System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting user data including purchase history, health status, and preferences; means for generating a product list based on the collected user data; means for loading products onto a mobile sales vehicle based on the generated product list; means for optimizing a delivery route of the mobile sales vehicle based on the user data and traffic information; means for accepting an on-demand request from a user or a care manager; means for delivering products to a user's home or a set location based on the product list and the on-demand request; and means for providing the products to the user at a stop point and holding an interaction event on the spot.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] With the increasing number of elderly people, providing support for the daily lives of those living alone has become an important issue. For elderly people who have difficulty going out, obtaining daily necessities and medical products is a major burden, and social isolation is also a serious problem. Conventional mobile sales and delivery services cannot adequately address many of these issues, so new approaches are needed to improve the quality of life of the elderly. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by utilizing AI to provide a personalized mobile sales service specifically for the elderly. First, a means for collecting user data, including purchase history, health status, and preferences, is provided. Next, a means for generating a product list using an AI algorithm based on the collected user data is provided. A means for loading products onto a mobile sales vehicle based on the generated product list is provided. Furthermore, a means for optimizing the delivery route of the mobile sales vehicle in real time based on user data and traffic information is provided. A means for accepting on-demand requests from users or care managers and delivering products to the user's home or a designated location based on the product list and on-demand request is also provided. By building a system that includes a means for the mobile sales vehicle to provide products to users at stops and hold on-site social events, it is possible to meet individual needs, prevent social isolation among the elderly, and improve their quality of life.

[0006] "Purchase history" is a record of information about products and services purchased by a user in the past.

[0007] "Health Status" refers to information about a user's physical health, such as medical history, illnesses, current health status, etc.

[0008] "Preferences" refers to information based on the user's tastes and preferences, such as dietary preferences, allergies, and preferences for specific products.

[0009] "User Data" collectively refers to various information about a user, including purchasing history, health status, and preferences.

[0010] An "AI algorithm" is a computational method that uses artificial intelligence technology to analyze large amounts of data and find patterns.

[0011] A "product list" is a list of recommended or required products generated based on a user's needs and preferences.

[0012] A "mobile sales vehicle" is a vehicle that is loaded with merchandise and travels to a user's residence or a set location to provide the merchandise.

[0013] "Traffic information" refers to information on road conditions, traffic congestion, etc. that is collected in real time.

[0014] "Delivery route" refers to the route that a mobile sales vehicle takes to deliver goods.

[0015] An "on-demand request" is a request sent by a user or care manager via an app or other means when they need a specific product or service.

[0016] A "stop" is a location where a mobile food truck temporarily stops to offer its products.

[0017] "Exchange events" are social activities such as roundtable discussions and mini-games that are held to promote interaction among seniors. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] This invention utilizes AI to provide a personalized mobile sales service specifically for the elderly. Hereinafter, an embodiment of the invention will be described in detail.

[0040] 1. Collection of User Data

[0041] server

[0042] The server collects data about the user's purchasing history, health status, and preferences, including information the user enters through the app, past shopping history, and results of regular checkups. Using a device, the user enters their health information and preferences into the application, which is then sent to the server.

[0043] Specific examples

[0044] User A enters his / her high blood pressure information and low-salt food purchase history into the app. The device sends the information to the server, which stores it in a database.

[0045] 2. Analyze data and generate product list

[0046] server

[0047] Based on the collected user data, the server uses an AI algorithm to generate a personalized product list for each user, including medicines tailored to their health condition, foods tailored to their preferences, etc. The generated product list is stored in a database for each user.

[0048] Specific examples

[0049] Based on User A's high blood pressure information, the server adds low-salt foods and blood pressure monitors to the recommended product list.

[0050] 3. Calculating delivery routes and notifying mobile sales vehicles

[0051] server

[0052] The server calculates the optimal delivery route based on the user's location data and real-time traffic information, and sends this optimal route information to the mobile sales vehicle's terminal.

[0053] Specific examples

[0054] Based on the traffic information collected by the server, the most efficient route from the area where user A lives to the address of user B is calculated and sent to the navigation system of the mobile sales vehicle.

[0055] 4. Acceptance of On-Demand Delivery Requests

[0056] User

[0057] Users or care managers can submit on-demand requests for products through the app.

[0058] Terminal

[0059] The terminal sends these requests to the server.

[0060] server

[0061] The server accepts the request and adds it to the current delivery route.

[0062] Specific examples

[0063] User B suddenly needs a blood glucose test kit and sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[0064] 5. Supply and delivery of goods

[0065] Mobile sales vehicle

[0066] The mobile sales vehicle follows the optimal route received from the server and visits elderly people's homes and designated locations, providing products requested by users and recommended products.

[0067] Specific examples

[0068] The mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to the next destination, the home of user B, and delivers a blood glucose testing kit.

[0069] 6. Providing a platform for social interaction

[0070] Mobile sales vehicle

[0071] The mobile sales vans will serve as a place for seniors to interact with each other while delivering products, and will hold events such as mini-games and roundtable discussions at each stop to prevent social isolation.

[0072] Specific examples

[0073] Mobile sales trucks visit nursing homes and promote interaction between the elderly by holding mini-games and health seminars while delivering products.

[0074] summary

[0075] This invention utilizes AI to provide personalized services tailored to the needs of the elderly and provides a system that plans efficient delivery routes, allowing them to easily obtain daily necessities and medical products while providing opportunities for social interaction and improving their quality of life.

[0076] The processing flow will be explained below.

[0077] Step 1:

[0078] Through the application, users input data about their purchasing history, health status, and preferences. For example, a user may input information about their high blood pressure or a preference for low-salt foods.

[0079] Step 2:

[0080] The terminal receives the data entered by the user and transmits it to the server.

[0081] Step 3:

[0082] The server stores the received user data in a database, organizing information such as purchase history, health status, and preferences, and storing it in a specific format.

[0083] Step 4:

[0084] The server uses AI algorithms to analyze the stored user data and generate a personalized product list for each user, for example, recommending low-salt foods to a user with high blood pressure.

[0085] Step 5:

[0086] The server stores the generated product list in a database and transmits it to the mobile sales vehicle.

[0087] Step 6:

[0088] The server collects user location data and real-time traffic information, and uses this data to calculate the optimal delivery route using an AI algorithm.

[0089] Step 7:

[0090] The server then sends the calculated optimal route to the mobile sales vehicle's terminal, which receives this information and sets the route according to the instructions.

[0091] Step 8:

[0092] A user or care manager can send an on-demand request through the application. For example, if User B urgently needs a blood glucose test kit, he or she can send this information as a request.

[0093] Step 9:

[0094] The terminal sends an on-demand request to the server.

[0095] Step 10:

[0096] The server receives on-demand requests and recalculates and updates the current delivery route.

[0097] Step 11:

[0098] The server then sends the recalculated route information to the mobile sales vehicle's terminal, which receives the information and moves along the new route.

[0099] Step 12:

[0100] The mobile sales vehicle follows the optimal route received from the server, visits elderly people's homes and other designated locations, and delivers the products loaded on it based on the user's personalized product list.

[0101] Step 13:

[0102] The mobile food truck arrives at its destination, offers products to users, and hosts social events at each stop, such as health seminars or mini-games.

[0103] Step 14:

[0104] Users receive the products and, if necessary, participate in events to interact with other elderly people.

[0105] Example 1

[0106] 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."

[0107] Elderly people face challenges in easily obtaining daily necessities and medicines, and are prone to feeling socially isolated. Current mobile sales services often lack the ability to provide products tailored to the user's health condition and preferences, and delivery routes are often not optimized for efficiency. Furthermore, they lack a system capable of responding to on-demand requests, making it difficult to respond to sudden demand. To address these issues, it is necessary to provide personalized products specifically for the elderly, establish efficient delivery routes, and promote social interaction.

[0108] 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.

[0109] In this invention, the server includes means for collecting user data including purchase history, health status, and preferences, means for generating a product list based on the collected user data, means for loading products onto a mobile food truck based on the generated product list, means for optimizing a delivery route for the mobile food truck based on the user data and traffic information, means for receiving an on-demand request from a user or a care manager, means for delivering products to the user's home or a set location based on the product list and the on-demand request, means for the mobile food truck to provide products to the user at a stop and hold a social event on the spot, means for the mobile food truck to add on-demand delivery based on the user's request, means for generating a personalized product list using an AI algorithm, and means for calculating a delivery route based on real-time traffic information. This not only enables elderly people to easily obtain the products they need, but also enables the establishment of efficient delivery routes and promotion of social interactions.

[0110] "Purchase history" is data that records details of products and services purchased by a user in the past.

[0111] "Health Status" refers to information about a user's physical and mental health, including data based on medical records and self-reporting.

[0112] "Preferences" are data that indicate a user's tendency to prefer certain types of products or services.

[0113] "User Data" refers to information including purchasing history, health status, and preferences.

[0114] A "product list" is a list of recommended products and services generated for each user based on collected user data.

[0115] A "mobile sales vehicle" is a vehicle that operates to provide products and services to users.

[0116] "Delivery route" refers to the route taken by a mobile sales vehicle to deliver goods.

[0117] An "on-demand request" is a request made by a user or care manager for an urgently needed product or service.

[0118] An "AI algorithm" is a program that uses machine learning and artificial intelligence technology to analyze data and make predictions.

[0119] "Real-time traffic information" refers to data that provides real-time information on current traffic conditions and road congestion.

[0120] "Social networking events" refer to activities such as mini-games, roundtable discussions, and seminars that are planned to encourage social interaction among seniors.

[0121] This invention is a system that utilizes AI to provide a personalized mobile sales service specifically for the elderly. Specific embodiments for carrying out this invention will be described below.

[0122] First, the server collects user data, including purchase history, health status, and preferences. This includes information entered by the user through a dedicated application, past purchase history, and the results of regular checkups. The devices used are devices such as smartphones and tablets, and the data entered through these devices is sent to the server.

[0123] For example, user A enters his or her high blood pressure information and low-salt food purchase history into the app. The device then sends the information to the server, which then stores it in a database.

[0124] Next, the server uses an AI algorithm based on the collected user data to generate a personalized product list for each user. The AI ​​algorithm typically uses machine learning models such as TensorFlow or PyTorch. The generated product list is stored in a database for each user.

[0125] For example, the server adds low-salt foods and blood pressure monitors to the recommended product list based on User A's high blood pressure information. An AI algorithm then operates to generate the optimal product list.

[0126] The server then calculates the optimal delivery route based on the user's location data and real-time traffic information. This process uses map data and traffic information APIs such as Google Maps API. The calculation results are sent to the navigation system of the mobile sales vehicle.

[0127] As a specific example, based on traffic information collected by the server, the most efficient route from the area where user A lives to the address of user B is calculated and sent to the navigation system of the mobile sales vehicle.

[0128] Furthermore, the user or care manager can send an on-demand request for a product through a dedicated app. The device then sends this request to the server, which then updates the current delivery route based on the received request.

[0129] For example, if User B urgently needs a blood glucose test kit, he or she sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[0130] The mobile sales vehicle follows the optimal route received from the server and visits elderly people's homes and designated locations, providing products requested by users and products recommended by the server.

[0131] As a concrete example, a mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to its next destination, the home of user B, and delivers a blood glucose testing kit.

[0132] Furthermore, the mobile sales vans will function as a place for elderly people to interact with each other while delivering products, and events such as mini-games and roundtable discussions will be held at each stop to prevent social isolation.

[0133] As a concrete example, a mobile sales truck visits nursing homes and holds mini-games and health seminars while delivering products, thereby promoting interaction between the elderly.

[0134] In this way, the present invention provides a system that allows elderly people to easily obtain daily necessities and medical products by providing personalized services according to their needs and planning efficient delivery routes.

[0135] Prompt Sentence Examples

[0136] "Please explain in detail the algorithm that generates a recommended product list based on user A's high blood pressure information and calculates and notifies the user of a highly efficient delivery route."

[0137] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0138] Step 1: Collect user data

[0139] server

[0140] The server collects data about the user's purchasing history, health status, and preferences, including information entered by the user through the app, past shopping history, and the results of regular checkups. Specifically, the server receives the data sent by the client and stores it in a database.

[0141] Terminal

[0142] The device sends the health information and preferences that the user entered into the application to the server. Specifically, the user enters data into the app, and the device sends that information to the server.

[0143] Input: Health information, purchase history, and preferences entered by the user into the device

[0144] Output: User data stored in a server-side database

[0145] Step 2: Analyze the data and generate a product list

[0146] server

[0147] The server uses an AI algorithm to generate a product list based on the collected user data. This process uses machine learning models (e.g., TensorFlow or PyTorch) to analyze the data and select the most suitable products for each user. Specifically, the server inputs the user's health data, and the AI ​​algorithm generates a personalized product list based on that data.

[0148] Input: User health information, purchase history, and preferences stored in a database

[0149] Data processing: Analyze user data using AI algorithms

[0150] Output: A personalized product list saved to the database

[0151] Step 3: Calculate delivery route and notify the mobile sales vehicle

[0152] server

[0153] The server calculates the optimal delivery route based on the user's location data and real-time traffic information. This calculation uses map data and traffic information APIs (e.g., Google Maps API). Specifically, the server analyzes the real-time traffic information collected and notifies the navigation system of the optimal route for the mobile sales vehicle.

[0154] Input: User location data, real-time traffic information

[0155] Data processing: Calculate the optimal route using traffic information API

[0156] Output: Optimized delivery route information is sent to the mobile sales vehicle's navigation system

[0157] Step 4: Accepting an On-Demand Delivery Request

[0158] User

[0159] A user or care manager uses the app to submit an on-demand request for a product. Specifically, the user enters the request in the app and presses the submit button.

[0160] Terminal

[0161] The device sends the request to the server. Specifically, it transfers the request data sent from the app to the server.

[0162] server

[0163] The server receives the request and adds a new destination to the current delivery route. Specifically, the server analyzes the received request and updates and optimizes the delivery route.

[0164] Input: On-demand requests submitted by users

[0165] Data manipulation: Add a new delivery destination to the current delivery route

[0166] Output: Updated delivery route information

[0167] Step 5: Product delivery and delivery

[0168] Mobile sales vehicle

[0169] The mobile sales vehicle follows the optimal route received from the server, travels around the specified locations, and provides products to each user. Specifically, the mobile sales vehicle arrives at the destination and provides the requested products or products recommended by the server.

[0170] Input: Optimal route information and product list sent from the server

[0171] Output: The product is served to the user

[0172] Step 6: Providing social interaction

[0173] Mobile sales vehicle

[0174] The mobile sales vans will function as a place where elderly people can interact with each other while delivering products. Specifically, they will hold events such as mini-games, roundtable discussions, and health seminars at their stops to prevent social isolation.

[0175] Input: Event program

[0176] Output: A social event for seniors will be held.

[0177] These are the specific processing steps for a personalized mobile sales service that utilizes AI and is specifically targeted at the elderly. At each step, the server, terminals, and mobile sales vehicles work together to provide efficient and personalized services.

[0178] (Application example 1)

[0179] 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."

[0180] In modern society, the increasing elderly population has become a major social issue, particularly as it becomes more difficult for the elderly to easily obtain daily necessities and groceries. Furthermore, elderly people often require specific foods and medicines depending on their health condition, requiring personalized recommendations. Furthermore, opportunities for interaction to prevent social isolation are also important. However, existing services have difficulty efficiently and consistently meeting these needs. Therefore, the present invention provides a system to solve these problems.

[0181] 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.

[0182] In this invention, the server includes: means for collecting user data including purchase history, health status, and preferences; means for generating a product list based on the collected user data; means for loading products onto a mobile food truck based on the generated product list; means for optimizing a delivery route for the mobile food truck based on the user data and traffic information; means for receiving an on-demand request from a user or a care manager; means for delivering products to the user's home or a set location based on the product list and the on-demand request; means for the mobile food truck to provide products to the user at a stop and hold a social event on the spot; a smartphone application for suggesting foods based on the user's health status; a smartphone application for transmitting a request for products desired by the user; and means for making personalized product suggestions using an AI model. This allows elderly people to easily obtain products that meet their individual needs and also provides a forum for social interaction, improving their quality of life.

[0183] "Purchase history" is a list of products that a user has purchased in the past, which allows the user's preferences and consumption patterns to be understood.

[0184] "Health status" refers to information about the user's current physical health, and specifically includes data such as blood pressure, blood sugar level, and medical history.

[0185] "Preferences" refers to the personal preferences that a user has for specific foods or products, and are an element for providing personalized services based on these preferences.

[0186] "User Data" is a collective term for a set of information about a user, including purchasing history, health status, and preferences.

[0187] A "product list" is a list of products recommended to a user, generated based on collected user data.

[0188] A "mobile sales vehicle" is a vehicle that is loaded with merchandise and moves around to provide merchandise to users.

[0189] The "delivery route" refers to the route that the mobile sales vehicle follows to deliver goods to the user.

[0190] An "on-demand request" is a request that is sent immediately when a user or care manager needs a particular product or service.

[0191] A "smartphone application" is software that runs on a smartphone and allows users to enter user data, request products, receive product lists, and so on.

[0192] An "AI model" is an algorithm that uses artificial intelligence to analyze user data and generate personalized suggestions.

[0193] A "prompt" is text data input to a generative AI model, and is an instruction statement to obtain a specific output.

[0194] This invention utilizes AI to provide a personalized mobile sales service specifically for the elderly. The program to realize this system is configured as follows.

[0195] First, we will explain the user data collection part. The device (smartphone) collects data from the user, such as purchase history, health status, and food preferences. This data is sent to a server via a mobile application. For example, when a user enters their blood pressure value into the app, the data is saved on the server.

[0196] Next, we will explain data analysis and product list generation. The server analyzes the collected user data using AI algorithms (e.g., TensorFlow, PyTorch) and generates a personalized product list for each user. This product list includes foods and medicines that are optimal for the user's health condition and preferences. For example, the server may recommend low-salt foods to a user with high blood pressure.

[0197] Calculating the delivery route is also a very important factor. The server calculates the optimal delivery route based on the user's location data and real-time traffic information. This calculation uses route calculation algorithms such as Google Maps API. The optimal route information is sent to the navigation system of the mobile sales vehicle.

[0198] The system also accepts on-demand delivery requests. Users or care managers can submit requests for specific items through a smartphone application. The request is sent from the device to a server, which uses the information to add additional stops to the current delivery route.

[0199] The mobile sales vehicle also provides and delivers products. The mobile sales vehicle travels around according to the optimal route received from the server and provides products to users. When users receive products, social events are also held at the same time. For example, a mobile sales vehicle may visit a nursing home and hold a roundtable discussion or health seminar while delivering products.

[0200] Smartphone applications that suggest foods based on a user's health status are very useful. The application suggests optimal foods based on the user's health information when the user inputs it. For example, if the user inputs "I have high blood pressure. Can you recommend some low-salt foods?", the AI ​​model generates a response.

[0201] An example of a prompt for a generative AI model is:

[0202] "I have high blood pressure. Can you recommend some low-sodium foods?"

[0203] "I was recently diagnosed with diabetes. What foods are good for me?"

[0204] Examples include:

[0205] As described above, this invention provides a wide range of functions in one, including user data collection, data analysis using AI, calculation of optimal delivery routes, acceptance of on-demand requests, product provision, and hosting of social events. This allows seniors to easily obtain products that meet their individual needs, while also providing a venue for social interaction, improving their quality of life.

[0206] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0207] Step 1:

[0208] A user inputs data such as health information, food preferences, and past purchasing history into a smartphone application. This data is sent from the user's device (smartphone) to a server. Examples of input data include blood pressure, blood sugar levels, and favorite foods. The server receives this data and stores it in a database. At this stage, the input is the user's health information, preferences, and purchasing history, and the output is user data stored on the server.

[0209] Step 2:

[0210] The server performs data analysis using AI algorithms (e.g., TensorFlow, PyTorch) based on the stored user data. The data processing performed here generates a personalized product list based on the user's health condition and purchasing history. For example, this product list might suggest low-salt foods and blood pressure monitors to a user with high blood pressure. The input is the stored user data, and the output is a personalized product list.

[0211] Step 3:

[0212] The server then sends information for loading products onto the mobile sales vehicle based on the generated product list. This loading information contains detailed information about the products required by each user. For example, the server generates an inventory list of specific products based on the product list and sends it to the mobile sales vehicle management system. The input is the product list, and the output is the loading information.

[0213] Step 4:

[0214] The server optimizes the delivery routes of the mobile sales vehicles based on user data and real-time traffic information. This optimization uses route calculation algorithms such as Google Maps API. The data processing here involves calculating the most efficient route based on each user's location and real-time traffic information. The input is user location data and real-time traffic information, and the output is the optimized delivery route.

[0215] Step 5:

[0216] A user or care manager submits an on-demand request for a product through a smartphone application. This request is sent from the device to the server and added to the current delivery route. For example, the server responds by adding a new stop to the existing route. The input is the on-demand request, and the output is the updated delivery route.

[0217] Step 6:

[0218] The mobile food truck travels around according to the optimal delivery route received from the server. At each stop, the mobile food truck provides products to users and also holds social events. For example, when the mobile food truck visits a nursing home, it not only provides products but also holds mini-games and round-table discussions. The input is the optimal delivery route and product list, and the output is the delivered products and a place for positive social interaction.

[0219] Step 7:

[0220] A user uses a smartphone application to input a product request or question to the AI ​​model. For example, "I have high blood pressure. Can you recommend some low-salt foods?" The server runs the AI ​​model based on this prompt and provides appropriate products and information. The input is the user's prompt, and the output is the suggestions and information obtained from the AI ​​model.

