System

Abstract

A system is provided.SOLUTION: An information processor using a generative AI model that proposes an activity after retirement based on personal preferences and experiences, the information processor comprising: means for inputting preferences and experiences of a user; means for analyzing information inputted by the user using the generative AI model and listing appropriate activities and hobbies; means for narrowing down the listed activities and hobbies based on persona analysis; means for acquiring information related to the narrowed down activities and hobbies; and means for providing the acquired information to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In modern society, many seniors lose track of their next steps after retirement and often suffer from loneliness and lethargy. Leaving a workplace where they have worked for many years can lead to fewer daily activities and interactions, making retirement life less fulfilling. There is a need for a system that can solve this problem and suggest appropriate activities and hobbies for seniors to lead richer and more fulfilling lives after retirement. [Means for solving the problem]

[0005] To solve the above problems, we provide an information processing device that uses a generative AI model to suggest post-retirement activities based on individual preferences and experiences. This device includes an input means for a user to input preferences and experiences, an analysis means for analyzing the user's input information using the generative AI model and listing appropriate activities and hobbies, a narrowing down means for narrowing down the listed activities and hobbies based on persona analysis, an information acquisition means for acquiring information related to the narrowed down activities and hobbies, and a provision means for providing the acquired information to the user. This configuration utilizes the generative AI model to suggest activities and hobbies suitable for each user, helping seniors live active lives even after retirement.

[0006] A "generative AI model" is a model that uses artificial intelligence technology to analyze user input data and create a list of optimal activities and hobbies.

[0007] The term "information processing device" refers to a computer system in general that receives input information from a user, analyzes it, and makes appropriate suggestions.

[0008] "Input means" refers to a device or interface that allows a user to input preferences and experiences into the system.

[0009] "Analysis means" refers to the function of analyzing data obtained from the input means based on a generative AI model and selecting the most suitable activities or hobbies.

[0010] "Persona analysis" refers to a method for analyzing a user's characteristics and behavioral patterns and making appropriate suggestions based on that.

[0011] "Refinement methods" refers to the ability to further refine the activities and hobbies listed by the generative AI model based on persona analysis.

[0012] "Information acquisition means" refers to the function of acquiring information related to narrowed-down activities or hobbies from a database, etc.

[0013] The "provision means" refers to a function for displaying and providing the acquired information to the user.

[0014] "Commission" refers to the fee collected by the system when a contract is concluded between a user and a store or service.

[0015] "Stores and services" refers to businesses and service providers related to retirement activities and hobbies. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] This invention relates to an information processing system that uses a generative AI model to suggest post-retirement activities based on personal preferences and experiences. This system is implemented using a user terminal, a server, and related databases. The specific operations of the system's program processing are explained in natural language below.

[0038] System Overview

[0039] The system uses a generative AI model to analyze a user's personal information and suggest optimal Second Life activities and hobbies. The system has the following key features:

[0040] 1. An "input method" that allows users to input their personal preferences and work experience.

[0041] 2. "Analysis means" that analyzes the information entered by the user and lists appropriate activities and hobbies.

[0042] 3. A "refining method" that narrows down the listed activities and hobbies based on persona analysis.

[0043] 4. "Means of information acquisition" to obtain information related to narrowed-down activities and hobbies.

[0044] 5. "Means of provision" that provides the acquired information to the user and performs matching as necessary.

[0045] Program processing

[0046] The specific operation is described below.

[0047] 1. A user logs in from a terminal

[0048] A user logs in using a specific interface and inputs information such as interests and experiences. Specifically, the user inputs information such as hobbies, past work history, and fields of interest.

[0049] 2. Sending input information to the server

[0050] The data entered by the user is transmitted from the terminal to the server.

[0051] 3. Analysis of Information

[0052] The server inputs the received information into a generative AI model for analysis, which then generates a list of appropriate activities and hobbies based on the user's data.

[0053] 4. Narrowing down through persona analysis

[0054] The server uses persona analysis to narrow down the list obtained from the generative AI model and determine the most suitable activity for the user.

[0055] 5. Obtaining related information

[0056] The server retrieves information related to the determined activity from a database, including local activity clubs, events, classes, etc.

[0057] 6. Provision of Information

[0058] The server transmits the acquired information to the user terminal and displays it in a format that the user can intuitively understand.

[0059] 7. Activity Selection and Planning

[0060] The user plans their second life based on the displayed information.

[0061] 8. Matching

[0062] If necessary, the server matches the user with relevant stores and services, allowing the user to actually experience the suggested activities.

[0063] 9. Contracts and Fee Collection

[0064] When a contract is concluded between the user and the store or service, the server collects a fee.

[0065] Specific examples

[0066] Step 1-2: Enter user information

[0067] The user enters into the device, "My hobby is gardening, I used to work in sales, and I'm interested in outdoor activities and community activities."

[0068] The device sends this information to the server.

[0069] Step 3: Analyze the information

[0070] The server passes the data to the generative AI model for analysis.

[0071] The generative AI model lists activities such as "joining a local gardening club" and "joining a nearby cooking class."

[0072] Step 4: Persona Analysis

[0073] The server conducted a persona analysis and specifically selected "joining a local gardening club" and "joining a nearby cooking class."

[0074] Step 5: Obtain relevant information

[0075] The server retrieves from a database information about stores and services related to the proposed activity, such as details of a gardening club or a cooking class schedule.

[0076] Step 6: Provide information

[0077] The server sends the acquired information to the user's terminal and displays it.

[0078] Steps 7-9: Activity selection and contract formation

[0079] The user makes plans based on the suggested activities and, if necessary, enters into contracts with stores and services.

[0080] If the contract is concluded, the server collects the fee.

[0081] In this way, the system suggests activities and hobbies that will help seniors live fulfilling lives after retirement, and supports them in taking concrete actions.

[0082] The processing flow will be explained below.

[0083] Step 1:

[0084] A user logs in from a device. The user enters their profile information, interests, past work experience, etc. This information includes hobbies (e.g., gardening, cooking), past work experience (e.g., sales), and areas of interest (e.g., outdoors, local activities).

[0085] Step 2:

[0086] The terminal transmits the user's input information to the server.

[0087] Step 3:

[0088] The server inputs the received information into a generative AI model for analysis. As a result of this analysis, a list of activities and hobbies that are best suited to the user is generated. For example, information such as "joining a gardening club" or "taking a cooking class" may be listed.

[0089] Step 4:

[0090] The server uses persona analysis to narrow down the list obtained from the generative AI model and determine the activities that are most suitable for the user. For example, persona analysis may specifically recommend "joining a local gardening club" and "attending a nearby cooking class."

[0091] Step 5:

[0092] The server retrieves information related to the determined activity from the database, including details of the activity and information on related stores and services (e.g., the activity schedule for a gardening club or the dates and times of cooking classes).

[0093] Step 6:

[0094] The server sends the acquired information to the user's terminal and displays it, allowing the user to use it as a reference when making their own plans.

[0095] Step 7:

[0096] Based on the displayed information, the user plans their Second Life by taking into account suggested activities and hobbies. For example, the user may decide to join a gardening club and create a schedule for it.

[0097] Step 8:

[0098] The server then matches the user with relevant stores and services as needed, providing appropriate contact information and detailed information about the activities the user is interested in. At this stage, a point of contact between the user and the store or service is created.

[0099] Step 9:

[0100] When a contract is concluded between a user and a store or service, the server collects a fee. This fee is based on the success of the introduction or match and is used to fund the operation of the service.

[0101] Through the above processing steps, the system can suggest activities and hobbies that will help seniors live fulfilling lives after retirement and support them in taking specific actions.

[0102] Example 1

[0103] 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."

[0104] In modern society, an increasing number of individuals wish to live fulfilling lives in their own way even after retirement. However, it is difficult to determine what activities and hobbies to choose, and it is hard to find the activities that best suit them. Furthermore, because information is scattered, it is time-consuming to obtain detailed information about specific activities. Furthermore, tasks such as matching proposed activities with actual stores and services and collecting fees after contracts are concluded are also cumbersome. There is a need for an efficient information processing device that can solve these problems.

[0105] 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.

[0106] In this invention, the server includes an input means for a user to input their preferences and experiences, an analysis means for analyzing the user's input information using a generative AI model and listing appropriate activities and hobbies, a narrowing down means for narrowing down the listed activities and hobbies based on persona analysis, an information acquisition means for acquiring information related to the narrowed down activities and hobbies, a provision means for providing the acquired information to the user, a matching means for matching the user with relevant stores and services as needed, and a fee collection means for collecting a fee when a contract is concluded between the user and a store or service. This enables the user to efficiently find the optimal post-retirement activities and hobbies, and the provision of specific activity information, matching, and fee collection after the contract is concluded are all carried out in an integrated manner.

[0107] An "information processing device" is a device that refers to the entire system that receives input from a user, analyzes it, and provides the results.

[0108] A "generative AI model" is an artificial intelligence model that generates new information based on a user's preferences and experiences and suggests appropriate activities and hobbies.

[0109] "Input means" refers to an interface or device that allows a user to input their preferences and experiences into the system.

[0110] "Analysis means" refers to the device or software that uses a generative AI model to analyze the user's input information and execute the process of listing activities and hobbies.

[0111] "Refinement methods" refers to the processes or devices used to further refine the activities and hobbies listed by the generative AI model based on persona analysis.

[0112] "Information acquisition means" refers to a device or software for acquiring information related to a narrowed-down activity or hobby from a database.

[0113] "Providing means" refers to an interface or device that provides the acquired information to the user and displays it in a form that the user can intuitively understand.

[0114] "Matching means" refers to a device or software for matching users with related stores or services.

[0115] The term "fee collection means" refers to a device or software for collecting a fee when a contract is concluded between a user and a store or service.

[0116] "Persona analysis" refers to an analytical method for selecting the most suitable activities and hobbies based on a user's attributes and preferences.

