and aggregates the harvest schedule information of all farmers.

[1680] Step 3:

[1681] Server: Generates a collection schedule. The server calculates the optimal collection route based on each farmer's location information and the expected harvest date, and creates a schedule. If the user's emotions are unstable, it provides a flexible schedule. This schedule information is sent to the autonomous transport vehicle.

[1682] Step 4:

[1683] Terminal: Sets the autonomous driving route. The terminal installed in the autonomous transport vehicle sets the autonomous driving route based on the schedule information received from the server. The emotion engine prioritizes routes that reduce stress based on the user's emotions.

[1684] Step 5:

[1685] Terminal: Start automatic driving. The automatic transport vehicle departs according to the set route and heads towards the farm.

[1686] Step 6:

[1687] Terminal: After arriving at the farm, the farmer collects the produce. The terminal uses sensors and cameras to recognize the produce and automatically collects it. If the user is in a hurry, the emotion engine speeds up the collection process.

[1688] Step 7:

[1689] Terminal: Identifies agricultural products. The image analysis system inside the truck identifies the type and quality of the collected agricultural products and sends the data to a server.

[1690] Step 8:

[1691] Server: Cross-checks inventory data. The server collects real-time inventory data from each sales facility and cross-checks it with the identified produce.

[1692] Step 9:

[1693] Server: Determines the appropriate sales facility. The server determines the optimal sales facility based on inventory data and agricultural product data. The emotion engine optimizes the delivery destination selection based on the user's emotions. This information is sent to the terminal of the autonomous transport vehicle.

[1694] Step 10:

[1695] Terminal: The truck generates the label and brand design. Based on the theme and message set by the user in the truck, AI generates the label and attaches it to the produce. The emotion engine optimizes the design according to the user's emotions.

[1696] Step 11:

[1697] Terminal: Start delivery to the sales facility. The autonomous transport vehicle departs for the designated sales facility.

[1698] Step 12:

[1699] Terminal: Arrives at the sales facility and delivers the produce. When the truck arrives at the sales facility, it automatically unloads the produce and completes the delivery process.

[1700] Step 13:

[1701] Server: Generates sales promotion data. The server generates sales promotion data about delivered agricultural products and distributes it to the information display device of the sales facility. Based on the emotion engine, it creates promotional messages that match the user's emotions.

[1702] Step 14:

[1703] Server: Display promotional messages. Promotional messages that take into account emotions, such as "Fresh produce in stock!", are displayed on the information display devices of sales facilities.

[1704] This process provides a personalized and responsive service to users, automating the collection, identification, delivery, labeling, branding, and promotion of produce.

[1705] Example 2

[1706] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1707] In a system that uses autonomous transport vehicles to collect and deliver agricultural produce to sales facilities, conventional technology sets uniform schedules and routes without considering the user's feelings, which leads to problems of low user satisfaction and efficiency.In addition, the process from collecting agricultural produce to delivery and sales promotion is not effectively automated, resulting in wasted effort and time.

[1708] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1709] In this invention, the server includes means for analyzing a user's emotions using an emotion engine and inputting a harvest schedule for agricultural produce, means for generating a collection schedule according to the harvest schedule based on the emotion engine, and means for transmitting the generated schedule information to a terminal of the autonomous transport vehicle and setting a route, thereby enabling efficient and personalized collection, delivery, and sales of agricultural produce that takes into consideration the user's emotions.

[1710] An "emotion engine" is software or hardware for analyzing a user's emotions and generating emotion data from facial expressions and voice.

[1711] "Harvest schedule" is data including information such as the harvest date, type, and quantity of agricultural produce, and is entered into the system by the user.

[1712] The "collection schedule" is a plan that determines the order and timing of visits by autonomous transport vehicles based on the harvest schedule.

[1713] An "autonomous delivery vehicle" is a vehicle that has the ability to drive autonomously and collect and deliver agricultural produce.

[1714] A "sensor" is a device that detects environmental information or the state of an object, and is used when collecting agricultural products.

[1715] "Camera" means a device that captures images and is used to identify agricultural products and inspect their quality.

[1716] "Image analysis" is a technology that identifies the type and quality of agricultural products from photographed images.

[1717] "Inventory data" refers to data that indicates the current inventory status of agricultural products at a sales facility.

[1718] A "label" is an information sheet that is affixed to agricultural products and includes the product name and producer information.

[1719] "Brand design" refers to the design applied to the packaging and labels of agricultural products, and is used to increase purchasing desire.

[1720] "Sales promotion data" refers to data generated for sales promotion purposes, and includes product features and recommended points.

[1721] An "information display device" is a digital signage or display device installed in a sales facility for displaying sales promotion data.

[1722] This invention is a system that uses autonomous transport vehicles to collect agricultural products and deliver them to sales facilities, and by combining it with an emotion engine, provides optimal services that meet the individual needs of users. This invention is composed of users, a server, and terminals.