[0221] 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.

[0222] This invention utilizes AI and an emotion engine to provide a personalized mobile sales service specifically for the elderly. Hereinafter, a specific embodiment of the invention will be described.

[0223] 1. Collection of User Data

[0224] server

[0225] The server collects data about the user's purchasing history, health status, and preferences, including information the user enters through the app, past shopping history, and results of regular checkups. Using a device, the user enters their health information and preferences into the application, which is then sent to the server.

[0226] Specific examples

[0227] User A enters his / her high blood pressure information and low-salt food purchase history into the app. The device sends the information to the server, which stores it in a database.

[0228] 2. Use of Emotion Engine

[0229] server

[0230] In addition to user data, the server uses an emotion engine to recognize the user's emotional state. For example, emotions can be read through facial recognition technology while the user is using the app. This emotion data is also stored in the database.

[0231] Specific examples

[0232] When User A uses the app, the emotion engine analyzes the user's facial expressions and recognizes that their current emotional state is happiness. This information is sent to the server and stored in the database.

[0233] 3. Analyze data and generate product list

[0234] server

[0235] Based on the collected user data and emotional data, the server uses AI algorithms to generate a personalized product list for each user, adjusting product selection and suggestions depending on the user's emotional state.

[0236] Specific examples

[0237] Based on the user A's high blood pressure information and the analysis results of the emotion engine, the server adds low-salt foods to the recommended product list, and further suggests special foods when the emotion is happy.

[0238] 4. Calculating delivery routes and notifying mobile sales vehicles

[0239] server

[0240] The server calculates the optimal delivery route based on the user's location data and real-time traffic information, and transmits this optimal route information to the mobile sales vehicle's terminal.

[0241] Specific examples

[0242] Based on the traffic information collected by the server, the most efficient route from the area where user A lives to the address of user B is calculated and sent to the navigation system of the mobile sales vehicle.

[0243] 5. Acceptance of On-Demand Delivery Requests

[0244] User

[0245] Users or care managers can submit on-demand requests for products through the app.

[0246] Terminal

[0247] The terminal sends these requests to the server.

[0248] server

[0249] The server accepts the request and adds it to the current delivery route.

[0250] Specific examples

[0251] User B suddenly needs a blood glucose test kit and sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[0252] 6. Supply and delivery of goods

[0253] Mobile sales vehicle

[0254] The mobile sales vehicle follows the optimal route received from the server and visits elderly people's homes and designated locations, providing products requested by users and recommended products.

[0255] Specific examples

[0256] The mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to the next destination, the home of user B, and delivers a blood glucose testing kit.

[0257] 7. Providing a platform for social interaction

[0258] Mobile sales vehicle

[0259] The mobile sales vans will serve as a place for seniors to interact with each other while delivering products, and will hold events such as mini-games and roundtable discussions at each stop to prevent social isolation.

[0260] Specific examples

[0261] Mobile sales trucks visit nursing homes and promote interaction between the elderly by holding mini-games and health seminars while delivering products.

[0262] summary

[0263] This invention utilizes AI and an emotion engine to provide personalized services tailored to the needs of elderly people and to provide a system that plans efficient delivery routes. By combining this with an emotion engine, it is possible to provide products and social interactions based on the user's emotional state, improving their quality of life.

[0264] The processing flow will be explained below.

[0265] Step 1:

[0266] Through the application, users input data about their purchasing history, health status, and preferences. For example, a user may input information about their high blood pressure or a preference for low-salt foods.

[0267] Step 2:

[0268] The terminal receives the data entered by the user and sends it to the server, which then sends it to the server in the appropriate format.

[0269] Step 3:

[0270] The server stores the received user data in a database, organizing information such as purchase history, health status, and preferences, and recording it in a specific format.

[0271] Step 4:

[0272] The server uses an emotion engine to collect data to recognize the user's emotional state. For example, while the user is using the app, facial recognition technology is used to analyze facial expressions and obtain emotional data in real time.

[0273] Step 5:

[0274] The device sends the emotion data acquired from the emotion engine to the server. The device then sends the facial recognition results and emotional state data to the server.

[0275] Step 6:

[0276] The server stores the emotion data in a database and integrates it with user data for analysis. For example, when a user shows happy emotions, it can enhance the recommendation of a specific product.

[0277] Step 7:

[0278] The server uses an AI algorithm to generate a personalized product list based on user data and emotional data. Product selection and recommendations are adjusted according to the user's emotional state.

[0279] Step 8:

[0280] The server stores the generated product list in a database and sends it to the mobile sales vehicle, which loads the products based on this information.

[0281] Step 9:

[0282] The server collects user location data and real-time traffic information and calculates the optimal delivery route.

[0283] Step 10:

[0284] The server calculates the optimal route and sends it to the mobile sales vehicle's terminal, which receives this information and sets the navigation according to the instructions.

[0285] Step 11:

[0286] A user or care manager sends an on-demand request through the app. For example, if User B urgently needs a blood glucose test kit, he or she sends this information as a request.

[0287] Step 12:

[0288] The terminal sends an on-demand request to the server.

[0289] Step 13:

[0290] The server accepts the on-demand request and recalculates and updates the current delivery route.

[0291] Step 14:

[0292] The server sends the recalculated route information to the mobile sales vehicle's terminal, which receives the information and moves along the new route.

[0293] Step 15:

[0294] The mobile sales vehicle travels according to the optimal route received from the server, visiting elderly people's homes and designated locations, and delivering the products loaded on it based on the user's personalized product list.

[0295] Step 16:

[0296] The mobile food truck arrives at its destination, offers products to users, and hosts social events at each stop, such as health seminars or mini-games.

[0297] Step 17:

[0298] Users receive the products and, if necessary, participate in events to interact with other elderly people.

[0299] Example 2

[0300] 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."

[0301] In mobile sales services for the elderly, conventional services have difficulty proposing products according to the user's health condition and individual preferences, and have not sufficiently improved convenience and satisfaction. Furthermore, while efficiency can be improved by calculating optimal delivery routes, providing a place for interaction to prevent social isolation among the elderly has not been fully realized.

[0302] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting user information including purchase history, health status, and preferences, means for generating a product list based on the collected user information and emotion data, means for loading products onto a mobile sales vehicle based on the generated product list, means for optimizing a delivery route of the mobile sales vehicle based on user location data and traffic information, means for accepting on-demand requests from users or care managers, means for delivering products to the user's home or a designated location based on the product list and the on-demand request, and means for the mobile sales vehicle to provide products to users at stops and hold social events on the spot. This enables personalized product provision and efficient delivery according to the individual needs of elderly people and prevents social isolation through interaction between elderly people.

[0303] "Purchase history" is a record of products purchased by a user in the past.

[0304] "Health Status" is information about a user's physical and mental health.

[0305] "Preferences" is information that indicates the user's personal tastes and selection tendencies.

[0306] "User Information" refers to all data about a user, including purchasing history, health status, and preferences.

[0307] "Emotion data" is information that indicates the emotional state of the user analyzed from facial expressions, voice, etc.

[0308] The "product list" is a list of products recommended to a user, generated based on user information and emotion data.

[0309] A "mobile sales vehicle" is a vehicle that transports merchandise along a set route and offers the merchandise at each stop.

[0310] A "delivery route" refers to the route taken by a mobile sales vehicle to deliver goods.

[0311] An "on-demand request" is a request from a user or care manager to provide a specific product.

[0312] A "stop" is a location where a mobile food truck temporarily stops to offer products and host events.

[0313] "Social events" refer to social activities such as mini-games and roundtable discussions that are offered to users by mobile food trucks at their stops.

[0314] An "AI algorithm" is a computational method that uses artificial intelligence to analyze data and identify patterns and trends.

[0315] "Real-time traffic information" is data for acquiring and analyzing current traffic conditions in real time.

[0316] This invention utilizes AI and an emotion engine to provide a personalized mobile sales service specifically for the elderly. Hereinafter, a specific embodiment of the invention will be described.

[0317] 1. Collection of User Data

[0318] server

[0319] The server collects data on the user's purchasing history, health status, and preferences. The collected data includes information entered by the user through the application, past purchase history, and results of regular checkups. This data is stored in a database and used for subsequent processing. The device used is a mobile device such as a smartphone or tablet, and the user enters the information using this device.

[0320] Specific examples

[0321] User A enters his / her high blood pressure information and low-salt food purchase history into the app. The device sends the information to the server, which stores it in a database.

[0322] 2. Use of Emotion Engine

[0323] server

[0324] In addition to user data, the server uses an emotion engine to recognize the user's emotional state. For example, while the user is using the app, the server captures their facial expressions using the device's camera and reads their emotions through facial recognition technology. This emotional data is also stored in the database.

[0325] Specific examples

[0326] When User A uses the app, the emotion engine analyzes the user's facial expressions and recognizes that their current emotional state is happiness. This information is sent to the server and stored in the database.

[0327] 3. Analyze data and generate product list

[0328] server

[0329] Based on the collected user data and emotional data, the server uses a generative AI model (AI algorithm) to generate a personalized product list for each user. Product selection and suggestions are adjusted according to the user's emotional state. In particular, the server creates a list of products that are optimal for each individual user based on attribute information such as health information and purchasing history.

[0330] Specific examples

[0331] Based on the user A's high blood pressure information and the analysis results of the emotion engine, the server adds low-salt foods to the recommended product list, and further suggests special foods when the emotion is happy.

[0332] 4. Calculating delivery routes and notifying mobile sales vehicles

[0333] server

[0334] The server uses the user's location data and real-time traffic information to calculate the optimal delivery route. This calculation uses a route optimization algorithm that takes road congestion into account. The optimal route information is then sent to the mobile sales vehicle's terminal.

[0335] Specific examples

[0336] Based on the traffic information collected by the server, the most efficient route from the area where user A lives to the address of user B is calculated and sent to the navigation system of the mobile sales vehicle.

[0337] 5. Acceptance of On-Demand Delivery Requests

[0338] User

[0339] Users or care managers submit on-demand product requests through the app, which include details of the product needed and a delivery address.

[0340] Terminal

[0341] The terminal sends these requests to the server.

[0342] server

[0343] The server accepts the request and adds the new destination to the current delivery route.

[0344] Specific examples

[0345] User B suddenly needs a blood glucose test kit and sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[0346] 6. Supply and delivery of goods

[0347] Mobile sales vehicle

[0348] The mobile sales vehicle will follow the optimal route received and visit the elderly person's home or designated location, providing the products requested by the user and recommended products.

[0349] Specific examples

[0350] The mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to the next destination, the home of user B, and delivers a blood glucose testing kit.

[0351] 7. Providing a platform for social interaction

[0352] Mobile sales vehicle

[0353] While providing products, the mobile food trucks also serve as a place for seniors to interact with each other, holding events such as mini-games and roundtable discussions at each stop to prevent social isolation.

[0354] Specific examples

[0355] Mobile sales trucks visit nursing homes and promote interaction between the elderly by holding mini-games and health seminars while delivering products.

[0356] Prompt Sentence Examples

[0357] Describe how the system works when a user enters new health information into the app.

[0358] summary

[0359] This invention is a system that utilizes AI and an emotion engine to provide personalized products and efficient delivery according to the needs of the elderly, and also promotes social interaction among the elderly, thereby improving the quality of life of users.

[0360] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0361] Step 1:

[0362] The user enters information into the app

[0363] User

[0364] Users open the application on their smartphone, tablet, or other device and enter information about their purchasing history, health status, and preferences. Data entered at this stage includes the user's medical history (e.g., high blood pressure), recent purchases (e.g., low-salt foods), and preferences (e.g., specific flavors or brands). The entered data is then stored on the device.

[0365] Input: User-entered purchasing history, health status, and preference information

[0366] Output: User information temporarily saved on the device

[0367] Specific actions

[0368] User A enters his or her high blood pressure information and low-salt food purchase history into the app.

[0369] Step 2:

[0370] The device sends the information to the server

[0371] Terminal

[0372] The terminal sends the information entered by the user to the server. This transmission process is done in real time using a communication protocol (e.g., HTTPS), and the data is encrypted before being sent. The server receives this information and adds it to a database as is.

[0373] Input: User information entered into the terminal

[0374] Output: User information sent to the server

[0375] Specific actions

[0376] User A's high blood pressure information and low-salt food purchase history are sent from the terminal to the server.

[0377] Step 3:

[0378] The server acquires emotion data

[0379] server

[0380] The server captures the user's facial expressions using the device's camera while the user is using the app and analyzes them with the emotion engine. The analyzed emotion data indicates the user's emotional state (e.g., happiness, sadness). The analysis results are sent to the server and stored in a database.

[0381] Input: Captured user facial expression data

[0382] Output: Parsed emotion data

[0383] Specific actions

[0384] When User A uses the app, the device camera captures User A's facial expression, and the emotion engine analyzes the emotion "happiness." The results are sent to the server.

[0385] Step 4:

[0386] The server analyzes the user data and generates a product list

[0387] server

[0388] The server uses an AI algorithm to generate a personalized product list based on the collected user data and emotional data. The AI ​​algorithm selects the most suitable products based on the user's health and emotional state and builds the list.

[0389] Input: User data and emotion data

[0390] Output: Personalized product list

[0391] Specific actions

[0392] The server adds low-salt foods to the recommended product list based on user A's high blood pressure information and the analysis results of the emotion engine, and also suggests special foods when the emotion is happy.

[0393] Step 5:

[0394] The server calculates the delivery route

[0395] server

[0396] The server integrates the user's location data and real-time traffic information to calculate the optimal delivery route, using a route optimization algorithm that takes into account factors such as road congestion, distance, and time. The calculated optimal route information is then sent to the mobile sales vehicle's terminal.

[0397] Input: User location data and real-time traffic information

[0398] Output: Optimal delivery route

[0399] Specific actions

[0400] The server calculates the optimal delivery route based on user A's address and current traffic conditions, and sends it to the navigation system of the mobile sales vehicle.

[0401] Step 6:

[0402] The server accepts the on-demand request and adds it to the route

[0403] server

[0404] When a user or care manager submits an on-demand request through the app, it is sent to the server, which accepts the request and adds a new delivery destination to the current delivery route.

[0405] Input: On-demand requests from users or care managers

[0406] Output: Updated delivery route

[0407] Specific actions

[0408] User B suddenly needs a blood glucose test kit and sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[0409] Step 7:

[0410] A mobile sales vehicle delivers goods along a route

[0411] Mobile sales vehicle

[0412] The mobile sales vehicle will follow the optimal route received and visit the elderly person's home or designated location, providing the products requested by the user and recommended products.

[0413] Input: Optimal delivery route and product list

[0414] Output: Item delivered to user

[0415] Specific actions

[0416] The mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to the next destination, the home of user B, and delivers a blood glucose testing kit.

[0417] Step 8:

[0418] Mobile food trucks provide a platform for social interaction

[0419] Mobile sales vehicle

[0420] While providing products, the mobile food trucks also serve as a place for seniors to interact with each other, holding events such as mini-games and roundtable discussions at each stop to prevent social isolation.

[0421] Input: Stops and Event Plan

[0422] Output: Social events held

[0423] Specific actions

[0424] Mobile sales trucks visit nursing homes and promote interaction between the elderly by holding mini-games and health seminars while delivering products.

[0425] (Application example 2)

[0426] 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."

[0427] Food delivery services for the elderly are required to simultaneously propose products based on not only the user's health status but also their emotional state, while improving delivery efficiency. It is also important to provide a place for social interaction and prevent isolation among the elderly. Current technology does not offer a system that comprehensively addresses these multiple factors, so a more effective system is needed to improve the quality of life for the elderly.

[0428] 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.

[0429] In this invention, the server includes means for collecting user data including purchase history, health status, and preferences, means for collecting the user's emotional state using emotion recognition technology, and means for generating a product list based on the collected user data and emotional state data. This makes it possible to generate a personalized product list based on the user's health status and emotional state, select an optimal delivery route, and provide appropriate products and services to elderly people. In addition, by having the mobile sales van deliver products to users at each stop and holding social events on the spot, it is possible to provide a place for social interaction among elderly people and prevent isolation.

[0430] "Purchase history" is a list of products purchased by the user in the past, along with detailed information about those products.

[0431] "Health status" refers to information related to the user's physical condition and medical care, such as blood pressure, blood sugar level, and allergy information.

[0432] "Preferences" are information about things that a user particularly likes or wants to avoid.

[0433] "Emotion recognition technology" is a technology that uses facial recognition, voice analysis, etc. to identify a user's emotional state.

[0434] "User Data" refers collectively to data including purchasing history, health status, preferences, and other personal information.

[0435] "Emotional state data" is data relating to the user's emotions obtained using emotion recognition technology.

[0436] The "product list" is a list of products to be recommended to the user, generated based on the user data and emotional state data.

[0437] A "mobile sales vehicle" is a vehicle that can stop at a designated location and provide products.

[0438] "Traffic information" refers to information related to traffic, such as road congestion and traffic regulations, that is collected in real time.

[0439] An "on-demand request" is a request to order a product made on the spot by a user or a care manager.

[0440] A "social interaction space" is a space or opportunity where users can interact and socialize with each other when providing products.

[0441] "Generative AI model" is a general term for artificial intelligence algorithms that generate product lists, etc. based on user data and emotional state data.

[0442] This invention is a system for providing a personalized food delivery service specifically for the elderly using AI and an emotion engine. The following describes in detail an embodiment of this invention.

[0443] The server first collects user data, including purchase history, health status, and preferences. This includes information entered by the user through a smartphone application, past purchase history, and regular checkup results. For example, User A enters his or her high blood pressure information and low-salt food purchase history into the app, and the data is sent to the server. The server stores this information in a database.

[0444] Next, the server uses emotion recognition technology to collect the user's emotional state. When a user uses a smartphone application, the camera scans their face and emotion recognition technology is used to read their emotions. This emotion data is also sent to the server and stored in a database. For example, user A's face is scanned while using an app, and the app recognizes that their emotion is happiness, and this information is sent to the server.

[0445] The server uses a generative AI model based on the collected user data and emotional state data to generate a personalized product list. This allows the server to suggest optimal products based on the user's health condition and current emotional state. For example, in the case of User A, based on information about high blood pressure and a feeling of happiness, it is possible to suggest low-salt foods as well as sweets as a special treat.

[0446] The server also calculates the optimal delivery route for the mobile sales vehicle based on user data and real-time traffic information. This optimal route information is sent to the sales vehicle's terminal. For example, the server calculates the shortest route from the area where user A lives to the address of user B, and sends this information to the navigation system of the mobile sales vehicle.

[0447] Additionally, users or care managers can send on-demand requests through the application. The device sends these requests to the server, which accepts the requests and adds them to the current delivery route. For example, User B suddenly needs a blood glucose test kit and sends a request through the application. This information is sent to the server, which adds User B's address to the existing route.

[0448] Finally, the mobile sales vehicle follows the optimal route received from the server and visits the elderly person's home or other designated locations, providing the products requested or recommended by the user. For example, the sales vehicle arrives at User A's home and provides low-salt food and a sweet treat, then heads to the next destination, User B's home, to deliver a blood glucose testing kit.

[0449] In this invention, the mobile sales van can provide products to users at the stops and also hold social events on the spot. This allows elderly people to interact with each other and deepen social interactions. As a specific example, the mobile sales van can visit a nursing home and hold mini-games and health seminars while providing products, thereby promoting interaction between elderly people.

[0450] An example prompt for a generative AI model is, "Design a system that allows elderly people to input their health and emotional state via a smartphone app, and then uses AI and an emotion engine to generate a personalized food list and delivery route."

[0451] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0452] Step 1:

[0453] User Data Collection

[0454] The device collects user data (purchase history, health status, and preferences). The user enters their information through a smartphone app, and the device sends the data to a server. The server stores this data in a database. For example, this data may include information about User A's high blood pressure and preference for low-salt foods.

[0455] Step 2:

[0456] Emotion recognition data collection

[0457] The device collects data on the user's emotional state. While the user is using a smartphone app, the camera scans the user's face and sends the image to emotion recognition technology. The emotion recognition technology analyzes the image and determines the user's emotional state. The results of this determination are sent from the device to a server and stored in a database. For example, if User A is recognized as having a happy emotion while using the app, that information is sent to the server.

[0458] Step 3:

[0459] Generate personalized product lists

[0460] Based on the user data and emotional state data collected by the server, a generative AI model is used to generate a personalized product list. Input data includes health status and emotional state, and specific products are selected based on that data. For example, in the case of User A, low-salt foods and treat sweets are included in the list because User A has high blood pressure and is in a state of happiness.

[0461] Step 4:

[0462] Calculating the optimal delivery route

[0463] The server calculates the optimal delivery route for the mobile sales truck based on user data and real-time traffic information. Inputs include each user's location and current traffic conditions. The server calculates this data and calculates the shortest and most efficient route. As a result, optimal route information from a specific user's address to the next user's address is generated and sent to the mobile sales truck's terminal.

[0464] Step 5:

[0465] Accepting on-demand requests

[0466] A user or care manager sends an on-demand request through a smartphone app. The device receives this request and sends it to the server. The server accepts the request and adds the address corresponding to the request to the existing delivery route. For example, User B suddenly needs a blood glucose test kit and sends a request from the app. The information is sent to the server, and User B's address is added to the delivery route.

[0467] Step 6:

[0468] Supply and delivery of goods

[0469] The mobile sales vehicle travels according to the optimal route received from the server, and delivers products to the user's home or a specified location. Specifically, the sales vehicle arrives at the home of user A and delivers low-salt foods and sweets. It then heads to the home of user B, its next destination, and delivers a blood glucose testing kit.