[0117] A "database" refers to a system or storage that stores related information and retrieves that information when needed.

[0118] System Overview

[0119] The present invention relates to an information processing device that uses a generative AI model to suggest post-retirement activities based on personal preferences and experiences. This device is implemented using a user terminal, a server, and related databases. Specific operations are described below.

[0120] Hardware and software used

[0121] This system uses the following hardware and software.

[0122] User device: An internet-connected device such as a smartphone, tablet, or PC.

[0123] Server: High performance computing server, cloud server.

[0124] Database: A relational database that stores user information and activity information.

[0125] Generative AI model: A neural network model that performs analysis based on user information.

[0126] Persona analysis software: Dedicated software for conducting persona analysis.

[0127] Communication protocol: Secure data communication using HTTP / HTTPS.

[0128] Specific actions

[0129] 1. A user logs in from a terminal

[0130] Users log in using a web browser or a dedicated app and enter information such as hobbies and experiences.

[0131] 2. Sending input information to the server

[0132] The data entered by the user is sent from the terminal to the server, where it is encrypted and sent securely.

[0133] 3. Analysis of Information

[0134] The server inputs the received information into a generative AI model for analysis, which then lists appropriate activities and hobbies based on the user's data.

[0135] 4. Narrowing down through persona analysis

[0136] The server uses persona analysis to narrow down the list obtained from the generative AI model and determine the most suitable activity for the user.

[0137] 5. Obtaining related information

[0138] The server retrieves information related to the determined activity from a database, including local activity clubs, events, classes, etc.

[0139] 6. Provision of Information

[0140] The server transmits the acquired information to the user terminal and displays it in a format that the user can intuitively understand.

[0141] 7. Activity Selection and Planning

[0142] The user plans their Second Life based on the displayed information. The user selects activities that interest them from the suggested activities and creates a plan.

[0143] 8. Matching

[0144] If necessary, the server matches the user with relevant stores and services, allowing the user to actually experience the suggested activities.

[0145] 9. Contracts and Fee Collection

[0146] When a contract is concluded between the user and the store or service, the server collects a fee. The contract details are managed within the system.

[0147] Specific examples

[0148] Below are some specific examples and prompts:

[0149] Specific examples

[0150] The user enters into the device, "My hobby is gardening, I used to work in sales, and I'm interested in outdoor activities and community activities."

[0151] The device sends this information to the server.

[0152] The server passes the data to a generative AI model for analysis, and lists options such as "joining a local gardening club" and "joining a nearby cooking class."

[0153] The server conducted a persona analysis and specifically selected "joining a local gardening club" and "joining a nearby cooking class."

[0154] The server retrieves from a database information about stores and services related to the proposed activity, examples of which include "gardening club details" and "cooking class schedules."

[0155] The server sends the acquired information to the user's terminal and displays it.

[0156] Prompt Sentence Examples

[0157] "Design a system that uses generative AI models to suggest optimal retirement activities and hobbies based on a user's interests and experiences."

[0158] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0159] System program processing flow

[0160] Step 1:

[0161] The user logs in from their device. They access the login page using a web browser or a dedicated app and enter their user ID and password. After successfully logging in, the user enters information such as their preferences, past work history, and areas of interest. This input information becomes the initial input data for the system.

[0162] Input: User ID, password, preferences, work history, areas of interest

[0163] Output: Login success flag, input information data

[0164] Step 2:

[0165] The information entered by the user is sent from the terminal to the server. During transmission, the data is encrypted and securely transferred to the server.

[0166] Input: Input information data

[0167] Output: A confirmation message sent to the server

[0168] Step 3:

[0169] The server inputs the received information into a generative AI model for analysis. The generative AI model then lists appropriate activities and hobbies based on the user's data. Specifically, it generates the most suitable activity candidates for the user based on data such as hobbies and work history.

[0170] Input: User-entered information data

[0171] Output: List of potential activities

[0172] Step 4:

[0173] The server inputs the list obtained from the generated AI model into persona analysis software to narrow down the list. From the list of candidate activities, persona analysis further selects the activity that best suits the user's attributes and preferences.

[0174] Input: List of possible activities

[0175] Output: A filtered list of activities

[0176] Step 5:

[0177] The server retrieves information related to the determined activity from a database, including local activity clubs, events, courses, etc. It performs a database search to retrieve the latest information related to the proposed activity.

[0178] Input: A filtered list of activities

[0179] Output: Details related to the activity

[0180] Step 6:

[0181] The server sends the acquired information to the user's device and displays it in a format that the user can intuitively understand. Specifically, the server organizes the information, converts it into a format suitable for the user interface, and then sends it.

[0182] Input: Details related to the activity

[0183] Output: Information displayed on the user's terminal

[0184] Step 7:

[0185] The user plans their Second Life based on the displayed information. They select activities that interest them from the suggested activities and formulate a specific plan. The selected information is fed back to the server.

[0186] Input: User-selected activity

[0187] Output: User selection information

[0188] Step 8:

[0189] The server matches the user with relevant stores and services as needed based on the user's selection information, allowing the user to actually experience the suggested activities.

[0190] Input: User selection information

[0191] Output: Matching results

[0192] Step 9:

[0193] When a contract is concluded between the user and the store or service, the server collects the fee. Details of the contract and fee are managed within the system, and a confirmation message is sent to the user and the store.

[0194] Input: Contract conclusion information

[0195] Output: Fee collection and confirmation message

[0196] The above is the specific processing flow of the program of this system.

[0197] (Application example 1)

[0198] 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."

[0199] To enrich the lives of seniors after retirement, there is a need for technology that not only suggests activities and hobbies suitable for seniors, but also provides new ways to enjoy themselves through dining experiences. However, existing systems are limited in the activities and hobbies they suggest based on the user's preferences and experience, making it difficult to translate these suggestions into concrete actions, particularly those such as cooking at home or participating in local cooking events. In addition, arranging ingredients and cooking equipment is complicated, and a simple method for doing this is needed.

[0200] 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.

[0201] In this invention, the server includes an input means for a user to input their preferences and experiences, an analysis means for analyzing the user's input information using a generative AI model to list appropriate activities and hobbies and to list recommended recipes and events to participate in, a narrowing down means for narrowing down the listed activities, hobbies, recommended recipes and events to participate in based on persona analysis, an information acquisition means for acquiring information related to the narrowed down activities, hobbies, recommended recipes and events to participate in, and a provision means for providing the acquired information to the user. This enables users to easily find activities and dining experiences that are best suited to their hobbies and experiences, and to easily arrange the ingredients and cooking utensils for them.

[0202] text

[0203] "Personal preferences and experiences" refers to information such as the user's specific interests, past work history, and areas of interest.

[0204] A "generative AI model" is an artificial intelligence model that analyzes input data and generates optimal suggestions.

[0205] The "input means for the user to input his / her preferences and experiences" is an interface that allows the user to input his / her preferences and experiences into the terminal.

[0206] "Analysis means" refers to a device or software that uses a generative AI model to analyze the user's input information and list appropriate activities, hobbies, recommended recipes, and events to participate in.

[0207] "Persona analysis" is an analytical method for narrowing down the best proposals for a specific target user group based on a typical user profile.

[0208] A "refinement tool" is a device or software that has the ability to optimize activities, hobbies, recommended recipes, or events to attend based on persona analysis.

[0209] The "information acquisition means" is a device or software that has the function of acquiring information related to the narrowed-down activities, hobbies, recommended recipes, and events to attend from a database or external information source.

[0210] The "providing means" is a device or software that has the function of providing the acquired information to the user and displaying it on the user terminal.

[0211] A "delivery means" is a device or software that allows a user to order ingredients and cooking utensils they need and arrange for their delivery.

[0212] text

[0213] The present invention relates to a system that provides a function for proposing post-retirement activities and dining experiences based on a user's preferences and experiences, and delivering the ingredients and cooking utensils required for those activities.

[0214] The system includes the following main components:

[0215] 1. An input method for users to input their preferences and experiences

[0216] 2. A method of analysis that uses a generative AI model to analyze user input and produce a list of appropriate activities, hobbies, recommended recipes, and events to attend.

[0217] 3. A filter to narrow down the activities, hobbies, recommended recipes, and events to attend based on the persona analysis.

[0218] 4. Information acquisition methods for obtaining information related to narrowed-down activities, hobbies, recommended recipes, and events to attend

[0219] 5. Means of providing acquired information to users

[0220] 6. A way for users to have the ingredients and cooking equipment they need delivered

[0221] In terms of the actual program processing, first, the user enters their preferences, past work history, and areas of interest through the interface. This can be done using a smartphone, and React Native can be used to configure the UI. The user's input information is then sent to the server.

[0222] On the server side, a generative AI model (such as GPT-3) and its analysis results are used to create a list of suitable activities, hobbies, recommended recipes, and events to attend. The persona analysis function is then used to refine the list of suggestions. This process uses Node.js and Express as the backend and MongoDB as the database.

[0223] The server retrieves related information from the database based on the filtered information and provides it to the user. This information includes information on local club activities, cooking events, and the ingredients and cooking equipment needed for recommended recipes. Users can check this information on their smartphones and order the necessary ingredients and cooking equipment through a delivery service.

[0224] For example, if a user inputs "Hobbies: cooking, travel," "Past work experience: sales," and "Favorite ingredients: tomatoes, pasta," the server will use the generative AI model to suggest "local Italian cooking classes" and "new recipes using pasta." These suggestions are optimized based on persona analysis and displayed to the user.

[0225] An example prompt is:

[0226] "User data: Hobbies: Cooking, traveling; Past work experience: Sales; Favorite ingredients: Tomato, pasta"

[0227] "Cooking Recommendations:"

[0228] In this way, by using the system of the present invention, users can easily find activities and dining experiences that best suit their hobbies and experiences, and easily arrange the ingredients and cooking utensils for them.