[1723] First, the user uses a smartphone or tablet to input their planned harvesting schedule (date, type, and quantity). The system is equipped with an emotion engine that analyzes emotional data from the user's facial expressions and voice, and optimizes system settings and information provision based on this. Specifically, if the user is feeling anxious, the emotion engine detects this and flexibly adjusts the harvesting schedule to reduce the user's stress.

[1724] The server aggregates harvest schedule data received from users and analyzes the harvest schedule information of all farmers. Based on the emotion engine, it generates an optimal collection schedule and sends it to the autonomous transport vehicle's terminal. This schedule includes an efficient and user-friendly visit sequence and timing.

[1725] Next, the autonomous vehicle's terminal receives the schedule information and uses the navigation system to set the optimal route. This route is selected with consideration for the user's emotions, with priority given to routes that cause as little stress as possible. The vehicle then travels along the set route and arrives at each farm.

[1726] When the transport vehicle arrives at the farm, the terminal's sensors and cameras scan the produce and take appropriate collection action. The collected produce is identified by an image analysis system for type and quality, and this data is sent to a server. The server compares this data with inventory information from sales facilities and determines the appropriate sales facility.

[1727] Once a sales facility is determined, that information is sent to the autonomous vehicle, which reroutes it. During delivery, labeling and branding are performed, and personalized labels are applied to the produce. Design elements are incorporated based on the user's emotions and themes.

[1728] Finally, when the autonomous vehicle arrives at the sales facility, it automatically unloads the produce and delivers it to the facility. After delivery, the server generates promotional data based on the emotion engine and distributes it to information display devices such as digital signage at the sales facility. This allows for effective promotion of the produce at the sales facility.

[1729] Examples:

[1730] The user, a farmer, opens the app on their smartphone and inputs their harvest schedule. For example, they might input "I plan to harvest tomatoes on May 1st." The emotion engine analyzes the user's facial expressions and voice when they input their data, and if the user seems anxious, the server will flexibly adjust the harvest schedule.

[1731] An example of a prompt using a generative AI model could be, "Describe a new produce collection system. Include a process where an emotion engine analyzes user emotions, and autonomous vehicles collect and deliver produce to sales facilities."

[1732] This system enables efficient and personalized collection, delivery, and sales of agricultural products that take into consideration the user's feelings.

[1733] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1734] Step 1:

[1735] User: Uses a smartphone or tablet to input planned harvest information (date, type, and quantity).

[1736] Input: The user enters details of the planned harvest into the application.

[1737] Data processing: The emotion engine uses the camera and microphone to analyze the user's facial expressions and voice in real time and generate emotion data.

[1738] Output: Harvest schedule data and emotion data are sent to the server.

[1739] How it works: A user opens the application and fills in a form with details of their harvest. The emotion engine analyzes facial expressions and tone of voice in real time to obtain emotional data. Finally, this data is sent to the server.

[1740] Step 2:

[1741] Server: Aggregates harvest schedule data and emotion data, and analyzes the harvest schedule information of all farmers.

[1742] Input: Harvest schedule data and emotion data.

[1743] Data processing: Based on the emotion engine, the optimal pickup schedule is generated taking into account the user's emotions.

[1744] Output: The generated collection schedule is sent to the autonomous transport vehicle terminal.

[1745] Specific operation: The server receives harvest plan data and emotion data sent from each farmer, and uses an algorithm to determine a collection schedule that takes into account efficiency and user emotions, and sends it to the transport vehicle.

[1746] Step 3:

[1747] Terminal: The terminal inside the autonomous transport vehicle receives the schedule information and uses the navigation system to plan the optimal route.

[1748] Input:Pickup Schedule.

[1749] Data processing: The navigation system calculates the optimal route taking into account the data from the emotion engine.

[1750] Output: The transport vehicle starts moving based on the set route.

[1751] Specific operation: The terminal receives the collection schedule, calculates the optimal route with the least stress, and moves the autonomous delivery vehicle.

[1752] Step 4:

[1753] Terminal: When the self-dri...

Claims

1. 1. A method for collecting agricultural produce and delivering the produce to a sales facility using an autonomous transport vehicle, comprising: a means for inputting a harvest schedule for agricultural produce; means for generating a collection schedule based on the harvest schedule; A means for directing an autonomous transport vehicle to each farm based on the generated schedule; A means for the autonomous transport vehicle to collect produce when it arrives at the farm; and means for performing image analysis to identify the collected produce; means for matching the identified produce data with inventory data at the sales facility; means for determining an appropriate sales facility based on sales facility inventory data; means for transmitting information about the sales facility to the autonomous transport vehicle; a means for autonomous transport vehicles to deliver produce to sales facilities; a means of labeling the produce during delivery; A means of applying brand design to agricultural products; a means of delivering agricultural produce at a sales facility; means for generating promotional data relating to the delivered produce; A system including means for delivering promotional data to an information display device at a sales establishment.

2. When collecting agricultural produce using an autonomous transport vehicle, The system of claim 1 further comprising means for generating an optimal route based on the location information of the farmer.

3. To identify and inspect agricultural products for quality.

10. The system of claim 1, further comprising an image analysis device and a quality inspection device located within the autonomous transport vehicle.

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