[0470] Step 7:

[0471] Providing a venue for social interaction

[0472] The mobile sales truck will deliver products to users at each stop and also hold social events on the spot. This allows users to interact with each other and deepen social interactions. For example, a mobile sales truck may visit a nursing home and hold mini-games and health seminars while delivering products, promoting interaction between the elderly.

[0473] 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.

[0474] 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.

[0475] 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.

[0476] [Second embodiment]

[0477] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0478] 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.

[0479] 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).

[0480] 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.

[0481] 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.

[0482] 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).

[0483] 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.

[0484] 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.

[0485] 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.

[0486] 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.

[0487] 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.

[0488] 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."

[0489] This invention utilizes AI to provide a personalized mobile sales service specifically for the elderly. Hereinafter, an embodiment of the invention will be described in detail.

[0490] 1. Collection of User Data

[0491] server

[0492] The server collects data about the user's purchasing history, health status, and preferences, including information the user enters through the app, past shopping history, and results of regular checkups. Using a device, the user enters their health information and preferences into the application, which is then sent to the server.

[0493] Specific examples

[0494] User A enters his / her high blood pressure information and low-salt food purchase history into the app. The device sends the information to the server, which stores it in a database.

[0495] 2. Analyze data and generate product list

[0496] server

[0497] Based on the collected user data, the server uses an AI algorithm to generate a personalized product list for each user, including medicines tailored to their health condition, foods tailored to their preferences, etc. The generated product list is stored in a database for each user.

[0498] Specific examples

[0499] Based on User A's high blood pressure information, the server adds low-salt foods and blood pressure monitors to the recommended product list.

[0500] 3. Calculating delivery routes and notifying mobile sales vehicles

[0501] server

[0502] The server calculates the optimal delivery route based on the user's location data and real-time traffic information, and sends this optimal route information to the mobile sales vehicle's terminal.

[0503] Specific examples

[0504] Based on the traffic information collected by the server, the most efficient route from the area where user A lives to the address of user B is calculated and sent to the navigation system of the mobile sales vehicle.

[0505] 4. Acceptance of On-Demand Delivery Requests

[0506] User

[0507] Users or care managers can submit on-demand requests for products through the app.

[0508] Terminal

[0509] The terminal sends these requests to the server.

[0510] server

[0511] The server accepts the request and adds it to the current delivery route.

[0512] Specific examples

[0513] User B suddenly needs a blood glucose test kit and sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[0514] 5. Supply and delivery of goods

[0515] Mobile sales vehicle

[0516] The mobile sales vehicle follows the optimal route received from the server and visits elderly people's homes and designated locations, providing products requested by users and recommended products.

[0517] Specific examples

[0518] The mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to the next destination, the home of user B, and delivers a blood glucose testing kit.

[0519] 6. Providing a platform for social interaction

[0520] Mobile sales vehicle

[0521] The mobile sales vans will serve as a place for seniors to interact with each other while delivering products, and will hold events such as mini-games and roundtable discussions at each stop to prevent social isolation.

[0522] Specific examples

[0523] Mobile sales trucks visit nursing homes and promote interaction between the elderly by holding mini-games and health seminars while delivering products.

[0524] summary

[0525] This invention utilizes AI to provide personalized services tailored to the needs of the elderly and provides a system that plans efficient delivery routes, allowing them to easily obtain daily necessities and medical products while providing opportunities for social interaction and improving their quality of life.

[0526] The processing flow will be explained below.

[0527] Step 1:

[0528] Through the application, users input data about their purchasing history, health status, and preferences. For example, a user may input information about their high blood pressure or a preference for low-salt foods.

[0529] Step 2:

[0530] The terminal receives the data entered by the user and transmits it to the server.

[0531] Step 3:

[0532] The server stores the received user data in a database, organizing information such as purchase history, health status, and preferences, and storing it in a specific format.

[0533] Step 4:

[0534] The server uses AI algorithms to analyze the stored user data and generate a personalized product list for each user, for example, recommending low-salt foods to a user with high blood pressure.

[0535] Step 5:

[0536] The server stores the generated product list in a database and transmits it to the mobile sales vehicle.

[0537] Step 6:

[0538] The server collects user location data and real-time traffic information, and uses this data to calculate the optimal delivery route using an AI algorithm.

[0539] Step 7:

[0540] The server then sends the calculated optimal route to the mobile sales vehicle's terminal, which receives this information and sets the route according to the instructions.

[0541] Step 8:

[0542] A user or care manager can send an on-demand request through the application. For example, if User B urgently needs a blood glucose test kit, he or she can send this information as a request.

[0543] Step 9:

[0544] The terminal sends an on-demand request to the server.

[0545] Step 10:

[0546] The server receives on-demand requests and recalculates and updates the current delivery route.

[0547] Step 11:

[0548] The server then sends the recalculated route information to the mobile sales vehicle's terminal, which receives the information and moves along the new route.

[0549] Step 12:

[0550] The mobile sales vehicle follows the optimal route received from the server, visits elderly people's homes and other designated locations, and delivers the products loaded on it based on the user's personalized product list.

[0551] Step 13:

[0552] The mobile food truck arrives at its destination, offers products to users, and hosts social events at each stop, such as health seminars or mini-games.

[0553] Step 14:

[0554] Users receive the products and, if necessary, participate in events to interact with other elderly people.

[0555] Example 1

[0556] 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."

[0557] Elderly people face challenges in easily obtaining daily necessities and medicines, and are prone to feeling socially isolated. Current mobile sales services often lack the ability to provide products tailored to the user's health condition and preferences, and delivery routes are often not optimized for efficiency. Furthermore, they lack a system capable of responding to on-demand requests, making it difficult to respond to sudden demand. To address these issues, it is necessary to provide personalized products specifically for the elderly, establish efficient delivery routes, and promote social interaction.

[0558] 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.

[0559] In this invention, the server includes means for collecting user data including purchase history, health status, and preferences, means for generating a product list based on the collected user data, means for loading products onto a mobile food truck based on the generated product list, means for optimizing a delivery route for the mobile food truck based on the user data and traffic information, means for receiving an on-demand request from a user or a care manager, means for delivering products to the user's home or a set location based on the product list and the on-demand request, means for the mobile food truck to provide products to the user at a stop and hold a social event on the spot, means for the mobile food truck to add on-demand delivery based on the user's request, means for generating a personalized product list using an AI algorithm, and means for calculating a delivery route based on real-time traffic information. This not only enables elderly people to easily obtain the products they need, but also enables the establishment of efficient delivery routes and promotion of social interactions.

[0560] "Purchase history" is data that records details of products and services purchased by a user in the past.

[0561] "Health Status" refers to information about a user's physical and mental health, including data based on medical records and self-reporting.

[0562] "Preferences" are data that indicate a user's tendency to prefer certain types of products or services.

[0563] "User Data" refers to information including purchasing history, health status, and preferences.

[0564] A "product list" is a list of recommended products and services generated for each user based on collected user data.

[0565] A "mobile sales vehicle" is a vehicle that operates to provide products and services to users.

[0566] "Delivery route" refers to the route taken by a mobile sales vehicle to deliver goods.

[0567] An "on-demand request" is a request made by a user or care manager for an urgently needed product or service.

[0568] An "AI algorithm" is a program that uses machine learning and artificial intelligence technology to analyze data and make predictions.

[0569] "Real-time traffic information" refers to data that provides real-time information on current traffic conditions and road congestion.

[0570] "Social networking events" refer to activities such as mini-games, roundtable discussions, and seminars that are planned to encourage social interaction among seniors.

[0571] This invention is a system that utilizes AI to provide a personalized mobile sales service specifically for the elderly. Specific embodiments for carrying out this invention will be described below.

[0572] First, the server collects user data, including purchase history, health status, and preferences. This includes information entered by the user through a dedicated application, past purchase history, and the results of regular checkups. The devices used are devices such as smartphones and tablets, and the data entered through these devices is sent to the server.

[0573] For example, user A enters his or her high blood pressure information and low-salt food purchase history into the app. The device then sends the information to the server, which then stores it in a database.

[0574] Next, the server uses an AI algorithm based on the collected user data to generate a personalized product list for each user. The AI ​​algorithm typically uses machine learning models such as TensorFlow or PyTorch. The generated product list is stored in a database for each user.

[0575] For example, the server adds low-salt foods and blood pressure monitors to the recommended product list based on User A's high blood pressure information. An AI algorithm then operates to generate the optimal product list.

[0576] The server then calculates the optimal delivery route based on the user's location data and real-time traffic information. This process uses map data and traffic information APIs such as Google Maps API. The calculation results are sent to the navigation system of the mobile sales vehicle.

[0577] As a specific example, based on traffic information collected by the server, the most efficient route from the area where user A lives to the address of user B is calculated and sent to the navigation system of the mobile sales vehicle.

[0578] Furthermore, the user or care manager can send an on-demand request for a product through a dedicated app. The device then sends this request to the server, which then updates the current delivery route based on the received request.

[0579] For example, if User B urgently needs a blood glucose test kit, he or she sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[0580] The mobile sales vehicle follows the optimal route received from the server and visits elderly people's homes and designated locations, providing products requested by users and products recommended by the server.

[0581] As a concrete example, a mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to its next destination, the home of user B, and delivers a blood glucose testing kit.

[0582] Furthermore, the mobile sales vans will function as a place for elderly people to interact with each other while delivering products, and events such as mini-games and roundtable discussions will be held at each stop to prevent social isolation.

[0583] As a concrete example, a mobile sales truck visits nursing homes and holds mini-games and health seminars while delivering products, thereby promoting interaction between the elderly.

[0584] In this way, the present invention provides a system that allows elderly people to easily obtain daily necessities and medical products by providing personalized services according to their needs and planning efficient delivery routes.

[0585] Prompt Sentence Examples

[0586] "Please explain in detail the algorithm that generates a recommended product list based on user A's high blood pressure information and calculates and notifies the user of a highly efficient delivery route."

[0587] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0588] Step 1: Collect user data

[0589] server

[0590] The server collects data about the user's purchasing history, health status, and preferences, including information entered by the user through the app, past shopping history, and the results of regular checkups. Specifically, the server receives the data sent by the client and stores it in a database.

[0591] Terminal

[0592] The device sends the health information and preferences that the user entered into the application to the server. Specifically, the user enters data into the app, and the device sends that information to the server.

[0593] Input: Health information, purchase history, and preferences entered by the user into the device

[0594] Output: User data stored in a server-side database

[0595] Step 2: Analyze the data and generate a product list

[0596] server

[0597] The server uses an AI algorithm to generate a product list based on the collected user data. This process uses machine learning models (e.g., TensorFlow or PyTorch) to analyze the data and select the most suitable products for each user. Specifically, the server inputs the user's health data, and the AI ​​algorithm generates a personalized product list based on that data.

[0598] Input: User health information, purchase history, and preferences stored in a database

[0599] Data processing: Analyze user data using AI algorithms

[0600] Output: A personalized product list saved to the database

[0601] Step 3: Calculate delivery route and notify the mobile sales vehicle

[0602] server

[0603] The server calculates the optimal delivery route based on the user's location data and real-time traffic information. This calculation uses map data and traffic information APIs (e.g., Google Maps API). Specifically, the server analyzes the real-time traffic information collected and notifies the navigation system of the optimal route for the mobile sales vehicle.

[0604] Input: User location data, real-time traffic information

[0605] Data processing: Calculate the optimal route using traffic information API

[0606] Output: Optimized delivery route information is sent to the mobile sales vehicle's navigation system

[0607] Step 4: Accepting an On-Demand Delivery Request

[0608] User

[0609] A user or care manager uses the app to submit an on-demand request for a product. Specifically, the user enters the request in the app and presses the submit button.

[0610] Terminal

[0611] The device sends the request to the server. Specifically, it transfers the request data sent from the app to the server.

[0612] server

[0613] The server receives the request and adds a new destination to the current delivery route. Specifically, the server analyzes the received request and updates and optimizes the delivery route.

[0614] Input: On-demand requests submitted by users

[0615] Data manipulation: Add a new delivery destination to the current delivery route

[0616] Output: Updated delivery route information

[0617] Step 5: Product delivery and delivery

[0618] Mobile sales vehicle

[0619] The mobile sales vehicle follows the optimal route received from the server, travels around the specified locations, and provides products to each user. Specifically, the mobile sales vehicle arrives at the destination and provides the requested products or products recommended by the server.

[0620] Input: Optimal route information and product list sent from the server

[0621] Output: The product is served to the user

[0622] Step 6: Providing social interaction

[0623] Mobile sales vehicle

[0624] The mobile sales vans will function as a place where elderly people can interact with each other while delivering products. Specifically, they will hold events such as mini-games, roundtable discussions, and health seminars at their stops to prevent social isolation.

[0625] Input: Event program

[0626] Output: A social event for seniors will be held.

[0627] These are the specific processing steps for a personalized mobile sales service that utilizes AI and is specifically targeted at the elderly. At each step, the server, terminals, and mobile sales vehicles work together to provide efficient and personalized services.

[0628] (Application example 1)

[0629] 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."

[0630] In modern society, the increasing elderly population has become a major social issue, particularly as it becomes more difficult for the elderly to easily obtain daily necessities and groceries. Furthermore, elderly people often require specific foods and medicines depending on their health condition, requiring personalized recommendations. Furthermore, opportunities for interaction to prevent social isolation are also important. However, existing services have difficulty efficiently and consistently meeting these needs. Therefore, the present invention provides a system to solve these problems.

[0631] 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.

[0632] In this invention, the server includes: means for collecting user data including purchase history, health status, and preferences; means for generating a product list based on the collected user data; means for loading products onto a mobile food truck based on the generated product list; means for optimizing a delivery route for the mobile food truck based on the user data and traffic information; means for receiving an on-demand request from a user or a care manager; means for delivering products to the user's home or a set location based on the product list and the on-demand request; means for the mobile food truck to provide products to the user at a stop and hold a social event on the spot; a smartphone application for suggesting foods based on the user's health status; a smartphone application for transmitting a request for products desired by the user; and means for making personalized product suggestions using an AI model. This allows elderly people to easily obtain products that meet their individual needs and also provides a forum for social interaction, improving their quality of life.

[0633] "Purchase history" is a list of products that a user has purchased in the past, which allows the user's preferences and consumption patterns to be understood.

[0634] "Health status" refers to information about the user's current physical health, and specifically includes data such as blood pressure, blood sugar level, and medical history.

[0635] "Preferences" refers to the personal preferences that a user has for specific foods or products, and are an element for providing personalized services based on these preferences.

[0636] "User Data" is a collective term for a set of information about a user, including purchasing history, health status, and preferences.

[0637] A "product list" is a list of products recommended to a user, generated based on collected user data.

[0638] A "mobile sales vehicle" is a vehicle that is loaded with merchandise and moves around to provide merchandise to users.

[0639] The "delivery route" refers to the route that the mobile sales vehicle follows to deliver goods to the user.

[0640] An "on-demand request" is a request that is sent immediately when a user or care manager needs a particular product or service.

[0641] A "smartphone application" is software that runs on a smartphone and allows users to enter user data, request products, receive product lists, and so on.

[0642] An "AI model" is an algorithm that uses artificial intelligence to analyze user data and generate personalized suggestions.

[0643] A "prompt" is text data input to a generative AI model, and is an instruction statement to obtain a specific output.

[0644] This invention utilizes AI to provide a personalized mobile sales service specifically for the elderly. The program to realize this system is configured as follows.

[0645] First, we will explain the user data collection part. The device (smartphone) collects data from the user, such as purchase history, health status, and food preferences. This data is sent to a server via a mobile application. For example, when a user enters their blood pressure value into the app, the data is saved on the server.

[0646] Next, we will explain data analysis and product list generation. The server analyzes the collected user data using AI algorithms (e.g., TensorFlow, PyTorch) and generates a personalized product list for each user. This product list includes foods and medicines that are optimal for the user's health condition and preferences. For example, the server may recommend low-salt foods to a user with high blood pressure.

[0647] Calculating the delivery route is also a very important factor. The server calculates the optimal delivery route based on the user's location data and real-time traffic information. This calculation uses route calculation algorithms such as Google Maps API. The optimal route information is sent to the navigation system of the mobile sales vehicle.

[0648] The system also accepts on-demand delivery requests. Users or care managers can submit requests for specific items through a smartphone application. The request is sent from the device to a server, which uses the information to add additional stops to the current delivery route.

[0649] The mobile sales vehicle also provides and delivers products. The mobile sales vehicle travels around according to the optimal route received from the server and provides products to users. When users receive products, social events are also held at the same time. For example, a mobile sales vehicle may visit a nursing home and hold a roundtable discussion or health seminar while delivering products.

[0650] Smartphone applications that suggest foods based on a user's health status are very useful. The application suggests optimal foods based on the user's health information when the user inputs it. For example, if the user inputs "I have high blood pressure. Can you recommend some low-salt foods?", the AI ​​model generates a response.

[0651] An example of a prompt for a generative AI model is:

[0652] "I have high blood pressure. Can you recommend some low-sodium foods?"

[0653] "I was recently diagnosed with diabetes. What foods are good for me?"

[0654] Examples include:

[0655] As described above, this invention provides a wide range of functions in one, including user data collection, data analysis using AI, calculation of optimal delivery routes, acceptance of on-demand requests, product provision, and hosting of social events. This allows seniors to easily obtain products that meet their individual needs, while also providing a venue for social interaction, improving their quality of life.

[0656] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0657] Step 1:

[0658] A user inputs data such as health information, food preferences, and past purchasing history into a smartphone application. This data is sent from the user's device (smartphone) to a server. Examples of input data include blood pressure, blood sugar levels, and favorite foods. The server receives this data and stores it in a database. At this stage, the input is the user's health information, preferences, and purchasing history, and the output is user data stored on the server.

[0659] Step 2:

[0660] The server performs data analysis using AI algorithms (e.g., TensorFlow, PyTorch) based on the stored user data. The data processing performed here generates a personalized product list based on the user's health condition and purchasing history. For example, this product list might suggest low-salt foods and blood pressure monitors to a user with high blood pressure. The input is the stored user data, and the output is a personalized product list.

[0661] Step 3:

[0662] The server then sends information for loading products onto the mobile sales vehicle based on the generated product list. This loading information contains detailed information about the products required by each user. For example, the server generates an inventory list of specific products based on the product list and sends it to the mobile sales vehicle management system. The input is the product list, and the output is the loading information.

[0663] Step 4:

[0664] The server optimizes the delivery routes of the mobile sales vehicles based on user data and real-time traffic information. This optimization uses route calculation algorithms such as Google Maps API. The data processing here involves calculating the most efficient route based on each user's location and real-time traffic information. The input is user location data and real-time traffic information, and the output is the optimized delivery route.

[0665] Step 5:

[0666] A user or care manager submits an on-demand request for a product through a smartphone application. This request is sent from the device to the server and added to the current delivery route. For example, the server responds by adding a new stop to the existing route. The input is the on-demand request, and the output is the updated delivery route.

[0667] Step 6:

[0668] The mobile food truck travels around according to the optimal delivery route received from the server. At each stop, the mobile food truck provides products to users and also holds social events. For example, when the mobile food truck visits a nursing home, it not only provides products but also holds mini-games and round-table discussions. The input is the optimal delivery route and product list, and the output is the delivered products and a place for positive social interaction.

[0669] Step 7:

[0670] A user uses a smartphone application to input a product request or question to the AI ​​model. For example, "I have high blood pressure. Can you recommend some low-salt foods?" The server runs the AI ​​model based on this prompt and provides appropriate products and information. The input is the user's prompt, and the output is the suggestions and information obtained from the AI ​​model.

[0671] 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.

[0672] This invention utilizes AI and an emotion engine to provide a personalized mobile sales service specifically for the elderly. Hereinafter, a specific embodiment of the invention will be described.

[0673] 1. Collection of User Data

[0674] server

[0675] The server collects data about the user's purchasing history, health status, and preferences, including information the user enters through the app, past shopping history, and results of regular checkups. Using a device, the user enters their health information and preferences into the application, which is then sent to the server.

[0676] Specific examples

[0677] User A enters his / her high blood pressure information and low-salt food purchase history into the app. The device sends the information to the server, which stores it in a database.

[0678] 2. Use of Emotion Engine

[0679] server

[0680] In addition to user data, the server uses an emotion engine to recognize the user's emotional state. For example, emotions can be read through facial recognition technology while the user is using the app. This emotion data is also stored in the database.

[0681] Specific examples

[0682] When User A uses the app, the emotion engine analyzes the user's facial expressions and recognizes that their current emotional state is happiness. This information is sent to the server and stored in the database.

[0683] 3. Analyze data and generate product list

[0684] server

[0685] Based on the collected user data and emotional data, the server uses AI algorithms to generate a personalized product list for each user, adjusting product selection and suggestions depending on the user's emotional state.

[0686] Specific examples

[0687] Based on the user A's high blood pressure information and the analysis results of the emotion engine, the server adds low-salt foods to the recommended product list, and further suggests special foods when the emotion is happy.

[0688] 4. Calculating delivery routes and notifying mobile sales vehicles

[0689] server

[0690] The server calculates the optimal delivery route based on the user's location data and real-time traffic information, and transmits this optimal route information to the mobile sales vehicle's terminal.

[0691] Specific examples

[0692] Based on the traffic information collected by the server, the most efficient route from the area where user A lives to the address of user B is calculated and sent to the navigation system of the mobile sales vehicle.

[0693] 5. Acceptance of On-Demand Delivery Requests

[0694] User

[0695] Users or care managers can submit on-demand requests for products through the app.