[0229] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0230] text

[0231] Step 1:

[0232] Users log in to the system using a device and enter information such as their preferences, past work history, and areas of interest. The entered data is necessary to proceed to the next processing step, and the information entered here forms the basis for the entire system. Specifically, a smartphone is used, and the UI is built using React Native.

[0233] Step 2:

[0234] The terminal sends the data entered by the user to the server. This sent data is input data to be analyzed by subsequent analysis means. Specific data content includes information such as "Hobbies: cooking, travel," "Past work history: sales," and "Favorite ingredients: tomatoes, pasta."

[0235] Step 3:

[0236] The server receives the input data and feeds it into a generative AI model (such as GPT-3) that analyzes the user's data and lists appropriate activities, hobbies, recommended recipes, and events to attend. During the analysis process, the generative AI model treats the input data as prompts.

[0237] Step 4:

[0238] Using the list data obtained from the generative AI model, the server performs persona analysis, which optimizes the listed proposals for specific target users. In this step, data is narrowed down based on a specific persona profile, and the proposals that are most suitable for the user are selected.

[0239] Step 5:

[0240] The server retrieves information related to the user's activities, hobbies, recommended recipes, and events from a database. This information includes details of local clubs, cooking events, and ingredients and utensils used in recipes. This data is retrieved using a database such as MongoDB.

[0241] Step 6:

[0242] The server then sends the acquired information to the user's device and provides it in a format that the user can intuitively understand. Here, the information is displayed on a user interface, allowing the user to check specific proposals.

[0243] Step 7:

[0244] Users select from suggested activities, hobbies, and dining experiences, and then order ingredients and cooking equipment via delivery services. The ordering process is completed by the user on their device, and the server sends the order data to the delivery service. Once the order is confirmed, the desired items are delivered to the user.

[0245] Step 8:

[0246] The server collects a fee when a contract is concluded between the user and the delivery service. This fee collection is performed automatically, and financial transactions between the user and the service provider are carried out smoothly.

[0247] 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.

[0248] This invention relates to an information processing system that combines an information processing device using a generative AI model that suggests post-retirement activities based on personal preferences and experience with an emotion engine that recognizes the user's emotions and reflects them in the activity suggestions. This system is implemented using a user terminal, a server, and devices and related databases required for emotion recognition. The specific operations of the system's program processing are explained below in natural language.

[0249] System Overview

[0250] The system uses a generative AI model and an emotion engine to analyze a user's personal information and suggest optimal Second Life activities and hobbies. The system has the following key features:

[0251] 1. An "input method" that allows users to input their personal preferences and work experience.

[0252] 2. "Analysis method" that analyzes user input information using a generative AI model and lists appropriate activities and hobbies.

[0253] 3. "Emotion recognition means" that recognizes the user's emotions in real time and reflects them in the analysis results.

[0254] 4. "Refining methods" to narrow down the activities and hobbies listed based on persona analysis.

[0255] 5. "Means of information acquisition" to obtain information related to narrowed-down activities and hobbies.

[0256] 6. "Means of provision" that provides the acquired information to the user and performs matching as necessary.

[0257] Program processing

[0258] The specific operation is described below.

[0259] 1. A user logs in from a terminal

[0260] A user logs in using a specific interface and inputs information about their interests, experiences, and emotions. Specifically, the user inputs their hobbies, past work history, areas of interest, and current emotional state.

[0261] 2. Sending input information to the server

[0262] The data entered by the user is transmitted from the terminal to the server.

[0263] 3. Analysis of Information

[0264] The server inputs the received information into a generative AI model for analysis. The generative AI model generates a list of appropriate activities and hobbies based on the user's data. For example, it might list information such as "joining a gardening club" or "attending cooking classes."

[0265] 4. Emotion Recognition by Emotion Engine

[0266] The emotion engine recognizes the user's emotional data in real time and further refines the activities and hobbies listed by the analysis means based on the emotional data. For example, if the user is feeling stressed, relaxing activities will be prioritized.

[0267] 5. Narrowing down through persona analysis

[0268] The server further analyzes the information obtained from the emotion engine using a persona analysis function to determine the most appropriate activity for the user.

[0269] 6. Obtaining related information

[0270] The server retrieves information related to the determined activity from a database, including local activity clubs, events, classes, etc.

[0271] 7. Provision of Information

[0272] The server sends the acquired information to the user's terminal and displays it, allowing the user to create a specific activity plan while referring to the displayed information.

[0273] 8. Activity Selection and Planning

[0274] Based on the displayed information, users can plan their Second Life by taking into account suggested activities and hobbies. For example, a user may decide to join a gardening club and create a schedule for it.

[0275] 9. Matching

[0276] The server then matches the user with relevant stores and services as needed, providing appropriate contact information and detailed information about the activities the user is interested in. At this stage, a point of contact between the user and the store or service is created.

[0277] 10. Contracts and Fee Collection

[0278] When a contract is concluded between a user and a store or service, the server collects a fee. This fee is based on the success of the introduction or match and is used to fund the operation of the service.

[0279] Specific examples

[0280] Step 1-2: Enter user information

[0281] The user types into the device, "My hobby is gardening, and I used to work in sales. I'm interested in outdoor activities and community activities, but recently I've been wanting to do something more relaxing."

[0282] The device sends this information to the server.

[0283] Step 3: Analyze the information

[0284] The server passes the data to the generative AI model for analysis.

[0285] The generative AI model lists activities such as "joining a local gardening club" and "joining a nearby cooking class."

[0286] Step 4: Emotion Recognition with the Emotion Engine

[0287] The emotion engine recognizes the user's emotional data in real time as they input, and prioritizes relaxing activities (e.g., gardening) when stress levels are high.

[0288] Step 5: Persona analysis

[0289] The server conducted a persona analysis and specifically recommended "joining a local gardening club."

[0290] Step 6: Obtain relevant information

[0291] The server retrieves details and activity schedules of local gardening clubs from a database.

[0292] Step 7: Provide information

[0293] The server sends the acquired information to the user's terminal and displays it.

[0294] Step 8: Select and plan your activities

[0295] A user decides to join a gardening club and makes a schedule for it.

[0296] Step 9: Matching

[0297] The server matches users with gardening clubs and provides contact information and details.

[0298] Step 10: Closing the deal and collecting fees

[0299] The user enters into a contract with the gardening club, and the server collects the fee.

[0300] In this way, the system can suggest activities and hobbies that seniors can pursue to live a fulfilling life after retirement, and can also use the emotion engine to make optimal suggestions based on the user's emotions. This makes it possible to provide services that meet individual needs and increase user satisfaction.

[0301] The processing flow will be explained below.

[0302] Step 1:

[0303] The user logs in from a terminal and uses a specific interface to input their preferences, experiences, and current emotional state. For example, they input their hobbies (gardening, cooking), past work history (sales), areas of interest (outdoors, local activities), and current feelings (wanting to relax).

[0304] Step 2:

[0305] The device sends the user's input information, including information about the emotional state, to the server.

[0306] Step 3:

[0307] The server inputs the received information into a generative AI model for analysis. The generative AI model analyzes the user's preferences and experience data and lists appropriate Second Life activities and hobbies. For example, it might list "join a gardening club" or "attend a cooking class."

[0308] Step 4:

[0309] The server uses an emotion engine to recognize the user's emotional data in real time as they input. The emotion engine then refines the activities and hobbies listed by the generative AI model based on the emotional data. For example, if the user is in the mood to relax, "joining a gardening club" will be prioritized.

[0310] Step 5:

[0311] The server performs persona analysis and further analyzes the information obtained from the emotion engine to determine the most suitable activities for the user. Persona analysis selects the best suggestions based on the user's detailed characteristics.

[0312] Step 6:

[0313] The server retrieves information related to the determined activity from a database, such as details about a local gardening club or a cooking class schedule.

[0314] Step 7:

[0315] The server sends the acquired information to the user's terminal and displays it on the screen. The user can select various activities based on the displayed information.

[0316] Step 8:

[0317] Based on the displayed information, the user plans their Second Life by taking into account the suggested activities and hobbies. For example, the user decides to "join a gardening club" and adjusts their schedule accordingly.

[0318] Step 9:

[0319] The server will match the user with relevant businesses and services as needed, for example if the user is interested in a gardening club, providing contact details and details on how to join.

[0320] Step 10:

[0321] When a contract is concluded between a user and a store or service, the server collects a fee. This fee is based on the success of the service introduction and matching, and is used to fund the system's operations.

[0322] Through these processing steps, the system can suggest activities and hobbies that seniors can pursue to lead fulfilling lives after retirement, and use the emotion engine to make optimal suggestions based on the user's emotions. Furthermore, by supporting users to start specific activities, the system can increase overall satisfaction.

[0323] Example 2

[0324] 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."

[0325] When suggesting post-retirement activities and hobbies, it is difficult to provide optimal options while appropriately considering the user's personal information and emotions. Furthermore, there is a need to reduce the effort required to obtain specific information about activities that interest users and to support them in starting activities smoothly. In particular, if suggestions do not reflect the user's emotional state, user satisfaction will decrease, and a system that solves this problem is needed.

[0326] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0327] In this invention, the server includes: an input means for a user to input information about their preferences, experiences, and emotions; a communication means for transmitting the input information to the server; an analysis means for analyzing the user's input information using a generative AI model and listing appropriate activities and hobbies; an emotion recognition means for recognizing the user's emotions and reflecting them in the analysis results; a narrowing down means for narrowing down the listed activities and hobbies based on persona analysis; an information acquisition means for acquiring information related to the narrowed down activities and hobbies; a provision means for providing the acquired information to the user; a matching means for matching the user with relevant stores and services; and a fee collection means for collecting a fee when a contract is concluded between the user and a store or service. This makes it possible to suggest optimal post-retirement activities and hobbies based on the user's individual preferences and emotions, allowing them to start activities smoothly, thereby increasing user satisfaction and improving the convenience of the service.

[0328] "Input means" refers to an interface through which a user inputs information about preferences, experiences, and emotions.

[0329] "Communication means" refers to a data communication function for transmitting information entered by the user to the server.

[0330] "Analysis means" refers to the function that uses a generative AI model to analyze the user's input information and list appropriate activities and hobbies.

[0331] "Emotion recognition means" refers to a function that recognizes the user's emotional state in real time and reflects the results in the analysis results.

[0332] "Refinement tools" refers to the ability to narrow down the activities and hobbies listed based on persona analysis.

[0333] "Information acquisition means" refers to the function of acquiring information related to narrowed-down activities and hobbies from a database.

[0334] "Providing means" refers to a function that provides the acquired information to the user and displays it on the interface.

[0335] "Matching means" refers to a function that matches users with related stores and services.

[0336] The "fee collection means" refers to a function for collecting a fee when a contract is concluded between a user and a store or service.

[0337] The present invention relates to an information processing system that suggests post-retirement activities based on a user's preferences, experiences, and emotions. This system is implemented using a user terminal, a server, an emotion recognition device, and related databases. The specific configuration and operation of the present invention are described in detail below.

[0338] The system includes an "input means" through which a user inputs information about preferences, experiences, and emotions. The input is performed through a terminal interface, such as a text box or drop-down menu, and is implemented using a common computing device, such as a smartphone or PC.

[0339] The information entered by the user is sent to the server via a "communication method." This communication method is realized via network communication, and usually uses the HTTPS protocol. This ensures that the input data is sent securely to the server.

[0340] The server uses an "analysis tool" to pass the user's input information to a generative AI model for analysis. The generative AI model may use Python-based Pytorch or OpenAI's GPT-3, for example. This analysis generates a list of appropriate activities and hobbies based on the user's preferences and experience.

[0341] The system also includes an "emotion recognition mechanism" that uses Microsoft's Emotion API or proprietary emotion recognition algorithms to recognize the user's emotional state in real time. This emotional data is sent to a server and reflected in the analysis results. If the user is feeling stressed, relaxation activities will be prioritized.

[0342] Next, a "refining method" further refines the best activities and hobbies using persona analysis, for example using Scikit-learn or TensorFlow. The server identifies the activities that best fit the user's profile and passes that information on to the next step.

[0343] Using the "information retrieval means," the server retrieves information related to the determined activity or hobby from the database. This information may include local activity clubs, events, classes, etc. Specifically, the server issues an SQL query to retrieve the necessary information from the database.

[0344] The acquired information is sent to the user terminal by the "providing means" and displayed on the user's interface. This allows the user to make specific plans based on the suggested activities. For example, the user may decide to join a gardening club and create a schedule for it.

[0345] Furthermore, the server uses a "matching method" to match users with relevant stores and services. Specifically, it uses a matching algorithm to provide users with the most suitable contact information and detailed information. This information is sent via email, SMS, or in-app notifications.

[0346] Finally, when a contract is concluded between the user and the store or service, the server collects the fee using the "fee collection means." This fee is processed using a payment system (for example, PayPal API or Stripe API) and becomes operating funds for the service.

[0347] Specific examples

[0348] A user logs in using a device and enters information such as, "My hobby is gardening, and I used to work in sales. I'm interested in outdoor activities and local activities, but recently I've been wanting to do something more relaxing." This information is sent to the server and analyzed by the generative AI model. The generative AI model then lists activities such as "joining a local gardening club" and "joining a nearby cooking class."

[0349] The emotional state of the user is also checked using an emotion engine; for example, if the stress level is high, "relaxing activities" are prioritized. Persona analysis is performed to narrow down the activities that are most suitable for the user. The server retrieves detailed information and activity schedules of local gardening clubs from a database and displays them on the user's device. The user decides to join the gardening club and creates a schedule for it.

[0350] The server matches users with gardening clubs, provides contact information and details, and finally, the user enters into a contract with the gardening club, and the server collects the commission.

[0351] This system makes it possible to suggest optimal post-retirement activities and hobbies based on the user's individual tastes and feelings, allowing them to smoothly start their activities, thereby increasing user satisfaction and improving the convenience of the service.

[0352] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0353] Step 1:

[0354] User logs in from terminal

[0355] The user inputs information about their preferences, experiences, and emotions. The device receives this input information and formats the data for transmission. The input data (e.g., "I enjoy gardening as a hobby and used to work in sales. I'm interested in outdoor activities and community activities, but recently I've been wanting to do something more relaxing") is prepared as a transmission request. In concrete terms, the user opens a web browser, accesses a login page, enters their username and password, and clicks the login button.

[0356] Step 2:

[0357] Sending input information to the server

[0358] The input data generated by the device is sent to the server using the HTTPS protocol. An encrypted channel is used for communication. The input data is decoded on the server side and prepared for further processing. Specifically, the user enters information into the input form and clicks the "Submit" button. At that time, the data is sent asynchronously using an AJAX request.

[0359] Step 3:

[0360] Analysis of information

[0361] The server inputs the user's input information into a generative AI model. The generative AI model (e.g., Python's Pytorch or GPT-3) is used to analyze the data and list appropriate activities and hobbies. The input data is passed to the generative AI model, and the analysis results, which are listed as activities and hobbies, are generated in JSON format. Specifically, a Python script is executed, the generative AI model analyzes the data, and the results are output.

[0362] Step 4:

[0363] Emotion recognition by emotion recognition means

[0364] The server receives emotion recognition data (e.g., from a facial recognition camera or Emotion API) and evaluates the user's emotional state. Based on this, the analysis results are prioritized. The emotion data is processed in real time and indicators such as stress levels are calculated. Specifically, the emotion recognition device collects emotion data, and the server analyzes it.

[0365] Step 5:

[0366] Narrowing down through persona analysis

[0367] The server uses the persona analysis function to further narrow down the listed activities and hobbies based on the analysis results and emotional data. A persona analysis algorithm (e.g., Scikit-learn or TensorFlow) is run to determine the best options. The input data and analysis results are passed to the persona analysis algorithm, which outputs the narrowed down results. Specifically, the persona analysis script is run on the server.

[0368] Step 6:

[0369] Obtaining related information

[0370] The server retrieves information related to the narrowed-down activities and hobbies from the database. It issues an SQL query to retrieve the target data and formats it as a response. The narrowed-down activities and hobbies are used in the database query, and the relevant information is returned in JSON format. Specifically, the server executes the SQL query and retrieves the information from the database.

[0371] Step 7:

[0372] Providing information

[0373] The server sends the retrieved relevant information to the user's device and displays it on the user's interface. The data is visually organized and displayed using HTML and CSS, allowing the user to review the information and make decisions. Specifically, the server sends the retrieved data in JSON format to the device, where it is displayed on the device's interface.

[0374] Step 8:

[0375] Activity selection and planning

[0376] The user selects activities and hobbies based on the displayed information and creates a specific plan. The user's selection is passed to the next processing step. On the device interface, the user clicks the "Join" button and registers the schedule in conjunction with the calendar app. Specifically, the device automatically generates a schedule based on the activities selected by the user.

[0377] Step 9:

[0378] Matching implementation

[0379] The server uses a matching algorithm to match the user with relevant stores and services. The server provides optimal contact information and detailed information. The matching results are generated and notified to the user. Specifically, the server executes the algorithm and sends the appropriate contact information to the user's device.

[0380] Step 10:

[0381] Contracts and fee collection

[0382] When a contract is concluded between the user and the store or service, the server records that information and collects the fee. The fee is processed using a payment system (e.g., PayPal API or Stripe API). The information about the conclusion of the contract is passed as input data to the payment system, which then processes the fee. Specifically, the server calls the payment API and completes the fee transaction.

[0383] (Application example 2)

[0384] 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."

[0385] There is a lack of methods to suggest optimal activities for retirement based on personal preferences and experiences. There is also a lack of technology that suggests appropriate activities while taking into account the user's emotions. Furthermore, there is a lack of systems that allow users to easily access and schedule suggested activities. Therefore, there is a need for methods to enrich retirement life.

[0386] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an emotion recognition means for recognizing the user's emotions and reflecting them in the proposals, an input means for the user to input their preferences and experiences, an analysis means for analyzing the user's input information using a generative AI model and listing appropriate activities and hobbies, a narrowing down means for narrowing down the listed activities and hobbies based on persona analysis, an information acquisition means for acquiring information related to the narrowed down activities and hobbies, a provision means for providing the acquired information to the user, a notification means for notifying the user of recommended activities, and a schedule setting means for setting a schedule based on the proposed activities. This makes it possible to propose optimal post-retirement activities taking into account the user's personal information and emotions.

[0387] The "input means" is an interface that allows the user to input their own preferences and experiences.

[0388] The "analysis means" is a device that uses a generative AI model to analyze the user's input information and list appropriate activities and hobbies.

[0389] A "narrowing tool" is a device that has the function of further narrowing down the activities and hobbies listed based on persona analysis.

[0390] The "information acquisition means" is a device that acquires information related to the narrowed-down activities and hobbies from a database.

[0391] The "providing means" is a device that provides the acquired information to the user.

[0392] An "emotion recognition means" is a device that recognizes the user's emotions in real time and reflects them in suggestions.

[0393] The "notification means" is a device that has the function of notifying the user of recommended activities.

[0394] A "schedule setting means" is a device that has the function of setting a schedule for a user based on suggested activities.

[0395] To implement the present invention, a system including emotion recognition means, input means, analysis means, narrowing means, information acquisition means, provision means, notification means, and schedule setting means is required.

[0396] System configuration and operation

[0397] The system consists of a user terminal, a server, and related databases. The operation of each component of the system is described in detail below.