[0696] Terminal

[0697] The terminal sends these requests to the server.

[0698] server

[0699] The server accepts the request and adds it to the current delivery route.

[0700] Specific examples

[0701] User B suddenly needs a blood glucose test kit and sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[0702] 6. Supply and delivery of goods

[0703] Mobile sales vehicle

[0704] The mobile sales vehicle follows the optimal route received from the server and visits elderly people's homes and designated locations, providing products requested by users and recommended products.

[0705] Specific examples

[0706] The mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to the next destination, the home of user B, and delivers a blood glucose testing kit.

[0707] 7. Providing a platform for social interaction

[0708] Mobile sales vehicle

[0709] The mobile sales vans will serve as a place for seniors to interact with each other while delivering products, and will hold events such as mini-games and roundtable discussions at each stop to prevent social isolation.

[0710] Specific examples

[0711] Mobile sales trucks visit nursing homes and promote interaction between the elderly by holding mini-games and health seminars while delivering products.

[0712] summary

[0713] This invention utilizes AI and an emotion engine to provide personalized services tailored to the needs of elderly people and to provide a system that plans efficient delivery routes. By combining this with an emotion engine, it is possible to provide products and social interactions based on the user's emotional state, improving their quality of life.

[0714] The processing flow will be explained below.

[0715] Step 1:

[0716] Through the application, users input data about their purchasing history, health status, and preferences. For example, a user may input information about their high blood pressure or a preference for low-salt foods.

[0717] Step 2:

[0718] The terminal receives the data entered by the user and sends it to the server, which then sends it to the server in the appropriate format.

[0719] Step 3:

[0720] The server stores the received user data in a database, organizing information such as purchase history, health status, and preferences, and recording it in a specific format.

[0721] Step 4:

[0722] The server uses an emotion engine to collect data to recognize the user's emotional state. For example, while the user is using the app, facial recognition technology is used to analyze facial expressions and obtain emotional data in real time.

[0723] Step 5:

[0724] The device sends the emotion data acquired from the emotion engine to the server. The device then sends the facial recognition results and emotional state data to the server.

[0725] Step 6:

[0726] The server stores the emotion data in a database and integrates it with user data for analysis. For example, when a user shows happy emotions, it can enhance the recommendation of a specific product.

[0727] Step 7:

[0728] The server uses an AI algorithm to generate a personalized product list based on user data and emotional data. Product selection and recommendations are adjusted according to the user's emotional state.

[0729] Step 8:

[0730] The server stores the generated product list in a database and sends it to the mobile sales vehicle, which loads the products based on this information.

[0731] Step 9:

[0732] The server collects user location data and real-time traffic information and calculates the optimal delivery route.

[0733] Step 10:

[0734] The server calculates the optimal route and sends it to the mobile sales vehicle's terminal, which receives this information and sets the navigation according to the instructions.

[0735] Step 11:

[0736] A user or care manager sends an on-demand request through the app. For example, if User B urgently needs a blood glucose test kit, he or she sends this information as a request.

[0737] Step 12:

[0738] The terminal sends an on-demand request to the server.

[0739] Step 13:

[0740] The server accepts the on-demand request and recalculates and updates the current delivery route.

[0741] Step 14:

[0742] The server sends the recalculated route information to the mobile sales vehicle's terminal, which receives the information and moves along the new route.

[0743] Step 15:

[0744] The mobile sales vehicle travels according to the optimal route received from the server, visiting elderly people's homes and designated locations, and delivering the products loaded on it based on the user's personalized product list.

[0745] Step 16:

[0746] The mobile food truck arrives at its destination, offers products to users, and hosts social events at each stop, such as health seminars or mini-games.

[0747] Step 17:

[0748] Users receive the products and, if necessary, participate in events to interact with other elderly people.

[0749] Example 2

[0750] 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."

[0751] In mobile sales services for the elderly, conventional services have difficulty proposing products according to the user's health condition and individual preferences, and have not sufficiently improved convenience and satisfaction. Furthermore, while efficiency can be improved by calculating optimal delivery routes, providing a place for interaction to prevent social isolation among the elderly has not been fully realized.

[0752] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting user information including purchase history, health status, and preferences, means for generating a product list based on the collected user information and emotion data, means for loading products onto a mobile sales vehicle based on the generated product list, means for optimizing a delivery route of the mobile sales vehicle based on user location data and traffic information, means for accepting on-demand requests from users or care managers, means for delivering products to the user's home or a designated location based on the product list and the on-demand request, and means for the mobile sales vehicle to provide products to users at stops and hold social events on the spot. This enables personalized product provision and efficient delivery according to the individual needs of elderly people and prevents social isolation through interaction between elderly people.

[0753] "Purchase history" is a record of products purchased by a user in the past.

[0754] "Health Status" is information about a user's physical and mental health.

[0755] "Preferences" is information that indicates the user's personal tastes and selection tendencies.

[0756] "User Information" refers to all data about a user, including purchasing history, health status, and preferences.

[0757] "Emotion data" is information that indicates the emotional state of the user analyzed from facial expressions, voice, etc.

[0758] The "product list" is a list of products recommended to a user, generated based on user information and emotion data.

[0759] A "mobile sales vehicle" is a vehicle that transports merchandise along a set route and offers the merchandise at each stop.

[0760] A "delivery route" refers to the route taken by a mobile sales vehicle to deliver goods.

[0761] An "on-demand request" is a request from a user or care manager to provide a specific product.

[0762] A "stop" is a location where a mobile food truck temporarily stops to offer products and host events.

[0763] "Social events" refer to social activities such as mini-games and roundtable discussions that are offered to users by mobile food trucks at their stops.

[0764] An "AI algorithm" is a computational method that uses artificial intelligence to analyze data and identify patterns and trends.

[0765] "Real-time traffic information" is data for acquiring and analyzing current traffic conditions in real time.

[0766] This invention utilizes AI and an emotion engine to provide a personalized mobile sales service specifically for the elderly. Hereinafter, a specific embodiment of the invention will be described.

[0767] 1. Collection of User Data

[0768] server

[0769] The server collects data on the user's purchasing history, health status, and preferences. The collected data includes information entered by the user through the application, past purchase history, and results of regular checkups. This data is stored in a database and used for subsequent processing. The device used is a mobile device such as a smartphone or tablet, and the user enters the information using this device.

[0770] Specific examples

[0771] User A enters his / her high blood pressure information and low-salt food purchase history into the app. The device sends the information to the server, which stores it in a database.

[0772] 2. Use of Emotion Engine

[0773] server

[0774] In addition to user data, the server uses an emotion engine to recognize the user's emotional state. For example, while the user is using the app, the server captures their facial expressions using the device's camera and reads their emotions through facial recognition technology. This emotional data is also stored in the database.

[0775] Specific examples

[0776] When User A uses the app, the emotion engine analyzes the user's facial expressions and recognizes that their current emotional state is happiness. This information is sent to the server and stored in the database.

[0777] 3. Analyze data and generate product list

[0778] server

[0779] Based on the collected user data and emotional data, the server uses a generative AI model (AI algorithm) to generate a personalized product list for each user. Product selection and suggestions are adjusted according to the user's emotional state. In particular, the server creates a list of products that are optimal for each individual user based on attribute information such as health information and purchasing history.

[0780] Specific examples

[0781] Based on the user A's high blood pressure information and the analysis results of the emotion engine, the server adds low-salt foods to the recommended product list, and further suggests special foods when the emotion is happy.

[0782] 4. Calculating delivery routes and notifying mobile sales vehicles

[0783] server

[0784] The server uses the user's location data and real-time traffic information to calculate the optimal delivery route. This calculation uses a route optimization algorithm that takes road congestion into account. The optimal route information is then sent to the mobile sales vehicle's terminal.

[0785] Specific examples

[0786] Based on the traffic information collected by the server, the most efficient route from the area where user A lives to the address of user B is calculated and sent to the navigation system of the mobile sales vehicle.

[0787] 5. Acceptance of On-Demand Delivery Requests

[0788] User

[0789] Users or care managers submit on-demand product requests through the app, which include details of the product needed and a delivery address.

[0790] Terminal

[0791] The terminal sends these requests to the server.

[0792] server

[0793] The server accepts the request and adds the new destination to the current delivery route.

[0794] Specific examples

[0795] User B suddenly needs a blood glucose test kit and sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[0796] 6. Supply and delivery of goods

[0797] Mobile sales vehicle

[0798] The mobile sales vehicle will follow the optimal route received and visit the elderly person's home or designated location, providing the products requested by the user and recommended products.

[0799] Specific examples

[0800] The mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to the next destination, the home of user B, and delivers a blood glucose testing kit.

[0801] 7. Providing a platform for social interaction

[0802] Mobile sales vehicle

[0803] While providing products, the mobile food trucks also serve as a place for seniors to interact with each other, holding events such as mini-games and roundtable discussions at each stop to prevent social isolation.

[0804] Specific examples

[0805] Mobile sales trucks visit nursing homes and promote interaction between the elderly by holding mini-games and health seminars while delivering products.

[0806] Prompt Sentence Examples

[0807] Describe how the system works when a user enters new health information into the app.

[0808] summary

[0809] This invention is a system that utilizes AI and an emotion engine to provide personalized products and efficient delivery according to the needs of the elderly, and also promotes social interaction among the elderly, thereby improving the quality of life of users.

[0810] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0811] Step 1:

[0812] The user enters information into the app

[0813] User

[0814] Users open the application on their smartphone, tablet, or other device and enter information about their purchasing history, health status, and preferences. Data entered at this stage includes the user's medical history (e.g., high blood pressure), recent purchases (e.g., low-salt foods), and preferences (e.g., specific flavors or brands). The entered data is then stored on the device.

[0815] Input: User-entered purchasing history, health status, and preference information

[0816] Output: User information temporarily saved on the device

[0817] Specific actions

[0818] User A enters his or her high blood pressure information and low-salt food purchase history into the app.

[0819] Step 2:

[0820] The device sends the information to the server

[0821] Terminal

[0822] The terminal sends the information entered by the user to the server. This transmission process is done in real time using a communication protocol (e.g., HTTPS), and the data is encrypted before being sent. The server receives this information and adds it to a database as is.

[0823] Input: User information entered into the terminal

[0824] Output: User information sent to the server

[0825] Specific actions

[0826] User A's high blood pressure information and low-salt food purchase history are sent from the terminal to the server.

[0827] Step 3:

[0828] The server acquires emotion data

[0829] server

[0830] The server captures the user's facial expressions using the device's camera while the user is using the app and analyzes them with the emotion engine. The analyzed emotion data indicates the user's emotional state (e.g., happiness, sadness). The analysis results are sent to the server and stored in a database.

[0831] Input: Captured user facial expression data

[0832] Output: Parsed emotion data

[0833] Specific actions

[0834] When User A uses the app, the device camera captures User A's facial expression, and the emotion engine analyzes the emotion "happiness." The results are sent to the server.

[0835] Step 4:

[0836] The server analyzes the user data and generates a product list

[0837] server

[0838] The server uses an AI algorithm to generate a personalized product list based on the collected user data and emotional data. The AI ​​algorithm selects the most suitable products based on the user's health and emotional state and builds the list.

[0839] Input: User data and emotion data

[0840] Output: Personalized product list

[0841] Specific actions

[0842] The server adds low-salt foods to the recommended product list based on user A's high blood pressure information and the analysis results of the emotion engine, and also suggests special foods when the emotion is happy.

[0843] Step 5:

[0844] The server calculates the delivery route

[0845] server

[0846] The server integrates the user's location data and real-time traffic information to calculate the optimal delivery route, using a route optimization algorithm that takes into account factors such as road congestion, distance, and time. The calculated optimal route information is then sent to the mobile sales vehicle's terminal.

[0847] Input: User location data and real-time traffic information

[0848] Output: Optimal delivery route

[0849] Specific actions

[0850] The server calculates the optimal delivery route based on user A's address and current traffic conditions, and sends it to the navigation system of the mobile sales vehicle.

[0851] Step 6:

[0852] The server accepts the on-demand request and adds it to the route

[0853] server

[0854] When a user or care manager submits an on-demand request through the app, it is sent to the server, which accepts the request and adds a new delivery destination to the current delivery route.

[0855] Input: On-demand requests from users or care managers

[0856] Output: Updated delivery route

[0857] Specific actions

[0858] User B suddenly needs a blood glucose test kit and sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[0859] Step 7:

[0860] A mobile sales vehicle delivers goods along a route

[0861] Mobile sales vehicle

[0862] The mobile sales vehicle will follow the optimal route received and visit the elderly person's home or designated location, providing the products requested by the user and recommended products.

[0863] Input: Optimal delivery route and product list

[0864] Output: Item delivered to user

[0865] Specific actions

[0866] The mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to the next destination, the home of user B, and delivers a blood glucose testing kit.

[0867] Step 8:

[0868] Mobile food trucks provide a platform for social interaction

[0869] Mobile sales vehicle

[0870] While providing products, the mobile food trucks also serve as a place for seniors to interact with each other, holding events such as mini-games and roundtable discussions at each stop to prevent social isolation.

[0871] Input: Stops and Event Plan

[0872] Output: Social events held

[0873] Specific actions

[0874] Mobile sales trucks visit nursing homes and promote interaction between the elderly by holding mini-games and health seminars while delivering products.

[0875] (Application example 2)

[0876] 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."

[0877] Food delivery services for the elderly are required to simultaneously propose products based on not only the user's health status but also their emotional state, while improving delivery efficiency. It is also important to provide a place for social interaction and prevent isolation among the elderly. Current technology does not offer a system that comprehensively addresses these multiple factors, so a more effective system is needed to improve the quality of life for the elderly.

[0878] 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.

[0879] In this invention, the server includes means for collecting user data including purchase history, health status, and preferences, means for collecting the user's emotional state using emotion recognition technology, and means for generating a product list based on the collected user data and emotional state data. This makes it possible to generate a personalized product list based on the user's health status and emotional state, select an optimal delivery route, and provide appropriate products and services to elderly people. In addition, by having the mobile sales van deliver products to users at each stop and holding social events on the spot, it is possible to provide a place for social interaction among elderly people and prevent isolation.

[0880] "Purchase history" is a list of products purchased by the user in the past, along with detailed information about those products.

[0881] "Health status" refers to information related to the user's physical condition and medical care, such as blood pressure, blood sugar level, and allergy information.

[0882] "Preferences" are information about things that a user particularly likes or wants to avoid.

[0883] "Emotion recognition technology" is a technology that uses facial recognition, voice analysis, etc. to identify a user's emotional state.

[0884] "User Data" refers collectively to data including purchasing history, health status, preferences, and other personal information.

[0885] "Emotional state data" is data relating to the user's emotions obtained using emotion recognition technology.

[0886] The "product list" is a list of products to be recommended to the user, generated based on the user data and emotional state data.

[0887] A "mobile sales vehicle" is a vehicle that can stop at a designated location and provide products.

[0888] "Traffic information" refers to information related to traffic, such as road congestion and traffic regulations, that is collected in real time.

[0889] An "on-demand request" is a request to order a product made on the spot by a user or a care manager.

[0890] A "social interaction space" is a space or opportunity where users can interact and socialize with each other when providing products.

[0891] "Generative AI model" is a general term for artificial intelligence algorithms that generate product lists, etc. based on user data and emotional state data.

[0892] This invention is a system for providing a personalized food delivery service specifically for the elderly using AI and an emotion engine. The following describes in detail an embodiment of this invention.

[0893] The server first collects user data, including purchase history, health status, and preferences. This includes information entered by the user through a smartphone application, past purchase history, and regular checkup results. For example, User A enters his or her high blood pressure information and low-salt food purchase history into the app, and the data is sent to the server. The server stores this information in a database.

[0894] Next, the server uses emotion recognition technology to collect the user's emotional state. When a user uses a smartphone application, the camera scans their face and emotion recognition technology is used to read their emotions. This emotion data is also sent to the server and stored in a database. For example, user A's face is scanned while using an app, and the app recognizes that their emotion is happiness, and this information is sent to the server.

[0895] The server uses a generative AI model based on the collected user data and emotional state data to generate a personalized product list. This allows the server to suggest optimal products based on the user's health condition and current emotional state. For example, in the case of User A, based on information about high blood pressure and a feeling of happiness, it is possible to suggest low-salt foods as well as sweets as a special treat.

[0896] The server also calculates the optimal delivery route for the mobile sales vehicle based on user data and real-time traffic information. This optimal route information is sent to the sales vehicle's terminal. For example, the server calculates the shortest route from the area where user A lives to the address of user B, and sends this information to the navigation system of the mobile sales vehicle.

[0897] Additionally, users or care managers can send on-demand requests through the application. The device sends these requests to the server, which accepts the requests and adds them to the current delivery route. For example, User B suddenly needs a blood glucose test kit and sends a request through the application. This information is sent to the server, which adds User B's address to the existing route.

[0898] Finally, the mobile sales vehicle follows the optimal route received from the server and visits the elderly person's home or other designated locations, providing the products requested or recommended by the user. For example, the sales vehicle arrives at User A's home and provides low-salt food and a sweet treat, then heads to the next destination, User B's home, to deliver a blood glucose testing kit.

[0899] In this invention, the mobile sales van can provide products to users at the stops and also hold social events on the spot. This allows elderly people to interact with each other and deepen social interactions. As a specific example, the mobile sales van can visit a nursing home and hold mini-games and health seminars while providing products, thereby promoting interaction between elderly people.

[0900] An example prompt for a generative AI model is, "Design a system that allows elderly people to input their health and emotional state via a smartphone app, and then uses AI and an emotion engine to generate a personalized food list and delivery route."

[0901] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0902] Step 1:

[0903] User Data Collection

[0904] The device collects user data (purchase history, health status, and preferences). The user enters their information through a smartphone app, and the device sends the data to a server. The server stores this data in a database. For example, this data may include information about User A's high blood pressure and preference for low-salt foods.

[0905] Step 2:

[0906] Emotion recognition data collection

[0907] The device collects data on the user's emotional state. While the user is using a smartphone app, the camera scans the user's face and sends the image to emotion recognition technology. The emotion recognition technology analyzes the image and determines the user's emotional state. The results of this determination are sent from the device to a server and stored in a database. For example, if User A is recognized as having a happy emotion while using the app, that information is sent to the server.

[0908] Step 3:

[0909] Generate personalized product lists

[0910] Based on the user data and emotional state data collected by the server, a generative AI model is used to generate a personalized product list. Input data includes health status and emotional state, and specific products are selected based on that data. For example, in the case of User A, low-salt foods and treat sweets are included in the list because User A has high blood pressure and is in a state of happiness.

[0911] Step 4:

[0912] Calculating the optimal delivery route

[0913] The server calculates the optimal delivery route for the mobile sales truck based on user data and real-time traffic information. Inputs include each user's location and current traffic conditions. The server calculates this data and calculates the shortest and most efficient route. As a result, optimal route information from a specific user's address to the next user's address is generated and sent to the mobile sales truck's terminal.

[0914] Step 5:

[0915] Accepting on-demand requests

[0916] A user or care manager sends an on-demand request through a smartphone app. The device receives this request and sends it to the server. The server accepts the request and adds the address corresponding to the request to the existing delivery route. For example, User B suddenly needs a blood glucose test kit and sends a request from the app. The information is sent to the server, and User B's address is added to the delivery route.

[0917] Step 6:

[0918] Supply and delivery of goods

[0919] The mobile sales vehicle travels according to the optimal route received from the server, and delivers products to the user's home or a specified location. Specifically, the sales vehicle arrives at the home of user A and delivers low-salt foods and sweets. It then heads to the home of user B, its next destination, and delivers a blood glucose testing kit.

[0920] Step 7:

[0921] Providing a venue for social interaction

[0922] The mobile sales truck will deliver products to users at each stop and also hold social events on the spot. This allows users to interact with each other and deepen social interactions. For example, a mobile sales truck may visit a nursing home and hold mini-games and health seminars while delivering products, promoting interaction between the elderly.

[0923] 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.

[0924] 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.

[0925] 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.

[0926] [Third embodiment]

[0927] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0928] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0929] 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).

[0930] 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.

[0931] 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.

[0932] 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).

[0933] 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.

[0934] 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.

[0935] 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.

[0936] 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.

[0937] 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.

[0938] 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."

[0939] This invention utilizes AI to provide a personalized mobile sales service specifically for the elderly. Hereinafter, an embodiment of the invention will be described in detail.

[0940] 1. Collection of User Data

[0941] server

[0942] The server collects data about the user's purchasing history, health status, and preferences, including information the user enters through the app, past shopping history, and results of regular checkups. Using a device, the user enters their health information and preferences into the application, which is then sent to the server.

[0943] Specific examples

[0944] User A enters his / her high blood pressure information and low-salt food purchase history into the app. The device sends the information to the server, which stores it in a database.

[0945] 2. Analyze data and generate product list

[0946] server

[0947] Based on the collected user data, the server uses an AI algorithm to generate a personalized product list for each user, including medicines tailored to their health condition, foods tailored to their preferences, etc. The generated product list is stored in a database for each user.

[0948] Specific examples

[0949] Based on User A's high blood pressure information, the server adds low-salt foods and blood pressure monitors to the recommended product list.

[0950] 3. Calculating delivery routes and notifying mobile sales vehicles

[0951] server

[0952] The server calculates the optimal delivery route based on the user's location data and real-time traffic information, and sends this optimal route information to the mobile sales vehicle's terminal.

[0953] Specific examples

[0954] Based on the traffic information collected by the server, the most efficient route from the area where user A lives to the address of user B is calculated and sent to the navigation system of the mobile sales vehicle.