[0398] User terminal

[0399] First, users log in to the system using their device (smartphone or tablet). After logging in, they can enter information about their preferences and experiences. An input method is provided, and an interface is prepared for users to enter details about their hobbies, work history, interests, etc.

[0400] server

[0401] The server includes the following means:

[0402] 1. Input Method

[0403] It provides an interface for users to input their preferences and experiences.

[0404] 2. Analysis method

[0405] The server receives the information entered by the user and analyzes it using a generative AI model, resulting in a list of activities and hobbies that are best suited to the user.

[0406] 3. Emotion recognition means

[0407] It includes a software module for recognizing users' emotions in real time, and this emotional data is reflected in the analysis results, improving the accuracy of the proposal activities.

[0408] 4. Narrowing methods

[0409] Based on persona analysis, narrow down the list of activities and hobbies generated to the most suitable items.

[0410] 5. Information acquisition means

[0411] It has the ability to retrieve information related to narrowed-down activities and hobbies (e.g., location, time, price) from a database.

[0412] 6. Means of provision

[0413] This is a means for providing the acquired information to the user. Specifically, it sends the information to the user's terminal and displays it.

[0414] 7. Means of notification

[0415] Notify users about recommended activities.

[0416] 8. Scheduling Methods

[0417] It is a way to set a schedule for the user based on suggested activities, and it also works with notifications to set reminders.

[0418] Hardware and Software

[0419] Emotion Recognition Engine: A software module for recognizing user emotions in real time.

[0420] Generative AI model: A model that analyzes user input and lists optimal activities and hobbies.

[0421] Database: A database that stores information about activities and hobbies and is accessed by information retrieval methods.

[0422] Specific examples

[0423] Suppose a user inputs "cooking" as their hobby, "sales" as their work history, "handicrafts" as their interest, and "slightly tired" as their current emotional state. This information is sent to the server and analyzed by the analysis means. The generative AI model lists activities such as "nearby handicraft classes" and "cooking workshops." The emotion recognition means confirms the emotion of "slightly tired," and prioritizes the relaxing "handicraft classes." The narrowing means selects more accurate activities, and the information acquisition means acquires specific location, time, and price information from the database. The provision means displays the information on the user's terminal, and the notification means notifies the user of recommended activities. Finally, the schedule setting means allows the user to set a schedule for the handicraft classes.

[0424] Prompt Sentence Examples

[0425] User Preferences: ["Cooking", "Crafts"]

[0426] User Experience: "Sales Job"

[0427] Current Emotion: "Slightly tired"

[0428] The above is a specific embodiment for carrying out the invention.

[0429] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0430] Step 1:

[0431] A user logs in to the system using a device. The user accesses the app's login screen and completes the login by entering their personal authentication information. The input data is the user's ID and password, and the output is access permission.

[0432] Step 2:

[0433] The user inputs their interests, experiences, and current emotional state into the terminal. Specifically, they input information such as "cooking" as a hobby, "sales experience," and an interest in "handicrafts." They also input "slightly tired" as their current emotional state. This information is sent to the server as input data.

[0434] Step 3:

[0435] The server inputs the received user information into a generative AI model for analysis. The input data is the user's preferences, experiences, and emotional state, and the output is a list of activities and hobbies that are best suited to the user. The generative AI model analyzes this data and lists activities such as "nearby craft classes" and "cooking workshops."

[0436] Step 4:

[0437] The server analyzes the user's emotional data using an emotion recognition means. The input data is the user's current emotional state, and the output is a list of activities that take emotions into account. Reflecting the emotional data of "slightly tired," the server prioritizes the suggestion of "sewing classes" to relax.

[0438] Step 5:

[0439] The server uses a refinement method to further refine the generated activity list based on persona analysis. The input data is the activity list and emotion recognition data, and the output is the refined activities that are most suitable for the user. Here, "Handicraft class" is particularly recommended from the refined list.

[0440] Step 6:

[0441] The server uses the information acquisition means to acquire detailed information related to the narrowed-down activities from the database. Specifically, it acquires information such as the location, time, and fee of the handicraft class. The input data is the narrowed-down activity name, and the output is the detailed information.

[0442] Step 7:

[0443] The server provides the acquired detailed information to the user terminal. Using the providing means, information such as the location, time, and fee of the handicraft class is displayed on the user terminal. The input data is the detailed information, and the output is the information displayed to the user.

[0444] Step 8:

[0445] The server uses the notification mechanism to notify the user about the recommended activity. The input data is the information provided, and the output is the notification content. The user receives a notification confirming "attend a sewing class."

[0446] Step 9:

[0447] The user selects the suggested activities and sets the schedule. The user confirms the dates and times of the craft classes and inputs the schedule. The input data is the user's schedule information, and the output is the scheduled information.

[0448] Step 10:

[0449] The server uses the schedule setting means to check the user's schedule setting and activate the reminder function, so that the user receives reminder notifications based on the set schedule. The input data is schedule information, and the output is reminder notifications.

[0450] The above is the specific processing flow of the present invention. Through this series of steps, the user can find the most suitable activity based on their personal tastes and feelings, and live a comfortable life after retirement.

[0451] 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.

[0452] 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.

[0453] 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.

[0454] [Second embodiment]

[0455] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0456] 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.

[0457] 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).

[0458] 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.

[0459] 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.

[0460] 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).

[0461] 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.

[0462] 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.

[0463] 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.

[0464] 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.

[0465] 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.

[0466] 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."

[0467] This invention relates to an information processing system that uses a generative AI model to suggest post-retirement activities based on personal preferences and experiences. This system is implemented using a user terminal, a server, and related databases. The specific operations of the system's program processing are explained in natural language below.

[0468] System Overview

[0469] The system uses a generative AI model to analyze a user's personal information and suggest optimal Second Life activities and hobbies. The system has the following key features:

[0470] 1. An "input method" that allows users to input their personal preferences and work experience.

[0471] 2. "Analysis means" that analyzes the information entered by the user and lists appropriate activities and hobbies.

[0472] 3. A "refining method" that narrows down the listed activities and hobbies based on persona analysis.

[0473] 4. "Means of information acquisition" to obtain information related to narrowed-down activities and hobbies.

[0474] 5. "Means of provision" that provides the acquired information to the user and performs matching as necessary.

[0475] Program processing

[0476] The specific operation is described below.

[0477] 1. A user logs in from a terminal

[0478] A user logs in using a specific interface and inputs information such as interests and experiences. Specifically, the user inputs information such as hobbies, past work history, and fields of interest.

[0479] 2. Sending input information to the server

[0480] The data entered by the user is transmitted from the terminal to the server.

[0481] 3. Analysis of Information

[0482] The server inputs the received information into a generative AI model for analysis, which then generates a list of appropriate activities and hobbies based on the user's data.

[0483] 4. Narrowing down through persona analysis

[0484] The server uses persona analysis to narrow down the list obtained from the generative AI model and determine the most suitable activity for the user.

[0485] 5. Obtaining related information

[0486] The server retrieves information related to the determined activity from a database, including local activity clubs, events, classes, etc.

[0487] 6. Provision of Information

[0488] The server transmits the acquired information to the user terminal and displays it in a format that the user can intuitively understand.

[0489] 7. Activity Selection and Planning

[0490] The user plans their second life based on the displayed information.

[0491] 8. Matching

[0492] If necessary, the server matches the user with relevant stores and services, allowing the user to actually experience the suggested activities.

[0493] 9. Contracts and Fee Collection

[0494] When a contract is concluded between the user and the store or service, the server collects a fee.

[0495] Specific examples

[0496] Step 1-2: Enter user information

[0497] The user enters into the device, "My hobby is gardening, I used to work in sales, and I'm interested in outdoor activities and community activities."

[0498] The device sends this information to the server.

[0499] Step 3: Analyze the information

[0500] The server passes the data to the generative AI model for analysis.

[0501] The generative AI model lists activities such as "joining a local gardening club" and "joining a nearby cooking class."

[0502] Step 4: Persona Analysis

[0503] The server conducted a persona analysis and specifically selected "joining a local gardening club" and "joining a nearby cooking class."

[0504] Step 5: Obtain relevant information

[0505] The server retrieves from a database information about stores and services related to the proposed activity, such as details of a gardening club or a cooking class schedule.

[0506] Step 6: Provide information

[0507] The server sends the acquired information to the user's terminal and displays it.

[0508] Steps 7-9: Activity selection and contract formation

[0509] The user makes plans based on the suggested activities and, if necessary, enters into contracts with stores and services.

[0510] If the contract is concluded, the server collects the fee.

[0511] In this way, the system suggests activities and hobbies that will help seniors live fulfilling lives after retirement, and supports them in taking concrete actions.

[0512] The processing flow will be explained below.

[0513] Step 1:

[0514] A user logs in from a device. The user enters their profile information, interests, past work experience, etc. This information includes hobbies (e.g., gardening, cooking), past work experience (e.g., sales), and areas of interest (e.g., outdoors, local activities).

[0515] Step 2:

[0516] The terminal transmits the user's input information to the server.

[0517] Step 3:

[0518] The server inputs the received information into a generative AI model for analysis. As a result of this analysis, a list of activities and hobbies that are best suited to the user is generated. For example, information such as "joining a gardening club" or "taking a cooking class" may be listed.

[0519] Step 4:

[0520] The server uses persona analysis to narrow down the list obtained from the generative AI model and determine the activities that are most suitable for the user. For example, persona analysis may specifically recommend "joining a local gardening club" and "attending a nearby cooking class."

[0521] Step 5:

[0522] The server retrieves information related to the determined activity from the database, including details of the activity and information on related stores and services (e.g., the activity schedule for a gardening club or the dates and times of cooking classes).

[0523] Step 6:

[0524] The server sends the acquired information to the user's terminal and displays it, allowing the user to use it as a reference when making their own plans.

[0525] Step 7:

[0526] Based on the displayed information, the user plans their Second Life by taking into account suggested activities and hobbies. For example, the user may decide to join a gardening club and create a schedule for it.