[0955] 4. Acceptance of On-Demand Delivery Requests

[0956] User

[0957] Users or care managers can submit on-demand requests for products through the app.

[0958] Terminal

[0959] The terminal sends these requests to the server.

[0960] server

[0961] The server accepts the request and adds it to the current delivery route.

[0962] Specific examples

[0963] User B suddenly needs a blood glucose test kit and sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[0964] 5. Supply and delivery of goods

[0965] Mobile sales vehicle

[0966] The mobile sales vehicle follows the optimal route received from the server and visits elderly people's homes and designated locations, providing products requested by users and recommended products.

[0967] Specific examples

[0968] The mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to the next destination, the home of user B, and delivers a blood glucose testing kit.

[0969] 6. Providing a platform for social interaction

[0970] Mobile sales vehicle

[0971] The mobile sales vans will serve as a place for seniors to interact with each other while delivering products, and will hold events such as mini-games and roundtable discussions at each stop to prevent social isolation.

[0972] Specific examples

[0973] Mobile sales trucks visit nursing homes and promote interaction between the elderly by holding mini-games and health seminars while delivering products.

[0974] summary

[0975] This invention utilizes AI to provide personalized services tailored to the needs of the elderly and provides a system that plans efficient delivery routes, allowing them to easily obtain daily necessities and medical products while providing opportunities for social interaction and improving their quality of life.

[0976] The processing flow will be explained below.

[0977] Step 1:

[0978] Through the application, users input data about their purchasing history, health status, and preferences. For example, a user may input information about their high blood pressure or a preference for low-salt foods.

[0979] Step 2:

[0980] The terminal receives the data entered by the user and transmits it to the server.

[0981] Step 3:

[0982] The server stores the received user data in a database, organizing information such as purchase history, health status, and preferences, and storing it in a specific format.

[0983] Step 4:

[0984] The server uses AI algorithms to analyze the stored user data and generate a personalized product list for each user, for example, recommending low-salt foods to a user with high blood pressure.

[0985] Step 5:

[0986] The server stores the generated product list in a database and transmits it to the mobile sales vehicle.

[0987] Step 6:

[0988] The server collects user location data and real-time traffic information, and uses this data to calculate the optimal delivery route using an AI algorithm.

[0989] Step 7:

[0990] The server then sends the calculated optimal route to the mobile sales vehicle's terminal, which receives this information and sets the route according to the instructions.

[0991] Step 8:

[0992] A user or care manager can send an on-demand request through the application. For example, if User B urgently needs a blood glucose test kit, he or she can send this information as a request.

[0993] Step 9:

[0994] The terminal sends an on-demand request to the server.

[0995] Step 10:

[0996] The server receives on-demand requests and recalculates and updates the current delivery route.

[0997] Step 11:

[0998] The server then sends the recalculated route information to the mobile sales vehicle's terminal, which receives the information and moves along the new route.

[0999] Step 12:

[1000] The mobile sales vehicle follows the optimal route received from the server, visits elderly people's homes and other designated locations, and delivers the products loaded on it based on the user's personalized product list.

[1001] Step 13:

[1002] The mobile food truck arrives at its destination, offers products to users, and hosts social events at each stop, such as health seminars or mini-games.

[1003] Step 14:

[1004] Users receive the products and, if necessary, participate in events to interact with other elderly people.

[1005] Example 1

[1006] 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."

[1007] Elderly people face challenges in easily obtaining daily necessities and medicines, and are prone to feeling socially isolated. Current mobile sales services often lack the ability to provide products tailored to the user's health condition and preferences, and delivery routes are often not optimized for efficiency. Furthermore, they lack a system capable of responding to on-demand requests, making it difficult to respond to sudden demand. To address these issues, it is necessary to provide personalized products specifically for the elderly, establish efficient delivery routes, and promote social interaction.

[1008] 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.

[1009] In this invention, the server includes means for collecting user data including purchase history, health status, and preferences, means for generating a product list based on the collected user data, means for loading products onto a mobile food truck based on the generated product list, means for optimizing a delivery route for the mobile food truck based on the user data and traffic information, means for receiving an on-demand request from a user or a care manager, means for delivering products to the user's home or a set location based on the product list and the on-demand request, means for the mobile food truck to provide products to the user at a stop and hold a social event on the spot, means for the mobile food truck to add on-demand delivery based on the user's request, means for generating a personalized product list using an AI algorithm, and means for calculating a delivery route based on real-time traffic information. This not only enables elderly people to easily obtain the products they need, but also enables the establishment of efficient delivery routes and promotion of social interactions.

[1010] "Purchase history" is data that records details of products and services purchased by a user in the past.

[1011] "Health Status" refers to information about a user's physical and mental health, including data based on medical records and self-reporting.

[1012] "Preferences" are data that indicate a user's tendency to prefer certain types of products or services.

[1013] "User Data" refers to information including purchasing history, health status, and preferences.

[1014] A "product list" is a list of recommended products and services generated for each user based on collected user data.

[1015] A "mobile sales vehicle" is a vehicle that operates to provide products and services to users.

[1016] "Delivery route" refers to the route taken by a mobile sales vehicle to deliver goods.

[1017] An "on-demand request" is a request made by a user or care manager for an urgently needed product or service.

[1018] An "AI algorithm" is a program that uses machine learning and artificial intelligence technology to analyze data and make predictions.

[1019] "Real-time traffic information" refers to data that provides real-time information on current traffic conditions and road congestion.

[1020] "Social networking events" refer to activities such as mini-games, roundtable discussions, and seminars that are planned to encourage social interaction among seniors.

[1021] This invention is a system that utilizes AI to provide a personalized mobile sales service specifically for the elderly. Specific embodiments for carrying out this invention will be described below.

[1022] First, the server collects user data, including purchase history, health status, and preferences. This includes information entered by the user through a dedicated application, past purchase history, and the results of regular checkups. The devices used are devices such as smartphones and tablets, and the data entered through these devices is sent to the server.

[1023] For example, user A enters his or her high blood pressure information and low-salt food purchase history into the app. The device then sends the information to the server, which then stores it in a database.

[1024] Next, the server uses an AI algorithm based on the collected user data to generate a personalized product list for each user. The AI ​​algorithm typically uses machine learning models such as TensorFlow or PyTorch. The generated product list is stored in a database for each user.

[1025] For example, the server adds low-salt foods and blood pressure monitors to the recommended product list based on User A's high blood pressure information. An AI algorithm then operates to generate the optimal product list.

[1026] The server then calculates the optimal delivery route based on the user's location data and real-time traffic information. This process uses map data and traffic information APIs such as Google Maps API. The calculation results are sent to the navigation system of the mobile sales vehicle.

[1027] As a specific example, based on traffic information collected by the server, the most efficient route from the area where user A lives to the address of user B is calculated and sent to the navigation system of the mobile sales vehicle.

[1028] Furthermore, the user or care manager can send an on-demand request for a product through a dedicated app. The device then sends this request to the server, which then updates the current delivery route based on the received request.

[1029] For example, if User B urgently needs a blood glucose test kit, he or she sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[1030] The mobile sales vehicle follows the optimal route received from the server and visits elderly people's homes and designated locations, providing products requested by users and products recommended by the server.

[1031] As a concrete example, a mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to its next destination, the home of user B, and delivers a blood glucose testing kit.

[1032] Furthermore, the mobile sales vans will function as a place for elderly people to interact with each other while delivering products, and events such as mini-games and roundtable discussions will be held at each stop to prevent social isolation.

[1033] As a concrete example, a mobile sales truck visits nursing homes and holds mini-games and health seminars while delivering products, thereby promoting interaction between the elderly.

[1034] In this way, the present invention provides a system that allows elderly people to easily obtain daily necessities and medical products by providing personalized services according to their needs and planning efficient delivery routes.

[1035] Prompt Sentence Examples

[1036] "Please explain in detail the algorithm that generates a recommended product list based on user A's high blood pressure information and calculates and notifies the user of a highly efficient delivery route."

[1037] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1038] Step 1: Collect user data

[1039] server

[1040] The server collects data about the user's purchasing history, health status, and preferences, including information entered by the user through the app, past shopping history, and the results of regular checkups. Specifically, the server receives the data sent by the client and stores it in a database.

[1041] Terminal

[1042] The device sends the health information and preferences that the user entered into the application to the server. Specifically, the user enters data into the app, and the device sends that information to the server.

[1043] Input: Health information, purchase history, and preferences entered by the user into the device

[1044] Output: User data stored in a server-side database

[1045] Step 2: Analyze the data and generate a product list

[1046] server

[1047] The server uses an AI algorithm to generate a product list based on the collected user data. This process uses machine learning models (e.g., TensorFlow or PyTorch) to analyze the data and select the most suitable products for each user. Specifically, the server inputs the user's health data, and the AI ​​algorithm generates a personalized product list based on that data.

[1048] Input: User health information, purchase history, and preferences stored in a database

[1049] Data processing: Analyze user data using AI algorithms

[1050] Output: A personalized product list saved to the database

[1051] Step 3: Calculate delivery route and notify the mobile sales vehicle

[1052] server

[1053] The server calculates the optimal delivery route based on the user's location data and real-time traffic information. This calculation uses map data and traffic information APIs (e.g., Google Maps API). Specifically, the server analyzes the real-time traffic information collected and notifies the navigation system of the optimal route for the mobile sales vehicle.

[1054] Input: User location data, real-time traffic information

[1055] Data processing: Calculate the optimal route using traffic information API

[1056] Output: Optimized delivery route information is sent to the mobile sales vehicle's navigation system

[1057] Step 4: Accepting an On-Demand Delivery Request

[1058] User

[1059] A user or care manager uses the app to submit an on-demand request for a product. Specifically, the user enters the request in the app and presses the submit button.

[1060] Terminal

[1061] The device sends the request to the server. Specifically, it transfers the request data sent from the app to the server.

[1062] server

[1063] The server receives the request and adds a new destination to the current delivery route. Specifically, the server analyzes the received request and updates and optimizes the delivery route.

[1064] Input: On-demand requests submitted by users

[1065] Data manipulation: Add a new delivery destination to the current delivery route

[1066] Output: Updated delivery route information

[1067] Step 5: Product delivery and delivery

[1068] Mobile sales vehicle

[1069] The mobile sales vehicle follows the optimal route received from the server, travels around the specified locations, and provides products to each user. Specifically, the mobile sales vehicle arrives at the destination and provides the requested products or products recommended by the server.

[1070] Input: Optimal route information and product list sent from the server

[1071] Output: The product is served to the user

[1072] Step 6: Providing social interaction

[1073] Mobile sales vehicle

[1074] The mobile sales vans will function as a place where elderly people can interact with each other while delivering products. Specifically, they will hold events such as mini-games, roundtable discussions, and health seminars at their stops to prevent social isolation.

[1075] Input: Event program

[1076] Output: A social event for seniors will be held.

[1077] These are the specific processing steps for a personalized mobile sales service that utilizes AI and is specifically targeted at the elderly. At each step, the server, terminals, and mobile sales vehicles work together to provide efficient and personalized services.

[1078] (Application example 1)

[1079] 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."

[1080] In modern society, the increasing elderly population has become a major social issue, particularly as it becomes more difficult for the elderly to easily obtain daily necessities and groceries. Furthermore, elderly people often require specific foods and medicines depending on their health condition, requiring personalized recommendations. Furthermore, opportunities for interaction to prevent social isolation are also important. However, existing services have difficulty efficiently and consistently meeting these needs. Therefore, the present invention provides a system to solve these problems.

[1081] 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.

[1082] In this invention, the server includes: means for collecting user data including purchase history, health status, and preferences; means for generating a product list based on the collected user data; means for loading products onto a mobile food truck based on the generated product list; means for optimizing a delivery route for the mobile food truck based on the user data and traffic information; means for receiving an on-demand request from a user or a care manager; means for delivering products to the user's home or a set location based on the product list and the on-demand request; means for the mobile food truck to provide products to the user at a stop and hold a social event on the spot; a smartphone application for suggesting foods based on the user's health status; a smartphone application for transmitting a request for products desired by the user; and means for making personalized product suggestions using an AI model. This allows elderly people to easily obtain products that meet their individual needs and also provides a forum for social interaction, improving their quality of life.

[1083] "Purchase history" is a list of products that a user has purchased in the past, which allows the user's preferences and consumption patterns to be understood.

[1084] "Health status" refers to information about the user's current physical health, and specifically includes data such as blood pressure, blood sugar level, and medical history.

[1085] "Preferences" refers to the personal preferences that a user has for specific foods or products, and are an element for providing personalized services based on these preferences.

[1086] "User Data" is a collective term for a set of information about a user, including purchasing history, health status, and preferences.

[1087] A "product list" is a list of products recommended to a user, generated based on collected user data.

[1088] A "mobile sales vehicle" is a vehicle that is loaded with merchandise and moves around to provide merchandise to users.

[1089] The "delivery route" refers to the route that the mobile sales vehicle follows to deliver goods to the user.

[1090] An "on-demand request" is a request that is sent immediately when a user or care manager needs a particular product or service.

[1091] A "smartphone application" is software that runs on a smartphone and allows users to enter user data, request products, receive product lists, and so on.

[1092] An "AI model" is an algorithm that uses artificial intelligence to analyze user data and generate personalized suggestions.

[1093] A "prompt" is text data input to a generative AI model, and is an instruction statement to obtain a specific output.

[1094] This invention utilizes AI to provide a personalized mobile sales service specifically for the elderly. The program to realize this system is configured as follows.

[1095] First, we will explain the user data collection part. The device (smartphone) collects data from the user, such as purchase history, health status, and food preferences. This data is sent to a server via a mobile application. For example, when a user enters their blood pressure value into the app, the data is saved on the server.

[1096] Next, we will explain data analysis and product list generation. The server analyzes the collected user data using AI algorithms (e.g., TensorFlow, PyTorch) and generates a personalized product list for each user. This product list includes foods and medicines that are optimal for the user's health condition and preferences. For example, the server may recommend low-salt foods to a user with high blood pressure.

[1097] Calculating the delivery route is also a very important factor. The server calculates the optimal delivery route based on the user's location data and real-time traffic information. This calculation uses route calculation algorithms such as Google Maps API. The optimal route information is sent to the navigation system of the mobile sales vehicle.

[1098] The system also accepts on-demand delivery requests. Users or care managers can submit requests for specific items through a smartphone application. The request is sent from the device to a server, which uses the information to add additional stops to the current delivery route.

[1099] The mobile sales vehicle also provides and delivers products. The mobile sales vehicle travels around according to the optimal route received from the server and provides products to users. When users receive products, social events are also held at the same time. For example, a mobile sales vehicle may visit a nursing home and hold a roundtable discussion or health seminar while delivering products.

[1100] Smartphone applications that suggest foods based on a user's health status are very useful. The application suggests optimal foods based on the user's health information when the user inputs it. For example, if the user inputs "I have high blood pressure. Can you recommend some low-salt foods?", the AI ​​model generates a response.

[1101] An example of a prompt for a generative AI model is:

[1102] "I have high blood pressure. Can you recommend some low-sodium foods?"

[1103] "I was recently diagnosed with diabetes. What foods are good for me?"

[1104] Examples include:

[1105] As described above, this invention provides a wide range of functions in one, including user data collection, data analysis using AI, calculation of optimal delivery routes, acceptance of on-demand requests, product provision, and hosting of social events. This allows seniors to easily obtain products that meet their individual needs, while also providing a venue for social interaction, improving their quality of life.

[1106] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1107] Step 1:

[1108] A user inputs data such as health information, food preferences, and past purchasing history into a smartphone application. This data is sent from the user's device (smartphone) to a server. Examples of input data include blood pressure, blood sugar levels, and favorite foods. The server receives this data and stores it in a database. At this stage, the input is the user's health information, preferences, and purchasing history, and the output is user data stored on the server.

[1109] Step 2:

[1110] The server performs data analysis using AI algorithms (e.g., TensorFlow, PyTorch) based on the stored user data. The data processing performed here generates a personalized product list based on the user's health condition and purchasing history. For example, this product list might suggest low-salt foods and blood pressure monitors to a user with high blood pressure. The input is the stored user data, and the output is a personalized product list.

[1111] Step 3:

[1112] The server then sends information for loading products onto the mobile sales vehicle based on the generated product list. This loading information contains detailed information about the products required by each user. For example, the server generates an inventory list of specific products based on the product list and sends it to the mobile sales vehicle management system. The input is the product list, and the output is the loading information.

[1113] Step 4:

[1114] The server optimizes the delivery routes of the mobile sales vehicles based on user data and real-time traffic information. This optimization uses route calculation algorithms such as Google Maps API. The data processing here involves calculating the most efficient route based on each user's location and real-time traffic information. The input is user location data and real-time traffic information, and the output is the optimized delivery route.

[1115] Step 5:

[1116] A user or care manager submits an on-demand request for a product through a smartphone application. This request is sent from the device to the server and added to the current delivery route. For example, the server responds by adding a new stop to the existing route. The input is the on-demand request, and the output is the updated delivery route.

[1117] Step 6:

[1118] The mobile food truck travels around according to the optimal delivery route received from the server. At each stop, the mobile food truck provides products to users and also holds social events. For example, when the mobile food truck visits a nursing home, it not only provides products but also holds mini-games and round-table discussions. The input is the optimal delivery route and product list, and the output is the delivered products and a place for positive social interaction.

[1119] Step 7:

[1120] A user uses a smartphone application to input a product request or question to the AI ​​model. For example, "I have high blood pressure. Can you recommend some low-salt foods?" The server runs the AI ​​model based on this prompt and provides appropriate products and information. The input is the user's prompt, and the output is the suggestions and information obtained from the AI ​​model.

[1121] 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.

[1122] This invention utilizes AI and an emotion engine to provide a personalized mobile sales service specifically for the elderly. Hereinafter, a specific embodiment of the invention will be described.

[1123] 1. Collection of User Data

[1124] server

[1125] The server collects data about the user's purchasing history, health status, and preferences, including information the user enters through the app, past shopping history, and results of regular checkups. Using a device, the user enters their health information and preferences into the application, which is then sent to the server.

[1126] Specific examples

[1127] User A enters his / her high blood pressure information and low-salt food purchase history into the app. The device sends the information to the server, which stores it in a database.

[1128] 2. Use of Emotion Engine

[1129] server

[1130] In addition to user data, the server uses an emotion engine to recognize the user's emotional state. For example, emotions can be read through facial recognition technology while the user is using the app. This emotion data is also stored in the database.

[1131] Specific examples

[1132] When User A uses the app, the emotion engine analyzes the user's facial expressions and recognizes that their current emotional state is happiness. This information is sent to the server and stored in the database.

[1133] 3. Analyze data and generate product list

[1134] server

[1135] Based on the collected user data and emotional data, the server uses AI algorithms to generate a personalized product list for each user, adjusting product selection and suggestions depending on the user's emotional state.

[1136] Specific examples

[1137] Based on the user A's high blood pressure information and the analysis results of the emotion engine, the server adds low-salt foods to the recommended product list, and further suggests special foods when the emotion is happy.

[1138] 4. Calculating delivery routes and notifying mobile sales vehicles

[1139] server

[1140] The server calculates the optimal delivery route based on the user's location data and real-time traffic information, and transmits this optimal route information to the mobile sales vehicle's terminal.

[1141] Specific examples

[1142] Based on the traffic information collected by the server, the most efficient route from the area where user A lives to the address of user B is calculated and sent to the navigation system of the mobile sales vehicle.

[1143] 5. Acceptance of On-Demand Delivery Requests

[1144] User

[1145] Users or care managers can submit on-demand requests for products through the app.

[1146] Terminal

[1147] The terminal sends these requests to the server.

[1148] server

[1149] The server accepts the request and adds it to the current delivery route.

[1150] Specific examples

[1151] User B suddenly needs a blood glucose test kit and sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[1152] 6. Supply and delivery of goods

[1153] Mobile sales vehicle

[1154] The mobile sales vehicle follows the optimal route received from the server and visits elderly people's homes and designated locations, providing products requested by users and recommended products.

[1155] Specific examples

[1156] The mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to the next destination, the home of user B, and delivers a blood glucose testing kit.

[1157] 7. Providing a platform for social interaction

[1158] Mobile sales vehicle

[1159] The mobile sales vans will serve as a place for seniors to interact with each other while delivering products, and will hold events such as mini-games and roundtable discussions at each stop to prevent social isolation.

[1160] Specific examples

[1161] Mobile sales trucks visit nursing homes and promote interaction between the elderly by holding mini-games and health seminars while delivering products.

[1162] summary

[1163] This invention utilizes AI and an emotion engine to provide personalized services tailored to the needs of elderly people and to provide a system that plans efficient delivery routes. By combining this with an emotion engine, it is possible to provide products and social interactions based on the user's emotional state, improving their quality of life.

[1164] The processing flow will be explained below.

[1165] Step 1:

[1166] Through the application, users input data about their purchasing history, health status, and preferences. For example, a user may input information about their high blood pressure or a preference for low-salt foods.

[1167] Step 2:

[1168] The terminal receives the data entered by the user and sends it to the server, which then sends it to the server in the appropriate format.

[1169] Step 3:

[1170] The server stores the received user data in a database, organizing information such as purchase history, health status, and preferences, and recording it in a specific format.

[1171] Step 4:

[1172] The server uses an emotion engine to collect data to recognize the user's emotional state. For example, while the user is using the app, facial recognition technology is used to analyze facial expressions and obtain emotional data in real time.