[0527] Step 8:

[0528] The server then matches the user with relevant stores and services as needed, providing appropriate contact information and detailed information about the activities the user is interested in. At this stage, a point of contact between the user and the store or service is created.

[0529] Step 9:

[0530] When a contract is concluded between a user and a store or service, the server collects a fee. This fee is based on the success of the introduction or match and is used to fund the operation of the service.

[0531] Through the above processing steps, the system can suggest activities and hobbies that will help seniors live fulfilling lives after retirement and support them in taking specific actions.

[0532] Example 1

[0533] 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."

[0534] In modern society, an increasing number of individuals wish to live fulfilling lives in their own way even after retirement. However, it is difficult to determine what activities and hobbies to choose, and it is hard to find the activities that best suit them. Furthermore, because information is scattered, it is time-consuming to obtain detailed information about specific activities. Furthermore, tasks such as matching proposed activities with actual stores and services and collecting fees after contracts are concluded are also cumbersome. There is a need for an efficient information processing device that can solve these problems.

[0535] 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.

[0536] In this invention, the server includes an input means for a user to input their preferences and experiences, an analysis means for analyzing the user's input information using a generative AI model and listing appropriate activities and hobbies, a narrowing down means for narrowing down the listed activities and hobbies based on persona analysis, an information acquisition means for acquiring information related to the narrowed down activities and hobbies, a provision means for providing the acquired information to the user, a matching means for matching the user with relevant stores and services as needed, and a fee collection means for collecting a fee when a contract is concluded between the user and a store or service. This enables the user to efficiently find the optimal post-retirement activities and hobbies, and the provision of specific activity information, matching, and fee collection after the contract is concluded are all carried out in an integrated manner.

[0537] An "information processing device" is a device that refers to the entire system that receives input from a user, analyzes it, and provides the results.

[0538] A "generative AI model" is an artificial intelligence model that generates new information based on a user's preferences and experiences and suggests appropriate activities and hobbies.

[0539] "Input means" refers to an interface or device that allows a user to input their preferences and experiences into the system.

[0540] "Analysis means" refers to the device or software that uses a generative AI model to analyze the user's input information and execute the process of listing activities and hobbies.

[0541] "Refinement methods" refers to the processes or devices used to further refine the activities and hobbies listed by the generative AI model based on persona analysis.

[0542] "Information acquisition means" refers to a device or software for acquiring information related to a narrowed-down activity or hobby from a database.

[0543] "Providing means" refers to an interface or device that provides the acquired information to the user and displays it in a form that the user can intuitively understand.

[0544] "Matching means" refers to a device or software for matching users with related stores or services.

[0545] The term "fee collection means" refers to a device or software for collecting a fee when a contract is concluded between a user and a store or service.

[0546] "Persona analysis" refers to an analytical method for selecting the most suitable activities and hobbies based on a user's attributes and preferences.

[0547] A "database" refers to a system or storage that stores related information and retrieves that information when needed.

[0548] System Overview

[0549] The present invention relates to an information processing device that uses a generative AI model to suggest post-retirement activities based on personal preferences and experiences. This device is implemented using a user terminal, a server, and related databases. Specific operations are described below.

[0550] Hardware and software used

[0551] This system uses the following hardware and software.

[0552] User device: An internet-connected device such as a smartphone, tablet, or PC.

[0553] Server: High performance computing server, cloud server.

[0554] Database: A relational database that stores user information and activity information.

[0555] Generative AI model: A neural network model that performs analysis based on user information.

[0556] Persona analysis software: Dedicated software for conducting persona analysis.

[0557] Communication protocol: Secure data communication using HTTP / HTTPS.

[0558] Specific actions

[0559] 1. A user logs in from a terminal

[0560] Users log in using a web browser or a dedicated app and enter information such as hobbies and experiences.

[0561] 2. Sending input information to the server

[0562] The data entered by the user is sent from the terminal to the server, where it is encrypted and sent securely.

[0563] 3. Analysis of Information

[0564] The server inputs the received information into a generative AI model for analysis, which then lists appropriate activities and hobbies based on the user's data.

[0565] 4. Narrowing down through persona analysis

[0566] The server uses persona analysis to narrow down the list obtained from the generative AI model and determine the most suitable activity for the user.

[0567] 5. Obtaining related information

[0568] The server retrieves information related to the determined activity from a database, including local activity clubs, events, classes, etc.

[0569] 6. Provision of Information

[0570] The server transmits the acquired information to the user terminal and displays it in a format that the user can intuitively understand.

[0571] 7. Activity Selection and Planning

[0572] The user plans their Second Life based on the displayed information. The user selects activities that interest them from the suggested activities and creates a plan.

[0573] 8. Matching

[0574] If necessary, the server matches the user with relevant stores and services, allowing the user to actually experience the suggested activities.

[0575] 9. Contracts and Fee Collection

[0576] When a contract is concluded between the user and the store or service, the server collects a fee. The contract details are managed within the system.

[0577] Specific examples

[0578] Below are some specific examples and prompts:

[0579] Specific examples

[0580] The user enters into the device, "My hobby is gardening, I used to work in sales, and I'm interested in outdoor activities and community activities."

[0581] The device sends this information to the server.

[0582] The server passes the data to a generative AI model for analysis, and lists options such as "joining a local gardening club" and "joining a nearby cooking class."

[0583] The server conducted a persona analysis and specifically selected "joining a local gardening club" and "joining a nearby cooking class."

[0584] The server retrieves from a database information about stores and services related to the proposed activity, examples of which include "gardening club details" and "cooking class schedules."

[0585] The server sends the acquired information to the user's terminal and displays it.

[0586] Prompt Sentence Examples

[0587] "Design a system that uses generative AI models to suggest optimal retirement activities and hobbies based on a user's interests and experiences."

[0588] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0589] System program processing flow

[0590] Step 1:

[0591] The user logs in from their device. They access the login page using a web browser or a dedicated app and enter their user ID and password. After successfully logging in, the user enters information such as their preferences, past work history, and areas of interest. This input information becomes the initial input data for the system.

[0592] Input: User ID, password, preferences, work history, areas of interest

[0593] Output: Login success flag, input information data

[0594] Step 2:

[0595] The information entered by the user is sent from the terminal to the server. During transmission, the data is encrypted and securely transferred to the server.

[0596] Input: Input information data

[0597] Output: A confirmation message sent to the server

[0598] Step 3:

[0599] The server inputs the received information into a generative AI model for analysis. The generative AI model then lists appropriate activities and hobbies based on the user's data. Specifically, it generates the most suitable activity candidates for the user based on data such as hobbies and work history.

[0600] Input: User-entered information data

[0601] Output: List of potential activities

[0602] Step 4:

[0603] The server inputs the list obtained from the generated AI model into persona analysis software to narrow down the list. From the list of candidate activities, persona analysis further selects the activity that best suits the user's attributes and preferences.

[0604] Input: List of possible activities

[0605] Output: A filtered list of activities

[0606] Step 5:

[0607] The server retrieves information related to the determined activity from a database, including local activity clubs, events, courses, etc. It performs a database search to retrieve the latest information related to the proposed activity.

[0608] Input: A filtered list of activities

[0609] Output: Details related to the activity

[0610] Step 6:

[0611] The server sends the acquired information to the user's device and displays it in a format that the user can intuitively understand. Specifically, the server organizes the information, converts it into a format suitable for the user interface, and then sends it.

[0612] Input: Details related to the activity

[0613] Output: Information displayed on the user's terminal

[0614] Step 7:

[0615] The user plans their Second Life based on the displayed information. They select activities that interest them from the suggested activities and formulate a specific plan. The selected information is fed back to the server.

[0616] Input: User-selected activity

[0617] Output: User selection information

[0618] Step 8:

[0619] The server matches the user with relevant stores and services as needed based on the user's selection information, allowing the user to actually experience the suggested activities.

[0620] Input: User selection information

[0621] Output: Matching results

[0622] Step 9:

[0623] When a contract is concluded between the user and the store or service, the server collects the fee. Details of the contract and fee are managed within the system, and a confirmation message is sent to the user and the store.

[0624] Input: Contract conclusion information

[0625] Output: Fee collection and confirmation message

[0626] The above is the specific processing flow of the program of this system.

[0627] (Application example 1)

[0628] 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."

[0629] To enrich the lives of seniors after retirement, there is a need for technology that not only suggests activities and hobbies suitable for seniors, but also provides new ways to enjoy themselves through dining experiences. However, existing systems are limited in the activities and hobbies they suggest based on the user's preferences and experience, making it difficult to translate these suggestions into concrete actions, particularly those such as cooking at home or participating in local cooking events. In addition, arranging ingredients and cooking equipment is complicated, and a simple method for doing this is needed.

[0630] 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.

[0631] In this invention, the server includes an input means for a user to input their preferences and experiences, an analysis means for analyzing the user's input information using a generative AI model to list appropriate activities and hobbies and to list recommended recipes and events to participate in, a narrowing down means for narrowing down the listed activities, hobbies, recommended recipes and events to participate in based on persona analysis, an information acquisition means for acquiring information related to the narrowed down activities, hobbies, recommended recipes and events to participate in, and a provision means for providing the acquired information to the user. This enables users to easily find activities and dining experiences that are best suited to their hobbies and experiences, and to easily arrange the ingredients and cooking utensils for them.

[0632] text

[0633] "Personal preferences and experiences" refers to information such as the user's specific interests, past work history, and areas of interest.

[0634] A "generative AI model" is an artificial intelligence model that analyzes input data and generates optimal suggestions.

[0635] The "input means for the user to input his / her preferences and experiences" is an interface that allows the user to input his / her preferences and experiences into the terminal.

[0636] "Analysis means" refers to a device or software that uses a generative AI model to analyze the user's input information and list appropriate activities, hobbies, recommended recipes, and events to participate in.