[1173] Step 5:

[1174] The device sends the emotion data acquired from the emotion engine to the server. The device then sends the facial recognition results and emotional state data to the server.

[1175] Step 6:

[1176] The server stores the emotion data in a database and integrates it with user data for analysis. For example, when a user shows happy emotions, it can enhance the recommendation of a specific product.

[1177] Step 7:

[1178] The server uses an AI algorithm to generate a personalized product list based on user data and emotional data. Product selection and recommendations are adjusted according to the user's emotional state.

[1179] Step 8:

[1180] The server stores the generated product list in a database and sends it to the mobile sales vehicle, which loads the products based on this information.

[1181] Step 9:

[1182] The server collects user location data and real-time traffic information and calculates the optimal delivery route.

[1183] Step 10:

[1184] The server calculates the optimal route and sends it to the mobile sales vehicle's terminal, which receives this information and sets the navigation according to the instructions.

[1185] Step 11:

[1186] A user or care manager sends an on-demand request through the app. For example, if User B urgently needs a blood glucose test kit, he or she sends this information as a request.

[1187] Step 12:

[1188] The terminal sends an on-demand request to the server.

[1189] Step 13:

[1190] The server accepts the on-demand request and recalculates and updates the current delivery route.

[1191] Step 14:

[1192] The server sends the recalculated route information to the mobile sales vehicle's terminal, which receives the information and moves along the new route.

[1193] Step 15:

[1194] The mobile sales vehicle travels according to the optimal route received from the server, visiting elderly people's homes and designated locations, and delivering the products loaded on it based on the user's personalized product list.

[1195] Step 16:

[1196] The mobile food truck arrives at its destination, offers products to users, and hosts social events at each stop, such as health seminars or mini-games.

[1197] Step 17:

[1198] Users receive the products and, if necessary, participate in events to interact with other elderly people.

[1199] Example 2

[1200] 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."

[1201] In mobile sales services for the elderly, conventional services have difficulty proposing products according to the user's health condition and individual preferences, and have not sufficiently improved convenience and satisfaction. Furthermore, while efficiency can be improved by calculating optimal delivery routes, providing a place for interaction to prevent social isolation among the elderly has not been fully realized.

[1202] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting user information including purchase history, health status, and preferences, means for generating a product list based on the collected user information and emotion data, means for loading products onto a mobile sales vehicle based on the generated product list, means for optimizing a delivery route of the mobile sales vehicle based on user location data and traffic information, means for accepting on-demand requests from users or care managers, means for delivering products to the user's home or a designated location based on the product list and the on-demand request, and means for the mobile sales vehicle to provide products to users at stops and hold social events on the spot. This enables personalized product provision and efficient delivery according to the individual needs of elderly people and prevents social isolation through interaction between elderly people.

[1203] "Purchase history" is a record of products purchased by a user in the past.

[1204] "Health Status" is information about a user's physical and mental health.

[1205] "Preferences" is information that indicates the user's personal tastes and selection tendencies.

[1206] "User Information" refers to all data about a user, including purchasing history, health status, and preferences.

[1207] "Emotion data" is information that indicates the emotional state of the user analyzed from facial expressions, voice, etc.

[1208] The "product list" is a list of products recommended to a user, generated based on user information and emotion data.

[1209] A "mobile sales vehicle" is a vehicle that transports merchandise along a set route and offers the merchandise at each stop.

[1210] A "delivery route" refers to the route taken by a mobile sales vehicle to deliver goods.

[1211] An "on-demand request" is a request from a user or care manager to provide a specific product.

[1212] A "stop" is a location where a mobile food truck temporarily stops to offer products and host events.

[1213] "Social events" refer to social activities such as mini-games and roundtable discussions that are offered to users by mobile food trucks at their stops.

[1214] An "AI algorithm" is a computational method that uses artificial intelligence to analyze data and identify patterns and trends.

[1215] "Real-time traffic information" is data for acquiring and analyzing current traffic conditions in real time.

[1216] This invention utilizes AI and an emotion engine to provide a personalized mobile sales service specifically for the elderly. Hereinafter, a specific embodiment of the invention will be described.

[1217] 1. Collection of User Data

[1218] server

[1219] The server collects data on the user's purchasing history, health status, and preferences. The collected data includes information entered by the user through the application, past purchase history, and results of regular checkups. This data is stored in a database and used for subsequent processing. The device used is a mobile device such as a smartphone or tablet, and the user enters the information using this device.

[1220] Specific examples

[1221] User A enters his / her high blood pressure information and low-salt food purchase history into the app. The device sends the information to the server, which stores it in a database.

[1222] 2. Use of Emotion Engine

[1223] server

[1224] In addition to user data, the server uses an emotion engine to recognize the user's emotional state. For example, while the user is using the app, the server captures their facial expressions using the device's camera and reads their emotions through facial recognition technology. This emotional data is also stored in the database.

[1225] Specific examples

[1226] When User A uses the app, the emotion engine analyzes the user's facial expressions and recognizes that their current emotional state is happiness. This information is sent to the server and stored in the database.

[1227] 3. Analyze data and generate product list

[1228] server

[1229] Based on the collected user data and emotional data, the server uses a generative AI model (AI algorithm) to generate a personalized product list for each user. Product selection and suggestions are adjusted according to the user's emotional state. In particular, the server creates a list of products that are optimal for each individual user based on attribute information such as health information and purchasing history.

[1230] Specific examples

[1231] Based on the user A's high blood pressure information and the analysis results of the emotion engine, the server adds low-salt foods to the recommended product list, and further suggests special foods when the emotion is happy.

[1232] 4. Calculating delivery routes and notifying mobile sales vehicles

[1233] server

[1234] The server uses the user's location data and real-time traffic information to calculate the optimal delivery route. This calculation uses a route optimization algorithm that takes road congestion into account. The optimal route information is then sent to the mobile sales vehicle's terminal.

[1235] Specific examples

[1236] Based on the traffic information collected by the server, the most efficient route from the area where user A lives to the address of user B is calculated and sent to the navigation system of the mobile sales vehicle.

[1237] 5. Acceptance of On-Demand Delivery Requests

[1238] User

[1239] Users or care managers submit on-demand product requests through the app, which include details of the product needed and a delivery address.

[1240] Terminal

[1241] The terminal sends these requests to the server.

[1242] server

[1243] The server accepts the request and adds the new destination to the current delivery route.

[1244] Specific examples

[1245] User B suddenly needs a blood glucose test kit and sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[1246] 6. Supply and delivery of goods

[1247] Mobile sales vehicle

[1248] The mobile sales vehicle will follow the optimal route received and visit the elderly person's home or designated location, providing the products requested by the user and recommended products.

[1249] Specific examples

[1250] The mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to the next destination, the home of user B, and delivers a blood glucose testing kit.

[1251] 7. Providing a platform for social interaction

[1252] Mobile sales vehicle

[1253] While providing products, the mobile food trucks also serve as a place for seniors to interact with each other, holding events such as mini-games and roundtable discussions at each stop to prevent social isolation.

[1254] Specific examples

[1255] Mobile sales trucks visit nursing homes and promote interaction between the elderly by holding mini-games and health seminars while delivering products.

[1256] Prompt Sentence Examples

[1257] Describe how the system works when a user enters new health information into the app.

[1258] summary

[1259] This invention is a system that utilizes AI and an emotion engine to provide personalized products and efficient delivery according to the needs of the elderly, and also promotes social interaction among the elderly, thereby improving the quality of life of users.

[1260] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1261] Step 1:

[1262] The user enters information into the app

[1263] User

[1264] Users open the application on their smartphone, tablet, or other device and enter information about their purchasing history, health status, and preferences. Data entered at this stage includes the user's medical history (e.g., high blood pressure), recent purchases (e.g., low-salt foods), and preferences (e.g., specific flavors or brands). The entered data is then stored on the device.

[1265] Input: User-entered purchasing history, health status, and preference information

[1266] Output: User information temporarily saved on the device

[1267] Specific actions

[1268] User A enters his or her high blood pressure information and low-salt food purchase history into the app.

[1269] Step 2:

[1270] The device sends the information to the server

[1271] Terminal

[1272] The terminal sends the information entered by the user to the server. This transmission process is done in real time using a communication protocol (e.g., HTTPS), and the data is encrypted before being sent. The server receives this information and adds it to a database as is.

[1273] Input: User information entered into the terminal

[1274] Output: User information sent to the server

[1275] Specific actions

[1276] User A's high blood pressure information and low-salt food purchase history are sent from the terminal to the server.

[1277] Step 3:

[1278] The server acquires emotion data

[1279] server

[1280] The server captures the user's facial expressions using the device's camera while the user is using the app and analyzes them with the emotion engine. The analyzed emotion data indicates the user's emotional state (e.g., happiness, sadness). The analysis results are sent to the server and stored in a database.

[1281] Input: Captured user facial expression data

[1282] Output: Parsed emotion data

[1283] Specific actions

[1284] When User A uses the app, the device camera captures User A's facial expression, and the emotion engine analyzes the emotion "happiness." The results are sent to the server.

[1285] Step 4:

[1286] The server analyzes the user data and generates a product list

[1287] server

[1288] The server uses an AI algorithm to generate a personalized product list based on the collected user data and emotional data. The AI ​​algorithm selects the most suitable products based on the user's health and emotional state and builds the list.

[1289] Input: User data and emotion data

[1290] Output: Personalized product list

[1291] Specific actions

[1292] The server adds low-salt foods to the recommended product list based on user A's high blood pressure information and the analysis results of the emotion engine, and also suggests special foods when the emotion is happy.

[1293] Step 5:

[1294] The server calculates the delivery route

[1295] server

[1296] The server integrates the user's location data and real-time traffic information to calculate the optimal delivery route, using a route optimization algorithm that takes into account factors such as road congestion, distance, and time. The calculated optimal route information is then sent to the mobile sales vehicle's terminal.

[1297] Input: User location data and real-time traffic information

[1298] Output: Optimal delivery route

[1299] Specific actions

[1300] The server calculates the optimal delivery route based on user A's address and current traffic conditions, and sends it to the navigation system of the mobile sales vehicle.

[1301] Step 6:

[1302] The server accepts the on-demand request and adds it to the route

[1303] server

[1304] When a user or care manager submits an on-demand request through the app, it is sent to the server, which accepts the request and adds a new delivery destination to the current delivery route.

[1305] Input: On-demand requests from users or care managers

[1306] Output: Updated delivery route

[1307] Specific actions

[1308] User B suddenly needs a blood glucose test kit and sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[1309] Step 7:

[1310] A mobile sales vehicle delivers goods along a route

[1311] Mobile sales vehicle

[1312] The mobile sales vehicle will follow the optimal route received and visit the elderly person's home or designated location, providing the products requested by the user and recommended products.

[1313] Input: Optimal delivery route and product list

[1314] Output: Item delivered to user

[1315] Specific actions

[1316] The mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to the next destination, the home of user B, and delivers a blood glucose testing kit.

[1317] Step 8:

[1318] Mobile food trucks provide a platform for social interaction

[1319] Mobile sales vehicle

[1320] While providing products, the mobile food trucks also serve as a place for seniors to interact with each other, holding events such as mini-games and roundtable discussions at each stop to prevent social isolation.

[1321] Input: Stops and Event Plan

[1322] Output: Social events held

[1323] Specific actions

[1324] Mobile sales trucks visit nursing homes and promote interaction between the elderly by holding mini-games and health seminars while delivering products.

[1325] (Application example 2)

[1326] 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."

[1327] Food delivery services for the elderly are required to simultaneously propose products based on not only the user's health status but also their emotional state, while improving delivery efficiency. It is also important to provide a place for social interaction and prevent isolation among the elderly. Current technology does not offer a system that comprehensively addresses these multiple factors, so a more effective system is needed to improve the quality of life for the elderly.

[1328] 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.

[1329] In this invention, the server includes means for collecting user data including purchase history, health status, and preferences, means for collecting the user's emotional state using emotion recognition technology, and means for generating a product list based on the collected user data and emotional state data. This makes it possible to generate a personalized product list based on the user's health status and emotional state, select an optimal delivery route, and provide appropriate products and services to elderly people. In addition, by having the mobile sales van deliver products to users at each stop and holding social events on the spot, it is possible to provide a place for social interaction among elderly people and prevent isolation.

[1330] "Purchase history" is a list of products purchased by the user in the past, along with detailed information about those products.

[1331] "Health status" refers to information related to the user's physical condition and medical care, such as blood pressure, blood sugar level, and allergy information.

[1332] "Preferences" are information about things that a user particularly likes or wants to avoid.

[1333] "Emotion recognition technology" is a technology that uses facial recognition, voice analysis, etc. to identify a user's emotional state.

[1334] "User Data" refers collectively to data including purchasing history, health status, preferences, and other personal information.

[1335] "Emotional state data" is data relating to the user's emotions obtained using emotion recognition technology.

[1336] The "product list" is a list of products to be recommended to the user, generated based on the user data and emotional state data.

[1337] A "mobile sales vehicle" is a vehicle that can stop at a designated location and provide products.

[1338] "Traffic information" refers to information related to traffic, such as road congestion and traffic regulations, that is collected in real time.

[1339] An "on-demand request" is a request to order a product made on the spot by a user or a care manager.

[1340] A "social interaction space" is a space or opportunity where users can interact and socialize with each other when providing products.

[1341] "Generative AI model" is a general term for artificial intelligence algorithms that generate product lists, etc. based on user data and emotional state data.

[1342] This invention is a system for providing a personalized food delivery service specifically for the elderly using AI and an emotion engine. The following describes in detail an embodiment of this invention.

[1343] The server first collects user data, including purchase history, health status, and preferences. This includes information entered by the user through a smartphone application, past purchase history, and regular checkup results. For example, User A enters his or her high blood pressure information and low-salt food purchase history into the app, and the data is sent to the server. The server stores this information in a database.

[1344] Next, the server uses emotion recognition technology to collect the user's emotional state. When a user uses a smartphone application, the camera scans their face and emotion recognition technology is used to read their emotions. This emotion data is also sent to the server and stored in a database. For example, user A's face is scanned while using an app, and the app recognizes that their emotion is happiness, and this information is sent to the server.

[1345] The server uses a generative AI model based on the collected user data and emotional state data to generate a personalized product list. This allows the server to suggest optimal products based on the user's health condition and current emotional state. For example, in the case of User A, based on information about high blood pressure and a feeling of happiness, it is possible to suggest low-salt foods as well as sweets as a special treat.

[1346] The server also calculates the optimal delivery route for the mobile sales vehicle based on user data and real-time traffic information. This optimal route information is sent to the sales vehicle's terminal. For example, the server calculates the shortest route from the area where user A lives to the address of user B, and sends this information to the navigation system of the mobile sales vehicle.

[1347] Additionally, users or care managers can send on-demand requests through the application. The device sends these requests to the server, which accepts the requests and adds them to the current delivery route. For example, User B suddenly needs a blood glucose test kit and sends a request through the application. This information is sent to the server, which adds User B's address to the existing route.

[1348] Finally, the mobile sales vehicle follows the optimal route received from the server and visits the elderly person's home or other designated locations, providing the products requested or recommended by the user. For example, the sales vehicle arrives at User A's home and provides low-salt food and a sweet treat, then heads to the next destination, User B's home, to deliver a blood glucose testing kit.

[1349] In this invention, the mobile sales van can provide products to users at the stops and also hold social events on the spot. This allows elderly people to interact with each other and deepen social interactions. As a specific example, the mobile sales van can visit a nursing home and hold mini-games and health seminars while providing products, thereby promoting interaction between elderly people.

[1350] An example prompt for a generative AI model is, "Design a system that allows elderly people to input their health and emotional state via a smartphone app, and then uses AI and an emotion engine to generate a personalized food list and delivery route."

[1351] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1352] Step 1:

[1353] User Data Collection

[1354] The device collects user data (purchase history, health status, and preferences). The user enters their information through a smartphone app, and the device sends the data to a server. The server stores this data in a database. For example, this data may include information about User A's high blood pressure and preference for low-salt foods.

[1355] Step 2:

[1356] Emotion recognition data collection

[1357] The device collects data on the user's emotional state. While the user is using a smartphone app, the camera scans the user's face and sends the image to emotion recognition technology. The emotion recognition technology analyzes the image and determines the user's emotional state. The results of this determination are sent from the device to a server and stored in a database. For example, if User A is recognized as having a happy emotion while using the app, that information is sent to the server.

[1358] Step 3:

[1359] Generate personalized product lists

[1360] Based on the user data and emotional state data collected by the server, a generative AI model is used to generate a personalized product list. Input data includes health status and emotional state, and specific products are selected based on that data. For example, in the case of User A, low-salt foods and treat sweets are included in the list because User A has high blood pressure and is in a state of happiness.

[1361] Step 4:

[1362] Calculating the optimal delivery route

[1363] The server calculates the optimal delivery route for the mobile sales truck based on user data and real-time traffic information. Inputs include each user's location and current traffic conditions. The server calculates this data and calculates the shortest and most efficient route. As a result, optimal route information from a specific user's address to the next user's address is generated and sent to the mobile sales truck's terminal.

[1364] Step 5:

[1365] Accepting on-demand requests

[1366] A user or care manager sends an on-demand request through a smartphone app. The device receives this request and sends it to the server. The server accepts the request and adds the address corresponding to the request to the existing delivery route. For example, User B suddenly needs a blood glucose test kit and sends a request from the app. The information is sent to the server, and User B's address is added to the delivery route.

[1367] Step 6:

[1368] Supply and delivery of goods

[1369] The mobile sales vehicle travels according to the optimal route received from the server, and delivers products to the user's home or a specified location. Specifically, the sales vehicle arrives at the home of user A and delivers low-salt foods and sweets. It then heads to the home of user B, its next destination, and delivers a blood glucose testing kit.

[1370] Step 7:

[1371] Providing a venue for social interaction

[1372] The mobile sales truck will deliver products to users at each stop and also hold social events on the spot. This allows users to interact with each other and deepen social interactions. For example, a mobile sales truck may visit a nursing home and hold mini-games and health seminars while delivering products, promoting interaction between the elderly.

[1373] 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.

[1374] 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.

[1375] 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.

[1376] [Fourth embodiment]

[1377] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1378] 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.

[1379] 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).

[1380] 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.

[1381] 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.

[1382] 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).

[1383] 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.

[1384] 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.

[1385] 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.

[1386] 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.

[1387] 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.

[1388] 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.

[1389] 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."

[1390] This invention utilizes AI to provide a personalized mobile sales service specifically for the elderly. Hereinafter, an embodiment of the invention will be described in detail.

[1391] 1. Collection of User Data

[1392] server

[1393] The server collects data about the user's purchasing history, health status, and preferences, including information the user enters through the app, past shopping history, and results of regular checkups. Using a device, the user enters their health information and preferences into the application, which is then sent to the server.

[1394] Specific examples

[1395] User A enters his / her high blood pressure information and low-salt food purchase history into the app. The device sends the information to the server, which stores it in a database.

[1396] 2. Analyze data and generate product list

[1397] server

[1398] Based on the collected user data, the server uses an AI algorithm to generate a personalized product list for each user, including medicines tailored to their health condition, foods tailored to their preferences, etc. The generated product list is stored in a database for each user.

[1399] Specific examples

[1400] Based on User A's high blood pressure information, the server adds low-salt foods and blood pressure monitors to the recommended product list.

[1401] 3. Calculating delivery routes and notifying mobile sales vehicles

[1402] server

[1403] The server calculates the optimal delivery route based on the user's location data and real-time traffic information, and sends this optimal route information to the mobile sales vehicle's terminal.

[1404] Specific examples

[1405] Based on the traffic information collected by the server, the most efficient route from the area where user A lives to the address of user B is calculated and sent to the navigation system of the mobile sales vehicle.

[1406] 4. Acceptance of On-Demand Delivery Requests

[1407] User

[1408] Users or care managers can submit on-demand requests for products through the app.

[1409] Terminal

[1410] The terminal sends these requests to the server.

[1411] server

[1412] The server accepts the request and adds it to the current delivery route.

[1413] Specific examples

[1414] User B suddenly needs a blood glucose test kit and sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[1415] 5. Supply and delivery of goods

[1416] Mobile sales vehicle

[1417] The mobile sales vehicle follows the optimal route received from the server and visits elderly people's homes and designated locations, providing products requested by users and recommended products.

[1418] Specific examples

[1419] The mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to the next destination, the home of user B, and delivers a blood glucose testing kit.

[1420] 6. Providing a platform for social interaction

[1421] Mobile sales vehicle

[1422] The mobile sales vans will serve as a place for seniors to interact with each other while delivering products, and will hold events such as mini-games and roundtable discussions at each stop to prevent social isolation.

[1423] Specific examples

[1424] Mobile sales trucks visit nursing homes and promote interaction between the elderly by holding mini-games and health seminars while delivering products.

[1425] summary

[1426] This invention utilizes AI to provide personalized services tailored to the needs of the elderly and provides a system that plans efficient delivery routes, allowing them to easily obtain daily necessities and medical products while providing opportunities for social interaction and improving their quality of life.

[1427] The processing flow will be explained below.

[1428] Step 1:

[1429] Through the application, users input data about their purchasing history, health status, and preferences. For example, a user may input information about their high blood pressure or a preference for low-salt foods.

[1430] Step 2:

[1431] The terminal receives the data entered by the user and transmits it to the server.

[1432] Step 3:

[1433] The server stores the received user data in a database, organizing information such as purchase history, health status, and preferences, and storing it in a specific format.

[1434] Step 4:

[1435] The server uses AI algorithms to analyze the stored user data and generate a personalized product list for each user, for example, recommending low-salt foods to a user with high blood pressure.