[0637] "Persona analysis" is an analytical method for narrowing down the best proposals for a specific target user group based on a typical user profile.

[0638] A "refinement tool" is a device or software that has the ability to optimize activities, hobbies, recommended recipes, or events to attend based on persona analysis.

[0639] The "information acquisition means" is a device or software that has the function of acquiring information related to the narrowed-down activities, hobbies, recommended recipes, and events to attend from a database or external information source.

[0640] The "providing means" is a device or software that has the function of providing the acquired information to the user and displaying it on the user terminal.

[0641] A "delivery means" is a device or software that allows a user to order ingredients and cooking utensils they need and arrange for their delivery.

[0642] text

[0643] The present invention relates to a system that provides a function for proposing post-retirement activities and dining experiences based on a user's preferences and experiences, and delivering the ingredients and cooking utensils required for those activities.

[0644] The system includes the following main components:

[0645] 1. An input method for users to input their preferences and experiences

[0646] 2. A method of analysis that uses a generative AI model to analyze user input and produce a list of appropriate activities, hobbies, recommended recipes, and events to attend.

[0647] 3. A filter to narrow down the activities, hobbies, recommended recipes, and events to attend based on the persona analysis.

[0648] 4. Information acquisition methods for obtaining information related to narrowed-down activities, hobbies, recommended recipes, and events to attend

[0649] 5. Means of providing acquired information to users

[0650] 6. A way for users to have the ingredients and cooking equipment they need delivered

[0651] In terms of the actual program processing, first, the user enters their preferences, past work history, and areas of interest through the interface. This can be done using a smartphone, and React Native can be used to configure the UI. The user's input information is then sent to the server.

[0652] On the server side, a generative AI model (such as GPT-3) and its analysis results are used to create a list of suitable activities, hobbies, recommended recipes, and events to attend. The persona analysis function is then used to refine the list of suggestions. This process uses Node.js and Express as the backend and MongoDB as the database.

[0653] The server retrieves related information from the database based on the filtered information and provides it to the user. This information includes information on local club activities, cooking events, and the ingredients and cooking equipment needed for recommended recipes. Users can check this information on their smartphones and order the necessary ingredients and cooking equipment through a delivery service.

[0654] For example, if a user inputs "Hobbies: cooking, travel," "Past work experience: sales," and "Favorite ingredients: tomatoes, pasta," the server will use the generative AI model to suggest "local Italian cooking classes" and "new recipes using pasta." These suggestions are optimized based on persona analysis and displayed to the user.

[0655] An example prompt is:

[0656] "User data: Hobbies: Cooking, traveling; Past work experience: Sales; Favorite ingredients: Tomato, pasta"

[0657] "Cooking Recommendations:"

[0658] In this way, by using the system of the present invention, users can easily find activities and dining experiences that best suit their hobbies and experiences, and easily arrange the ingredients and cooking utensils for them.

[0659] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0660] text

[0661] Step 1:

[0662] Users log in to the system using a device and enter information such as their preferences, past work history, and areas of interest. The entered data is necessary to proceed to the next processing step, and the information entered here forms the basis for the entire system. Specifically, a smartphone is used, and the UI is built using React Native.

[0663] Step 2:

[0664] The terminal sends the data entered by the user to the server. This sent data is input data to be analyzed by subsequent analysis means. Specific data content includes information such as "Hobbies: cooking, travel," "Past work history: sales," and "Favorite ingredients: tomatoes, pasta."

[0665] Step 3:

[0666] The server receives the input data and feeds it into a generative AI model (such as GPT-3) that analyzes the user's data and lists appropriate activities, hobbies, recommended recipes, and events to attend. During the analysis process, the generative AI model treats the input data as prompts.

[0667] Step 4:

[0668] Using the list data obtained from the generative AI model, the server performs persona analysis, which optimizes the listed proposals for specific target users. In this step, data is narrowed down based on a specific persona profile, and the proposals that are most suitable for the user are selected.

[0669] Step 5:

[0670] The server retrieves information related to the user's activities, hobbies, recommended recipes, and events from a database. This information includes details of local clubs, cooking events, and ingredients and utensils used in recipes. This data is retrieved using a database such as MongoDB.

[0671] Step 6:

[0672] The server then sends the acquired information to the user's device and provides it in a format that the user can intuitively understand. Here, the information is displayed on a user interface, allowing the user to check specific proposals.

[0673] Step 7:

[0674] Users select from suggested activities, hobbies, and dining experiences, and then order ingredients and cooking equipment via delivery services. The ordering process is completed by the user on their device, and the server sends the order data to the delivery service. Once the order is confirmed, the desired items are delivered to the user.

[0675] Step 8:

[0676] The server collects a fee when a contract is concluded between the user and the delivery service. This fee collection is performed automatically, and financial transactions between the user and the service provider are carried out smoothly.

[0677] 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.

[0678] This invention relates to an information processing system that combines an information processing device using a generative AI model that suggests post-retirement activities based on personal preferences and experience with an emotion engine that recognizes the user's emotions and reflects them in the activity suggestions. This system is implemented using a user terminal, a server, and devices and related databases required for emotion recognition. The specific operations of the system's program processing are explained below in natural language.

[0679] System Overview

[0680] The system uses a generative AI model and an emotion engine to analyze a user's personal information and suggest optimal Second Life activities and hobbies. The system has the following key features:

[0681] 1. An "input method" that allows users to input their personal preferences and work experience.

[0682] 2. "Analysis method" that analyzes user input information using a generative AI model and lists appropriate activities and hobbies.

[0683] 3. "Emotion recognition means" that recognizes the user's emotions in real time and reflects them in the analysis results.

[0684] 4. "Refining methods" to narrow down the activities and hobbies listed based on persona analysis.

[0685] 5. "Means of information acquisition" to obtain information related to narrowed-down activities and hobbies.

[0686] 6. "Means of provision" that provides the acquired information to the user and performs matching as necessary.

[0687] Program processing

[0688] The specific operation is described below.

[0689] 1. A user logs in from a terminal

[0690] A user logs in using a specific interface and inputs information about their interests, experiences, and emotions. Specifically, the user inputs their hobbies, past work history, areas of interest, and current emotional state.

[0691] 2. Sending input information to the server

[0692] The data entered by the user is transmitted from the terminal to the server.

[0693] 3. Analysis of Information

[0694] The server inputs the received information into a generative AI model for analysis. The generative AI model generates a list of appropriate activities and hobbies based on the user's data. For example, it might list information such as "joining a gardening club" or "attending cooking classes."

[0695] 4. Emotion Recognition by Emotion Engine

[0696] The emotion engine recognizes the user's emotional data in real time and further refines the activities and hobbies listed by the analysis means based on the emotional data. For example, if the user is feeling stressed, relaxing activities will be prioritized.

[0697] 5. Narrowing down through persona analysis

[0698] The server further analyzes the information obtained from the emotion engine using a persona analysis function to determine the most appropriate activity for the user.

[0699] 6. Obtaining related information

[0700] The server retrieves information related to the determined activity from a database, including local activity clubs, events, classes, etc.

[0701] 7. Provision of Information

[0702] The server sends the acquired information to the user's terminal and displays it, allowing the user to create a specific activity plan while referring to the displayed information.

[0703] 8. Activity Selection and Planning

[0704] Based on the displayed information, users can plan their Second Life by taking into account suggested activities and hobbies. For example, a user may decide to join a gardening club and create a schedule for it.

[0705] 9. Matching

[0706] The server then matches the user with relevant stores and services as needed, providing appropriate contact information and detailed information about the activities the user is interested in. At this stage, a point of contact between the user and the store or service is created.

[0707] 10. Contracts and Fee Collection

[0708] When a contract is concluded between a user and a store or service, the server collects a fee. This fee is based on the success of the introduction or match and is used to fund the operation of the service.

[0709] Specific examples

[0710] Step 1-2: Enter user information

[0711] The user types into the device, "My hobby is gardening, and I used to work in sales. I'm interested in outdoor activities and community activities, but recently I've been wanting to do something more relaxing."

[0712] The device sends this information to the server.

[0713] Step 3: Analyze the information

[0714] The server passes the data to the generative AI model for analysis.

[0715] The generative AI model lists activities such as "joining a local gardening club" and "joining a nearby cooking class."

[0716] Step 4: Emotion Recognition with the Emotion Engine

[0717] The emotion engine recognizes the user's emotional data in real time as they input, and prioritizes relaxing activities (e.g., gardening) when stress levels are high.

[0718] Step 5: Persona analysis

[0719] The server conducted a persona analysis and specifically recommended "joining a local gardening club."

[0720] Step 6: Obtain relevant information

[0721] The server retrieves details and activity schedules of local gardening clubs from a database.

[0722] Step 7: Provide information

[0723] The server sends the acquired information to the user's terminal and displays it.

[0724] Step 8: Select and plan your activities

[0725] A user decides to join a gardening club and makes a schedule for it.

[0726] Step 9: Matching

[0727] The server matches users with gardening clubs and provides contact information and details.

[0728] Step 10: Closing the deal and collecting fees

[0729] The user enters into a contract with the gardening club, and the server collects the fee.

[0730] In this way, the system can suggest activities and hobbies that seniors can pursue to live a fulfilling life after retirement, and can also use the emotion engine to make optimal suggestions based on the user's emotions. This makes it possible to provide services that meet individual needs and increase user satisfaction.

[0731] The processing flow will be explained below.

[0732] Step 1:

[0733] The user logs in from a terminal and uses a specific interface to input their preferences, experiences, and current emotional state. For example, they input their hobbies (gardening, cooking), past work history (sales), areas of interest (outdoors, local activities), and current feelings (wanting to relax).

[0734] Step 2:

[0735] The device sends the user's input information, including information about the emotional state, to the server.