[1436] Step 5:

[1437] The server stores the generated product list in a database and transmits it to the mobile sales vehicle.

[1438] Step 6:

[1439] The server collects user location data and real-time traffic information, and uses this data to calculate the optimal delivery route using an AI algorithm.

[1440] Step 7:

[1441] The server then sends the calculated optimal route to the mobile sales vehicle's terminal, which receives this information and sets the route according to the instructions.

[1442] Step 8:

[1443] A user or care manager can send an on-demand request through the application. For example, if User B urgently needs a blood glucose test kit, he or she can send this information as a request.

[1444] Step 9:

[1445] The terminal sends an on-demand request to the server.

[1446] Step 10:

[1447] The server receives on-demand requests and recalculates and updates the current delivery route.

[1448] Step 11:

[1449] The server then sends the recalculated route information to the mobile sales vehicle's terminal, which receives the information and moves along the new route.

[1450] Step 12:

[1451] The mobile sales vehicle follows the optimal route received from the server, visits elderly people's homes and other designated locations, and delivers the products loaded on it based on the user's personalized product list.

[1452] Step 13:

[1453] The mobile food truck arrives at its destination, offers products to users, and hosts social events at each stop, such as health seminars or mini-games.

[1454] Step 14:

[1455] Users receive the products and, if necessary, participate in events to interact with other elderly people.

[1456] Example 1

[1457] 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."

[1458] Elderly people face challenges in easily obtaining daily necessities and medicines, and are prone to feeling socially isolated. Current mobile sales services often lack the ability to provide products tailored to the user's health condition and preferences, and delivery routes are often not optimized for efficiency. Furthermore, they lack a system capable of responding to on-demand requests, making it difficult to respond to sudden demand. To address these issues, it is necessary to provide personalized products specifically for the elderly, establish efficient delivery routes, and promote social interaction.

[1459] 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.

[1460] In this invention, the server includes means for collecting user data including purchase history, health status, and preferences, means for generating a product list based on the collected user data, means for loading products onto a mobile food truck based on the generated product list, means for optimizing a delivery route for the mobile food truck based on the user data and traffic information, means for receiving an on-demand request from a user or a care manager, means for delivering products to the user's home or a set location based on the product list and the on-demand request, means for the mobile food truck to provide products to the user at a stop and hold a social event on the spot, means for the mobile food truck to add on-demand delivery based on the user's request, means for generating a personalized product list using an AI algorithm, and means for calculating a delivery route based on real-time traffic information. This not only enables elderly people to easily obtain the products they need, but also enables the establishment of efficient delivery routes and promotion of social interactions.

[1461] "Purchase history" is data that records details of products and services purchased by a user in the past.

[1462] "Health Status" refers to information about a user's physical and mental health, including data based on medical records and self-reporting.

[1463] "Preferences" are data that indicate a user's tendency to prefer certain types of products or services.

[1464] "User Data" refers to information including purchasing history, health status, and preferences.

[1465] A "product list" is a list of recommended products and services generated for each user based on collected user data.

[1466] A "mobile sales vehicle" is a vehicle that operates to provide products and services to users.

[1467] "Delivery route" refers to the route taken by a mobile sales vehicle to deliver goods.

[1468] An "on-demand request" is a request made by a user or care manager for an urgently needed product or service.

[1469] An "AI algorithm" is a program that uses machine learning and artificial intelligence technology to analyze data and make predictions.

[1470] "Real-time traffic information" refers to data that provides real-time information on current traffic conditions and road congestion.

[1471] "Social networking events" refer to activities such as mini-games, roundtable discussions, and seminars that are planned to encourage social interaction among seniors.

[1472] This invention is a system that utilizes AI to provide a personalized mobile sales service specifically for the elderly. Specific embodiments for carrying out this invention will be described below.

[1473] First, the server collects user data, including purchase history, health status, and preferences. This includes information entered by the user through a dedicated application, past purchase history, and the results of regular checkups. The devices used are devices such as smartphones and tablets, and the data entered through these devices is sent to the server.

[1474] For example, user A enters his or her high blood pressure information and low-salt food purchase history into the app. The device then sends the information to the server, which then stores it in a database.

[1475] Next, the server uses an AI algorithm based on the collected user data to generate a personalized product list for each user. The AI ​​algorithm typically uses machine learning models such as TensorFlow or PyTorch. The generated product list is stored in a database for each user.

[1476] For example, the server adds low-salt foods and blood pressure monitors to the recommended product list based on User A's high blood pressure information. An AI algorithm then operates to generate the optimal product list.

[1477] The server then calculates the optimal delivery route based on the user's location data and real-time traffic information. This process uses map data and traffic information APIs such as Google Maps API. The calculation results are sent to the navigation system of the mobile sales vehicle.

[1478] As a specific example, based on traffic information collected by the server, the most efficient route from the area where user A lives to the address of user B is calculated and sent to the navigation system of the mobile sales vehicle.

[1479] Furthermore, the user or care manager can send an on-demand request for a product through a dedicated app. The device then sends this request to the server, which then updates the current delivery route based on the received request.

[1480] For example, if User B urgently needs a blood glucose test kit, he or she sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[1481] The mobile sales vehicle follows the optimal route received from the server and visits elderly people's homes and designated locations, providing products requested by users and products recommended by the server.

[1482] As a concrete example, a mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to its next destination, the home of user B, and delivers a blood glucose testing kit.

[1483] Furthermore, the mobile sales vans will function as a place for elderly people to interact with each other while delivering products, and events such as mini-games and roundtable discussions will be held at each stop to prevent social isolation.

[1484] As a concrete example, a mobile sales truck visits nursing homes and holds mini-games and health seminars while delivering products, thereby promoting interaction between the elderly.

[1485] In this way, the present invention provides a system that allows elderly people to easily obtain daily necessities and medical products by providing personalized services according to their needs and planning efficient delivery routes.

[1486] Prompt Sentence Examples

[1487] "Please explain in detail the algorithm that generates a recommended product list based on user A's high blood pressure information and calculates and notifies the user of a highly efficient delivery route."

[1488] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1489] Step 1: Collect user data

[1490] server

[1491] The server collects data about the user's purchasing history, health status, and preferences, including information entered by the user through the app, past shopping history, and the results of regular checkups. Specifically, the server receives the data sent by the client and stores it in a database.

[1492] Terminal

[1493] The device sends the health information and preferences that the user entered into the application to the server. Specifically, the user enters data into the app, and the device sends that information to the server.

[1494] Input: Health information, purchase history, and preferences entered by the user into the device

[1495] Output: User data stored in a server-side database

[1496] Step 2: Analyze the data and generate a product list

[1497] server

[1498] The server uses an AI algorithm to generate a product list based on the collected user data. This process uses machine learning models (e.g., TensorFlow or PyTorch) to analyze the data and select the most suitable products for each user. Specifically, the server inputs the user's health data, and the AI ​​algorithm generates a personalized product list based on that data.

[1499] Input: User health information, purchase history, and preferences stored in a database

[1500] Data processing: Analyze user data using AI algorithms

[1501] Output: A personalized product list saved to the database

[1502] Step 3: Calculate delivery route and notify the mobile sales vehicle

[1503] server

[1504] The server calculates the optimal delivery route based on the user's location data and real-time traffic information. This calculation uses map data and traffic information APIs (e.g., Google Maps API). Specifically, the server analyzes the real-time traffic information collected and notifies the navigation system of the optimal route for the mobile sales vehicle.

[1505] Input: User location data, real-time traffic information

[1506] Data processing: Calculate the optimal route using traffic information API

[1507] Output: Optimized delivery route information is sent to the mobile sales vehicle's navigation system

[1508] Step 4: Accepting an On-Demand Delivery Request

[1509] User

[1510] A user or care manager uses the app to submit an on-demand request for a product. Specifically, the user enters the request in the app and presses the submit button.

[1511] Terminal

[1512] The device sends the request to the server. Specifically, it transfers the request data sent from the app to the server.

[1513] server

[1514] The server receives the request and adds a new destination to the current delivery route. Specifically, the server analyzes the received request and updates and optimizes the delivery route.

[1515] Input: On-demand requests submitted by users

[1516] Data manipulation: Add a new delivery destination to the current delivery route

[1517] Output: Updated delivery route information

[1518] Step 5: Product delivery and delivery

[1519] Mobile sales vehicle

[1520] The mobile sales vehicle follows the optimal route received from the server, travels around the specified locations, and provides products to each user. Specifically, the mobile sales vehicle arrives at the destination and provides the requested products or products recommended by the server.

[1521] Input: Optimal route information and product list sent from the server

[1522] Output: The product is served to the user

[1523] Step 6: Providing social interaction

[1524] Mobile sales vehicle

[1525] The mobile sales vans will function as a place where elderly people can interact with each other while delivering products. Specifically, they will hold events such as mini-games, roundtable discussions, and health seminars at their stops to prevent social isolation.

[1526] Input: Event program

[1527] Output: A social event for seniors will be held.

[1528] These are the specific processing steps for a personalized mobile sales service that utilizes AI and is specifically targeted at the elderly. At each step, the server, terminals, and mobile sales vehicles work together to provide efficient and personalized services.

[1529] (Application example 1)

[1530] 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."

[1531] In modern society, the increasing elderly population has become a major social issue, particularly as it becomes more difficult for the elderly to easily obtain daily necessities and groceries. Furthermore, elderly people often require specific foods and medicines depending on their health condition, requiring personalized recommendations. Furthermore, opportunities for interaction to prevent social isolation are also important. However, existing services have difficulty efficiently and consistently meeting these needs. Therefore, the present invention provides a system to solve these problems.

[1532] 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.

[1533] In this invention, the server includes: means for collecting user data including purchase history, health status, and preferences; means for generating a product list based on the collected user data; means for loading products onto a mobile food truck based on the generated product list; means for optimizing a delivery route for the mobile food truck based on the user data and traffic information; means for receiving an on-demand request from a user or a care manager; means for delivering products to the user's home or a set location based on the product list and the on-demand request; means for the mobile food truck to provide products to the user at a stop and hold a social event on the spot; a smartphone application for suggesting foods based on the user's health status; a smartphone application for transmitting a request for products desired by the user; and means for making personalized product suggestions using an AI model. This allows elderly people to easily obtain products that meet their individual needs and also provides a forum for social interaction, improving their quality of life.

[1534] "Purchase history" is a list of products that a user has purchased in the past, which allows the user's preferences and consumption patterns to be understood.

[1535] "Health status" refers to information about the user's current physical health, and specifically includes data such as blood pressure, blood sugar level, and medical history.

[1536] "Preferences" refers to the personal preferences that a user has for specific foods or products, and are an element for providing personalized services based on these preferences.

[1537] "User Data" is a collective term for a set of information about a user, including purchasing history, health status, and preferences.

[1538] A "product list" is a list of products recommended to a user, generated based on collected user data.

[1539] A "mobile sales vehicle" is a vehicle that is loaded with merchandise and moves around to provide merchandise to users.

[1540] The "delivery route" refers to the route that the mobile sales vehicle follows to deliver goods to the user.

[1541] An "on-demand request" is a request that is sent immediately when a user or care manager needs a particular product or service.

[1542] A "smartphone application" is software that runs on a smartphone and allows users to enter user data, request products, receive product lists, and so on.

[1543] An "AI model" is an algorithm that uses artificial intelligence to analyze user data and generate personalized suggestions.

[1544] A "prompt" is text data input to a generative AI model, and is an instruction statement to obtain a specific output.

[1545] This invention utilizes AI to provide a personalized mobile sales service specifically for the elderly. The program to realize this system is configured as follows.

[1546] First, we will explain the user data collection part. The device (smartphone) collects data from the user, such as purchase history, health status, and food preferences. This data is sent to a server via a mobile application. For example, when a user enters their blood pressure value into the app, the data is saved on the server.

[1547] Next, we will explain data analysis and product list generation. The server analyzes the collected user data using AI algorithms (e.g., TensorFlow, PyTorch) and generates a personalized product list for each user. This product list includes foods and medicines that are optimal for the user's health condition and preferences. For example, the server may recommend low-salt foods to a user with high blood pressure.

[1548] Calculating the delivery route is also a very important factor. The server calculates the optimal delivery route based on the user's location data and real-time traffic information. This calculation uses route calculation algorithms such as Google Maps API. The optimal route information is sent to the navigation system of the mobile sales vehicle.

[1549] The system also accepts on-demand delivery requests. Users or care managers can submit requests for specific items through a smartphone application. The request is sent from the device to a server, which uses the information to add additional stops to the current delivery route.

[1550] The mobile sales vehicle also provides and delivers products. The mobile sales vehicle travels around according to the optimal route received from the server and provides products to users. When users receive products, social events are also held at the same time. For example, a mobile sales vehicle may visit a nursing home and hold a roundtable discussion or health seminar while delivering products.

[1551] Smartphone applications that suggest foods based on a user's health status are very useful. The application suggests optimal foods based on the user's health information when the user inputs it. For example, if the user inputs "I have high blood pressure. Can you recommend some low-salt foods?", the AI ​​model generates a response.

[1552] An example of a prompt for a generative AI model is:

[1553] "I have high blood pressure. Can you recommend some low-sodium foods?"

[1554] "I was recently diagnosed with diabetes. What foods are good for me?"

[1555] Examples include:

[1556] As described above, this invention provides a wide range of functions in one, including user data collection, data analysis using AI, calculation of optimal delivery routes, acceptance of on-demand requests, product provision, and hosting of social events. This allows seniors to easily obtain products that meet their individual needs, while also providing a venue for social interaction, improving their quality of life.

[1557] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1558] Step 1:

[1559] A user inputs data such as health information, food preferences, and past purchasing history into a smartphone application. This data is sent from the user's device (smartphone) to a server. Examples of input data include blood pressure, blood sugar levels, and favorite foods. The server receives this data and stores it in a database. At this stage, the input is the user's health information, preferences, and purchasing history, and the output is user data stored on the server.

[1560] Step 2:

[1561] The server performs data analysis using AI algorithms (e.g., TensorFlow, PyTorch) based on the stored user data. The data processing performed here generates a personalized product list based on the user's health condition and purchasing history. For example, this product list might suggest low-salt foods and blood pressure monitors to a user with high blood pressure. The input is the stored user data, and the output is a personalized product list.

[1562] Step 3:

[1563] The server then sends information for loading products onto the mobile sales vehicle based on the generated product list. This loading information contains detailed information about the products required by each user. For example, the server generates an inventory list of specific products based on the product list and sends it to the mobile sales vehicle management system. The input is the product list, and the output is the loading information.

[1564] Step 4:

[1565] The server optimizes the delivery routes of the mobile sales vehicles based on user data and real-time traffic information. This optimization uses route calculation algorithms such as Google Maps API. The data processing here involves calculating the most efficient route based on each user's location and real-time traffic information. The input is user location data and real-time traffic information, and the output is the optimized delivery route.

[1566] Step 5:

[1567] A user or care manager submits an on-demand request for a product through a smartphone application. This request is sent from the device to the server and added to the current delivery route. For example, the server responds by adding a new stop to the existing route. The input is the on-demand request, and the output is the updated delivery route.

[1568] Step 6:

[1569] The mobile food truck travels around according to the optimal delivery route received from the server. At each stop, the mobile food truck provides products to users and also holds social events. For example, when the mobile food truck visits a nursing home, it not only provides products but also holds mini-games and round-table discussions. The input is the optimal delivery route and product list, and the output is the delivered products and a place for positive social interaction.

[1570] Step 7:

[1571] A user uses a smartphone application to input a product request or question to the AI ​​model. For example, "I have high blood pressure. Can you recommend some low-salt foods?" The server runs the AI ​​model based on this prompt and provides appropriate products and information. The input is the user's prompt, and the output is the suggestions and information obtained from the AI ​​model.

[1572] 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.

[1573] This invention utilizes AI and an emotion engine to provide a personalized mobile sales service specifically for the elderly. Hereinafter, a specific embodiment of the invention will be described.

[1574] 1. Collection of User Data

[1575] server

[1576] The server collects data about the user's purchasing history, health status, and preferences, including information the user enters through the app, past shopping history, and results of regular checkups. Using a device, the user enters their health information and preferences into the application, which is then sent to the server.

[1577] Specific examples

[1578] User A enters his / her high blood pressure information and low-salt food purchase history into the app. The device sends the information to the server, which stores it in a database.

[1579] 2. Use of Emotion Engine

[1580] server

[1581] In addition to user data, the server uses an emotion engine to recognize the user's emotional state. For example, emotions can be read through facial recognition technology while the user is using the app. This emotion data is also stored in the database.

[1582] Specific examples

[1583] When User A uses the app, the emotion engine analyzes the user's facial expressions and recognizes that their current emotional state is happiness. This information is sent to the server and stored in the database.

[1584] 3. Analyze data and generate product list

[1585] server

[1586] Based on the collected user data and emotional data, the server uses an AI algorithm to generate a personalized product list for each user, adjusting product selection and suggestions depending on the user's emotional state.

[1587] Specific examples

[1588] Based on the user A's high blood pressure information and the analysis results of the emotion engine, the server adds low-salt foods to the recommended product list, and further suggests special foods when the emotion is happy.

[1589] 4. Calculating delivery routes and notifying mobile sales vehicles

[1590] server

[1591] The server calculates the optimal delivery route based on the user's location data and real-time traffic information, and transmits this optimal route information to the mobile sales vehicle's terminal.

[1592] Specific examples

[1593] Based on the traffic information collected by the server, the most efficient route from the area where user A lives to the address of user B is calculated and sent to the navigation system of the mobile sales vehicle.

[1594] 5. Acceptance of On-Demand Delivery Requests

[1595] User

[1596] Users or care managers can submit on-demand requests for products through the app.

[1597] Terminal

[1598] The terminal sends these requests to the server.

[1599] server

[1600] The server accepts the request and adds it to the current delivery route.

[1601] Specific examples

[1602] User B suddenly needs a blood glucose test kit and sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[1603] 6. Supply and delivery of goods

[1604] Mobile sales vehicle

[1605] The mobile sales vehicle follows the optimal route received from the server and visits elderly people's homes and designated locations, providing products requested by users and recommended products.

[1606] Specific examples

[1607] The mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to the next destination, the home of user B, and delivers a blood glucose testing kit.

[1608] 7. Providing a platform for social interaction

[1609] Mobile sales vehicle

[1610] The mobile sales vans will serve as a place for seniors to interact with each other while delivering products, and will hold events such as mini-games and roundtable discussions at each stop to prevent social isolation.

[1611] Specific examples

[1612] Mobile sales trucks visit nursing homes and promote interaction between the elderly by holding mini-games and health seminars while delivering products.

[1613] summary

[1614] This invention utilizes AI and an emotion engine to provide personalized services tailored to the needs of elderly people and to provide a system that plans efficient delivery routes. By combining this with an emotion engine, it is possible to provide products and social interactions based on the user's emotional state, improving their quality of life.

[1615] The processing flow will be explained below.

[1616] Step 1:

[1617] Through the application, users input data about their purchasing history, health status, and preferences. For example, a user may input information about their high blood pressure or a preference for low-salt foods.

[1618] Step 2:

[1619] The terminal receives the data entered by the user and sends it to the server, which then sends it to the server in the appropriate format.

[1620] Step 3:

[1621] The server stores the received user data in a database, organizing information such as purchase history, health status, and preferences, and recording it in a specific format.

[1622] Step 4:

[1623] The server uses an emotion engine to collect data to recognize the user's emotional state. For example, while the user is using the app, facial recognition technology is used to analyze facial expressions and obtain emotional data in real time.

[1624] Step 5:

[1625] The device sends the emotion data acquired from the emotion engine to the server. The device then sends the facial recognition results and emotional state data to the server.

[1626] Step 6:

[1627] The server stores the emotion data in a database and integrates it with user data for analysis. For example, when a user shows happy emotions, it can enhance the recommendation of a specific product.

[1628] Step 7:

[1629] The server uses an AI algorithm to generate a personalized product list based on user data and emotional data. Product selection and recommendations are adjusted according to the user's emotional state.

[1630] Step 8:

[1631] The server stores the generated product list in a database and sends it to the mobile sales vehicle, which loads the products based on this information.

[1632] Step 9:

[1633] The server collects user location data and real-time traffic information and calculates the optimal delivery route.

[1634] Step 10:

[1635] The server calculates the optimal route and sends it to the mobile sales vehicle's terminal, which receives this information and sets the navigation according to the instructions.

[1636] Step 11:

[1637] A user or care manager sends an on-demand request through the app. For example, if User B urgently needs a blood glucose test kit, he or she sends this information as a request.

[1638] Step 12:

[1639] The terminal sends an on-demand request to the server.

[1640] Step 13:

[1641] The server accepts the on-demand request and recalculates and updates the current delivery route.

[1642] Step 14:

[1643] The server sends the recalculated route information to the mobile sales vehicle's terminal, which receives the information and moves along the new route.

[1644] Step 15:

[1645] The mobile sales vehicle travels according to the optimal route received from the server, visiting elderly people's homes and designated locations, and delivering the products loaded on it based on the user's personalized product list.

[1646] Step 16:

[1647] The mobile food truck arrives at its destination, offers products to users, and hosts social events at each stop, such as health seminars or mini-games.

[1648] Step 17:

[1649] Users receive the products and, if necessary, participate in events to interact with other elderly people.

[1650] Example 2

[1651] 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."

[1652] In mobile sales services for the elderly, conventional services have difficulty proposing products according to the user's health condition and individual preferences, and have not sufficiently improved convenience and satisfaction. Furthermore, while efficiency can be improved by calculating optimal delivery routes, providing a place for interaction to prevent social isolation among the elderly has not been fully realized.

[1653] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting user information including purchase history, health status, and preferences, means for generating a product list based on the collected user information and emotion data, means for loading products onto a mobile sales vehicle based on the generated product list, means for optimizing a delivery route of the mobile sales vehicle based on user location data and traffic information, means for accepting on-demand requests from users or care managers, means for delivering products to the user's home or a designated location based on the product list and the on-demand request, and means for the mobile sales vehicle to provide products to users at stops and hold social events on the spot. This enables personalized product provision and efficient delivery according to the individual needs of elderly people and prevents social isolation through interaction between elderly people.

[1654] "Purchase history" is a record of products purchased by a user in the past.

[1655] "Health Status" is information about a user's physical and mental health.

[1656] "Preferences" is information that indicates the user's personal tastes and selection tendencies.

[1657] "User Information" refers to all data about a user, including purchasing history, health status, and preferences.

[1658] "Emotion data" is information that indicates the emotional state of the user analyzed from facial expressions, voice, etc.

[1659] The "product list" is a list of products recommended to a user, generated based on user information and emotion data.

[1660] A "mobile sales vehicle" is a vehicle that transports merchandise along a set route and offers the merchandise at each stop.

[1661] A "delivery route" refers to the route taken by a mobile sales vehicle to deliver goods.

[1662] An "on-demand request" is a request from a user or care manager to provide a specific product.

[1663] A "stop" is a location where a mobile food truck temporarily stops to offer products and host events.

[1664] "Social events" refer to social activities such as mini-games and roundtable discussions that are offered to users by mobile food trucks at their stops.

[1665] An "AI algorithm" is a computational method that uses artificial intelligence to analyze data and identify patterns and trends.

[1666] "Real-time traffic information" is data for acquiring and analyzing current traffic conditions in real time.

[1667] This invention utilizes AI and an emotion engine to provide a personalized mobile sales service specifically for the elderly. Hereinafter, a specific embodiment of the invention will be described.

[1668] 1. Collection of User Data

[1669] server

[1670] The server collects data on the user's purchasing history, health status, and preferences. The collected data includes information entered by the user through the application, past purchase history, and results of regular checkups. This data is stored in a database and used for subsequent processing. The device used is a mobile device such as a smartphone or tablet, and the user enters the information using this device.

[1671] Specific examples

[1672] User A enters his / her high blood pressure information and low-salt food purchase history into the app. The device sends the information to the server, which stores it in a database.

[1673] 2. Use of Emotion Engine

[1674] server

[1675] In addition to user data, the server uses an emotion engine to recognize the user's emotional state. For example, while the user is using the app, the server captures their facial expressions using the device's camera and reads their emotions through facial recognition technology. This emotional data is also stored in the database.

[1676] Specific examples

[1677] When User A uses the app, the emotion engine analyzes the user's facial expressions and recognizes that their current emotional state is happiness. This information is sent to the server and stored in the database.

[1678] 3. Analyze data and generate product list

[1679] server

[1680] Based on the collected user data and emotional data, the server uses a generative AI model (AI algorithm) to generate a personalized product list for each user. Product selection and suggestions are adjusted according to the user's emotional state. In particular, the server creates a list of products that are optimal for each individual user based on attribute information such as health information and purchasing history.

[1681] Specific examples

[1682] Based on the user A's high blood pressure information and the analysis results of the emotion engine, the server adds low-salt foods to the recommended product list, and further suggests special foods when the emotion is happy.

[1683] 4. Calculating delivery routes and notifying mobile sales vehicles

[1684] server

[1685] The server uses the user's location data and real-time traffic information to calculate the optimal delivery route. This calculation uses a route optimization algorithm that takes road congestion into account. The optimal route information is then sent to the mobile sales vehicle's terminal.

[1686] Specific examples

[1687] Based on the traffic information collected by the server, the most efficient route from the area where user A lives to the address of user B is calculated and sent to the navigation system of the mobile sales vehicle.

[1688] 5. Acceptance of On-Demand Delivery Requests

[1689] User

[1690] Users or care managers submit on-demand product requests through the app, which include details of the product needed and a delivery address.

[1691] Terminal

[1692] The terminal sends these requests to the server.

[1693] server

[1694] The server accepts the request and adds the new destination to the current delivery route.

[1695] Specific examples

[1696] User B suddenly needs a blood glucose test kit and sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[1697] 6. Supply and delivery of goods

[1698] Mobile sales vehicle

[1699] The mobile sales vehicle will follow the optimal route received and visit the elderly person's home or designated location, providing the products requested by the user and recommended products.

[1700] Specific examples

[1701] The mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to the next destination, the home of user B, and delivers a blood glucose testing kit.

[1702] 7. Providing a platform for social interaction

[1703] Mobile sales vehicle

[1704] While providing products, the mobile food trucks also serve as a place for seniors to interact with each other, holding events such as mini-games and roundtable discussions at each stop to prevent social isolation.

[1705] Specific examples

[1706] Mobile sales trucks visit nursing homes and promote interaction between the elderly by holding mini-games and health seminars while delivering products.

[1707] Prompt Sentence Examples

[1708] Describe how the system works when a user enters new health information into the app.

[1709] summary

[1710] This invention is a system that utilizes AI and an emotion engine to provide personalized products and efficient delivery according to the needs of the elderly, and also promotes social interaction among the elderly, thereby improving the quality of life of users.

[1711] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1712] Step 1:

[1713] The user enters information into the app

[1714] User

[1715] Users open the application on their smartphone, tablet, or other device and enter information about their purchasing history, health status, and preferences. Data entered at this stage includes the user's medical history (e.g., high blood pressure), recent purchases (e.g., low-salt foods), and preferences (e.g., specific flavors or brands). The entered data is then stored on the device.

[1716] Input: User-entered purchasing history, health status, and preference information

[1717] Output: User information temporarily saved on the device

[1718] Specific actions

[1719] User A enters his or her high blood pressure information and low-salt food purchase history into the app.

[1720] Step 2:

[1721] The device sends the information to the server

[1722] Terminal

[1723] The terminal sends the information entered by the user to the server. This transmission process is done in real time using a communication protocol (e.g., HTTPS), and the data is encrypted before being sent. The server receives this information and adds it to a database as is.

[1724] Input: User information entered into the terminal

[1725] Output: User information sent to the server

[1726] Specific actions

[1727] User A's high blood pressure information and low-salt food purchase history are sent from the terminal to the server.

[1728] Step 3:

[1729] The server acquires emotion data

[1730] server

[1731] The server captures the user's facial expressions using the device's camera while the user is using the app and analyzes them with the emotion engine. The analyzed emotion data indicates the user's emotional state (e.g., happiness, sadness). The analysis results are sent to the server and stored in a database.

[1732] Input: Captured user facial expression data

[1733] Output: Parsed emotion data

[1734] Specific actions

[1735] When User A uses the app, the device camera captures User A's facial expression, and the emotion engine analyzes the emotion "happiness." The results are sent to the server.

[1736] Step 4:

[1737] The server analyzes the user data and generates a product list

[1738] server

[1739] The server uses an AI algorithm to generate a personalized product list based on the collected user data and emotional data. The AI ​​algorithm selects the most suitable products based on the user's health and emotional state and builds the list.

[1740] Input: User data and emotion data

[1741] Output: Personalized product list

[1742] Specific actions

[1743] The server adds low-salt foods to the recommended product list based on user A's high blood pressure information and the analysis results of the emotion engine, and also suggests special foods when the emotion is happy.

[1744] Step 5:

[1745] The server calculates the delivery route

[1746] server

[1747] The server integrates the user's location data and real-time traffic information to calculate the optimal delivery route, using a route optimization algorithm that takes into account factors such as road congestion, distance, and time. The calculated optimal route information is then sent to the mobile sales vehicle's terminal.

[1748] Input: User location data and real-time traffic information

[1749] Output: Optimal delivery route

[1750] Specific actions

[1751] The server calculates the optimal delivery route based on user A's address and current traffic conditions, and sends it to the navigation system of the mobile sales vehicle.

[1752] Step 6:

[1753] The server accepts the on-demand request and adds it to the route

[1754] server

[1755] When a user or care manager submits an on-demand request through the app, it is sent to the server, which accepts the request and adds a new delivery destination to the current delivery route.

[1756] Input: On-demand requests from users or care managers

[1757] Output: Updated delivery route

[1758] Specific actions

[1759] User B suddenly needs a blood glucose test kit and sends a request from the app. The device sends the information to the server, and the server adds User B's address to the existing route.

[1760] Step 7:

[1761] A mobile sales vehicle delivers goods along a route

[1762] Mobile sales vehicle

[1763] The mobile sales vehicle will follow the optimal route received and visit the elderly person's home or designated location, providing the products requested by the user and recommended products.

[1764] Input: Optimal delivery route and product list

[1765] Output: Item delivered to user

[1766] Specific actions

[1767] The mobile food truck arrives at the home of user A and provides low-salt food and a blood pressure monitor. It then heads to the next destination, the home of user B, and delivers a blood glucose testing kit.

[1768] Step 8:

[1769] Mobile food trucks provide a platform for social interaction

[1770] Mobile sales vehicle

[1771] While providing products, the mobile food trucks also serve as a place for seniors to interact with each other, holding events such as mini-games and roundtable discussions at each stop to prevent social isolation.

[1772] Input: Stops and Event Plan

[1773] Output: Social events held

[1774] Specific actions

[1775] Mobile sales trucks visit nursing homes and promote interaction between the elderly by holding mini-games and health seminars while delivering products.

[1776] (Application example 2)

[1777] 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 robot 414 will be referred to as a "terminal."

[1778] Food delivery services for the elderly are required to simultaneously propose products based on not only the user's health status but also their emotional state, while improving delivery efficiency. It is also important to provide a place for social interaction and prevent isolation among the elderly. Current technology does not offer a system that comprehensively addresses these multiple factors, so a more effective system is needed to improve the quality of life for the elderly.

[1779] 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.

[1780] In this invention, the server includes means for collecting user data including purchase history, health status, and preferences, means for collecting the user's emotional state using emotion recognition technology, and means for generating a product list based on the collected user data and emotional state data. This makes it possible to generate a personalized product list based on the user's health status and emotional state, select an optimal delivery route, and provide appropriate products and services to elderly people. In addition, by having the mobile sales van deliver products to users at each stop and holding social events on the spot, it is possible to provide a place for social interaction among elderly people and prevent isolation.

[1781] "Purchase history" is a list of products purchased by the user in the past, along with detailed information about those products.

[1782] "Health status" refers to information related to the user's physical condition and medical care, such as blood pressure, blood sugar level, and allergy information.

[1783] "Preferences" are information about things that a user particularly likes or wants to avoid.

[1784] "Emotion recognition technology" is a technology that uses facial recognition, voice analysis, etc. to identify a user's emotional state.

[1785] "User Data" refers collectively to data including purchasing history, health status, preferences, and other personal information.

[1786] "Emotional state data" is data relating to the user's emotions obtained using emotion recognition technology.

[1787] The "product list" is a list of products to be recommended to the user, generated based on the user data and emotional state data.

[1788] A "mobile sales vehicle" is a vehicle that can stop at a designated location and provide products.

[1789] "Traffic information" refers to information related to traffic, such as road congestion and traffic regulations, that is collected in real time.

[1790] An "on-demand request" is a request to order a product made on the spot by a user or a care manager.

[1791] A "social interaction space" is a space or opportunity where users can interact and socialize with each other when providing products.

[1792] "Generative AI model" is a general term for artificial intelligence algorithms that generate product lists, etc. based on user data and emotional state data.

[1793] This invention is a system for providing a personalized food delivery service specifically for the elderly using AI and an emotion engine. The following describes in detail an embodiment of this invention.

[1794] The server first collects user data, including purchase history, health status, and preferences. This includes information entered by the user through a smartphone application, past purchase history, and regular checkup results. For example, User A enters his or her high blood pressure information and low-salt food purchase history into the app, and the data is sent to the server. The server stores this information in a database.

[1795] Next, the server uses emotion recognition technology to collect the user's emotional state. When a user uses a smartphone application, the camera scans their face and emotion recognition technology is used to read their emotions. This emotion data is also sent to the server and stored in a database. For example, user A's face is scanned while using an app, and the app recognizes that their emotion is happiness, and this information is sent to the server.

[1796] The server uses a generative AI model based on the collected user data and emotional state data to generate a personalized product list. This allows the server to suggest optimal products based on the user's health condition and current emotional state. For example, in the case of User A, based on information about high blood pressure and a feeling of happiness, it is possible to suggest low-salt foods as well as sweets as a special treat.

[1797] The server also calculates the optimal delivery route for the mobile sales vehicle based on user data and real-time traffic information. This optimal route information is sent to the sales vehicle's terminal. For example, the server calculates the shortest route from the area where user A lives to the address of user B, and sends this information to the navigation system of the mobile sales vehicle.

[1798] Additionally, users or care managers can send on-demand requests through the application. The device sends these requests to the server, which accepts the requests and adds them to the current delivery route. For example, User B suddenly needs a blood glucose test kit and sends a request through the application. This information is sent to the server, which adds User B's address to the existing route.

[1799] Finally, the mobile sales vehicle follows the optimal route received from the server and visits the elderly person's home or other designated locations, providing the products requested or recommended by the user. For example, the sales vehicle arrives at User A's home and provides low-salt food and a sweet treat, then heads to the next destination, User B's home, to deliver a blood glucose testing kit.

[1800] In this invention, the mobile sales van can provide products to users at the stops and also hold social events on the spot. This allows elderly people to interact with each other and deepen social interactions. As a specific example, the mobile sales van can visit a nursing home and hold mini-games and health seminars while providing products, thereby promoting interaction between elderly people.

[1801] An example prompt for a generative AI model is, "Design a system that allows elderly people to input their health and emotional state via a smartphone app, and then uses AI and an emotion engine to generate a personalized food list and delivery route."

[1802] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1803] Step 1:

[1804] User Data Collection

[1805] The device collects user data (purchase history, health status, and preferences). The user enters their information through a smartphone app, and the device sends the data to a server. The server stores this data in a database. For example, this data may include information about User A's high blood pressure and preference for low-salt foods.

[1806] Step 2:

[1807] Emotion recognition data collection

[1808] The device collects data on the user's emotional state. While the user is using a smartphone app, the camera scans the user's face and sends the image to emotion recognition technology. The emotion recognition technology analyzes the image and determines the user's emotional state. The results of this determination are sent from the device to a server and stored in a database. For example, if User A is recognized as having a happy emotion while using the app, that information is sent to the server.

[1809] Step 3:

[1810] Generate personalized product lists

[1811] Based on the user data and emotional state data collected by the server, a generative AI model is used to generate a personalized product list. Input data includes health status and emotional state, and specific products are selected based on that data. For example, in the case of User A, low-salt foods and treat sweets are included in the list because User A has high blood pressure and is in a state of happiness.

[1812] Step 4:

[1813] Calculating the optimal delivery route

[1814] The server calculates the optimal delivery route for the mobile sales truck based on user data and real-time traffic information. Inputs include each user's location and current traffic conditions. The server calculates this data and calculates the shortest and most efficient route. As a result, optimal route information from a specific user's address to the next user's address is generated and sent to the mobile sales truck's terminal.

[1815] Step 5:

[1816] Accepting on-demand requests

[1817] A user or care manager sends an on-demand request through a smartphone app. The device receives this request and sends it to the server. The server accepts the request and adds the address corresponding to the request to the existing delivery route. For example, User B suddenly needs a blood glucose test kit and sends a request from the app. The information is sent to the server, and User B's address is added to the delivery route.

[1818] Step 6:

[1819] Supply and delivery of goods

[1820] The mobile sales vehicle travels according to the optimal route received from the server, and delivers products to the user's home or a specified location. Specifically, the sales vehicle arrives at the home of user A and delivers low-salt foods and sweets. It then heads to the home of user B, its next destination, and delivers a blood glucose testing kit.

[1821] Step 7:

[1822] Providing a venue for social interaction

[1823] The mobile sales truck will deliver products to users at each stop and also hold social events on the spot. This allows users to interact with each other and deepen social interactions. For example, a mobile sales truck may visit a nursing home and hold mini-games and health seminars while delivering products, promoting interaction between the elderly.

[1824] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice 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 voice data.

[1825] 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.

[1826] 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 robot 414.

[1827] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1828] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1829] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1830] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1831] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1832] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1833] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1834] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1835] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1836] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1837] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1838] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1839] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1840] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1841] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1842] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1843] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1844] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1845] The following is further disclosed regarding the above embodiment.

[1846] (Claim 1)

[1847] means for collecting user data, including purchasing history, health status, and preferences;

[1848] A means for generating a product list based on the collected user data;

[1849] a means for loading products onto a mobile sales vehicle based on the generated product list;

[1850] A means for optimizing delivery routes of mobile sales vehicles based on user data and traffic information;

[1851] a means for accepting on-demand requests from a user or a care manager;

[1852] means for delivering products to the user's home or a set location based on the product listing and on-demand request;

[1853] A mobile sales vehicle will provide products to users at the stop and hold a social event on the spot.

[1854] A system including:

[1855] (Claim 2)

[1856] 10. The system of claim 1, wherein the system uses an AI algorithm to analyze user data.

[1857] (Claim 3)

[1858] 2. The system according to claim 1, wherein the delivery route of a mobile sales vehicle is optimized based on real-time traffic information.

[1859] "Example 1"

[1860] (Claim 1)

[1861] means for collecting user data, including purchasing history, health status, and preferences;

[1862] A means for generating a product list based on the collected user data;

[1863] a means for loading products onto a mobile sales vehicle based on the generated product list;

[1864] A means for optimizing delivery routes of mobile sales vehicles based on user data and traffic information;

[1865] a means for accepting on-demand requests from a user or a care manager;

[1866] means for delivering products to the user's home or a set location based on the product listing and on-demand request;

[1867] A mobile sales vehicle will provide products to users at the stop and hold a social event on the spot.

[1868] a means for the mobile sales vehicle to add on-demand deliveries based on user requests;

[1869] A means of generating personalized product listings using AI algorithms;

[1870] means for calculating a delivery route based on real-time traffic information;

[1871] A system including:

[1872] (Claim 2)

[1873] 10. The system of claim 1, wherein the system uses an AI model to analyze user data.

[1874] (Claim 3)

[1875] 2. The system according to claim 1, wherein the delivery route of a mobile sales vehicle is optimized based on real-time traffic information.

[1876] "Application Example 1"

[1877] (Claim 1)

[1878] means for collecting user data, including purchasing history, health status, and preferences;

[1879] A means for generating a product list based on the collected user data;

[1880] a means for loading products onto a mobile sales vehicle based on the generated product list;

[1881] A means for optimizing delivery routes of mobile sales vehicles based on user data and traffic information;

[1882] a means for accepting on-demand requests from a user or a care manager;

[1883] means for delivering products to the user's home or a set location based on the product listing and on-demand request;

[1884] A mobile sales vehicle will provide products to users at the stop and hold a social event on the spot.

[1885] A smartphone application that suggests foods based on the user's health condition.

[1886] a smartphone application for users to submit requests for products they need;

[1887] A means of making personalized product recommendations using AI models,

[1888] A system including:

[1889] (Claim 2)

[1890] 10. The system of claim 1, wherein the system uses an AI algorithm to analyze user data.

[1891] (Claim 3)

[1892] 2. The system according to claim 1, wherein the delivery route of a mobile sales vehicle is optimized based on real-time traffic information.

[1893] "Example 2: Combining Emotion Engines"

[1894] (Claim 1)

[1895] means for collecting user information, including purchasing history, health status, and preferences;

[1896] A means for generating a product list based on the collected user information and emotion data;

[1897] a means for loading products onto a mobile sales vehicle based on the generated product list;

[1898] A means for optimizing delivery routes of mobile sales vehicles based on user location data and traffic information;

[1899] means for accepting on-demand requests from a user or care manager;

[1900] means for delivering products to the user's home or designated location based on the product listing and on-demand request;

[1901] A mobile sales vehicle will provide products to users at the stop and hold a social event on the spot.

[1902] A system including:

[1903] (Claim 2)

[1904] 10. The system of claim 1, wherein the system uses AI algorithms to analyze user information and sentiment data.

[1905] (Claim 3)

[1906] 2. The system according to claim 1, wherein the delivery route of a mobile sales vehicle is optimized based on real-time traffic information.

[1907] "Application example 2 when combining emotion engines"

[1908] (Claim 1)

[1909] means for collecting user data, including purchasing history, health status, and preferences;

[1910] means for collecting the user's emotional state using emotion recognition technology;

[1911] means for generating a product list based on the collected user data and emotional state data;

[1912] a means for loading products onto a mobile sales vehicle based on the generated product list;

[1913] A means for optimizing delivery ro...

Claims

1. means for collecting user data, including purchasing history, health status, and preferences; A means for generating a product list based on the collected user data; a means for loading products onto a mobile sales vehicle based on the generated product list; A means for optimizing delivery routes of mobile sales vehicles based on user data and traffic information; a means for accepting on-demand requests from a user or a care manager; means for delivering products to the user's home or a pre-defined location based on the product listing and on-demand request; A mobile sales vehicle will provide products to users at the stopover points and hold an on-site social event. A system including:

2. 10. The system of claim 1, wherein the system uses an AI algorithm to analyze the user data.

3. 2. The system according to claim 1, wherein the delivery route of the mobile sales vehicle is optimized based on real-time traffic information.

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