[0736] Step 3:

[0737] The server inputs the received information into a generative AI model for analysis. The generative AI model analyzes the user's preferences and experience data and lists appropriate Second Life activities and hobbies. For example, it might list "join a gardening club" or "attend a cooking class."

[0738] Step 4:

[0739] The server uses an emotion engine to recognize the user's emotional data in real time as they input. The emotion engine then refines the activities and hobbies listed by the generative AI model based on the emotional data. For example, if the user is in the mood to relax, "joining a gardening club" will be prioritized.

[0740] Step 5:

[0741] The server performs persona analysis and further analyzes the information obtained from the emotion engine to determine the most suitable activities for the user. Persona analysis selects the best suggestions based on the user's detailed characteristics.

[0742] Step 6:

[0743] The server retrieves information related to the determined activity from a database, such as details about a local gardening club or a cooking class schedule.

[0744] Step 7:

[0745] The server sends the acquired information to the user's terminal and displays it on the screen. The user can select various activities based on the displayed information.

[0746] Step 8:

[0747] Based on the displayed information, the user plans their Second Life by taking into account the suggested activities and hobbies. For example, the user decides to "join a gardening club" and adjusts their schedule accordingly.

[0748] Step 9:

[0749] The server will match the user with relevant businesses and services as needed, for example if the user is interested in a gardening club, providing contact details and details on how to join.

[0750] Step 10:

[0751] When a contract is concluded between a user and a store or service, the server collects a fee. This fee is based on the success of the service introduction and matching, and is used to fund the system's operations.

[0752] Through these processing steps, the system can suggest activities and hobbies that seniors can pursue to lead fulfilling lives after retirement, and use the emotion engine to make optimal suggestions based on the user's emotions. Furthermore, by supporting users to start specific activities, the system can increase overall satisfaction.

[0753] Example 2

[0754] 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."

[0755] When suggesting post-retirement activities and hobbies, it is difficult to provide optimal options while appropriately considering the user's personal information and emotions. Furthermore, there is a need to reduce the effort required to obtain specific information about activities that interest users and to support them in starting activities smoothly. In particular, if suggestions do not reflect the user's emotional state, user satisfaction will decrease, and a system that solves this problem is needed.

[0756] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0757] In this invention, the server includes: an input means for a user to input information about their preferences, experiences, and emotions; a communication means for transmitting the input information to the server; an analysis means for analyzing the user's input information using a generative AI model and listing appropriate activities and hobbies; an emotion recognition means for recognizing the user's emotions and reflecting them in the analysis results; a narrowing down means for narrowing down the listed activities and hobbies based on persona analysis; an information acquisition means for acquiring information related to the narrowed down activities and hobbies; a provision means for providing the acquired information to the user; a matching means for matching the user with relevant stores and services; and a fee collection means for collecting a fee when a contract is concluded between the user and a store or service. This makes it possible to suggest optimal post-retirement activities and hobbies based on the user's individual preferences and emotions, allowing them to start activities smoothly, thereby increasing user satisfaction and improving the convenience of the service.

[0758] "Input means" refers to an interface through which a user inputs information about preferences, experiences, and emotions.

[0759] "Communication means" refers to a data communication function for transmitting information entered by the user to the server.

[0760] "Analysis means" refers to the function that uses a generative AI model to analyze the user's input information and list appropriate activities and hobbies.

[0761] "Emotion recognition means" refers to a function that recognizes the user's emotional state in real time and reflects the results in the analysis results.

[0762] "Refinement tools" refers to the ability to narrow down the activities and hobbies listed based on persona analysis.

[0763] "Information acquisition means" refers to the function of acquiring information related to narrowed-down activities and hobbies from a database.

[0764] "Providing means" refers to a function that provides the acquired information to the user and displays it on the interface.

[0765] "Matching means" refers to a function that matches users with related stores and services.

[0766] The "fee collection means" refers to a function for collecting a fee when a contract is concluded between a user and a store or service.

[0767] The present invention relates to an information processing system that suggests post-retirement activities based on a user's preferences, experiences, and emotions. This system is implemented using a user terminal, a server, an emotion recognition device, and related databases. The specific configuration and operation of the present invention are described in detail below.

[0768] The system includes an "input means" through which a user inputs information about preferences, experiences, and emotions. The input is performed through a terminal interface, such as a text box or drop-down menu, and is implemented using a common computing device, such as a smartphone or PC.

[0769] The information entered by the user is sent to the server via a "communication method." This communication method is realized via network communication, and usually uses the HTTPS protocol. This ensures that the input data is sent securely to the server.

[0770] The server uses an "analysis tool" to pass the user's input information to a generative AI model for analysis. The generative AI model may use Python-based Pytorch or OpenAI's GPT-3, for example. This analysis generates a list of appropriate activities and hobbies based on the user's preferences and experience.

[0771] The system also includes an "emotion recognition mechanism" that uses Microsoft's Emotion API or proprietary emotion recognition algorithms to recognize the user's emotional state in real time. This emotional data is sent to a server and reflected in the analysis results. If the user is feeling stressed, relaxation activities will be prioritized.

[0772] Next, a "refining method" further refines the best activities and hobbies using persona analysis, for example using Scikit-learn or TensorFlow. The server identifies the activities that best fit the user's profile and passes that information on to the next step.

[0773] Using the "information retrieval means," the server retrieves information related to the determined activity or hobby from the database. This information may include local activity clubs, events, classes, etc. Specifically, the server issues an SQL query to retrieve the necessary information from the database.

[0774] The acquired information is sent to the user terminal by the "providing means" and displayed on the user's interface. This allows the user to make specific plans based on the suggested activities. For example, the user may decide to join a gardening club and create a schedule for it.

[0775] Furthermore, the server uses a "matching method" to match users with relevant stores and services. Specifically, it uses a matching algorithm to provide users with the most suitable contact information and detailed information. This information is sent via email, SMS, or in-app notifications.

[0776] Finally, when a contract is concluded between the user and the store or service, the server collects the fee using the "fee collection means." This fee is processed using a payment system (for example, PayPal API or Stripe API) and becomes operating funds for the service.

[0777] Specific examples

[0778] A user logs in using a device and enters information such as, "My hobby is gardening, and I used to work in sales. I'm interested in outdoor activities and local activities, but recently I've been wanting to do something more relaxing." This information is sent to the server and analyzed by the generative AI model. The generative AI model then lists activities such as "joining a local gardening club" and "joining a nearby cooking class."

[0779] The emotional state of the user is also checked using an emotion engine; for example, if the stress level is high, "relaxing activities" are prioritized. Persona analysis is performed to narrow down the activities that are most suitable for the user. The server retrieves detailed information and activity schedules of local gardening clubs from a database and displays them on the user's device. The user decides to join the gardening club and creates a schedule for it.

[0780] The server matches users with gardening clubs, provides contact information and details, and finally, the user enters into a contract with the gardening club, and the server collects the commission.

[0781] This system makes it possible to suggest optimal post-retirement activities and hobbies based on the user's individual tastes and feelings, allowing them to smoothly start their activities, thereby increasing user satisfaction and improving the convenience of the service.

[0782] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0783] Step 1:

[0784] User logs in from terminal

[0785] The user inputs information about their preferences, experiences, and emotions. The device receives this input information and formats the data for transmission. The input data (e.g., "I enjoy gardening as a hobby and used to work in sales. I'm interested in outdoor activities and community activities, but recently I've been wanting to do something more relaxing") is prepared as a transmission request. In concrete terms, the user opens a web browser, accesses a login page, enters their username and password, and clicks the login button.

[0786] Step 2:

[0787] Sending input information to the server

[0788] The input data generated by the device is sent to the server using the HTTPS protocol. An encrypted channel is used for communication. The input data is decoded on the server side and prepared for further processing. Specifically, the user enters information into the input form and clicks the "Submit" button. At that time, the data is sent asynchronously using an AJAX request.

[0789] Step 3:

[0790] Analysis of information

[0791] The server inputs the user's input information into a generative AI model. The generative AI model (e.g., Python's Pytorch or GPT-3) is used to analyze the data and list appropriate activities and hobbies. The input data is passed to the generative AI model, and the analysis results, which are listed as activities and hobbies, are generated in JSON format. Specifically, a Python script is executed, the generative AI model analyzes the data, and the results are output.

[0792] Step 4:

[0793] Emotion recognition by emotion recognition means

[0794] The server receives emotion recognition data (e.g., from a facial recognition camera or Emotion API) and evaluates the user's emotional state. Based on this, the analysis results are prioritized. The emotion data is processed in real time and indicators such as stress levels are calculated. Specifically, the emotion recognition device collects emotion data, and the server analyzes it.

[0795] Step 5:

[0796] Narrowing down through persona analysis

[0797] The server uses the persona analysis function to further narrow down the listed activities and hobbies based on the analysis results and emotional data. A persona analysis algorithm (e.g., Scikit-learn or TensorFlow) is run to determine the best options. The input data and analysis results are passed to the persona analysis algorithm, which outputs the narrowed down results. Specifically, the persona analysis script is run on the server.

[0798] Step 6:

[0799] Obtaining related information

[0800] The server retrieves information related to the narrowed-down activities and hobbies from the database. It issues an SQL query to retrieve the target data and formats it as a response. The narrowed-down activities and hobbies are used in the database query, and the relevant information is returned in JSON format. Specifically, the server executes the SQL query and retrieves the information from the database.

[0801] Step 7:

[0802] Providing information

[0803] The server sends the retrieved relevant information to the user's device and displays it on the user's interface. The data is visually organized and displayed using HTML and CSS, allowing the user to review the information and make decisions. Specifically, the server sends the retrieved data in JSON format to the device, where it is displayed on the device's interface.

[0804] Step 8:

[0805] Activity selection and planning

[0806] The user selects activities and hobbies based on the displayed information and creates a specific plan. The user's selection is passed to the next processing step. On the device interface, the user clicks the "Join" button and registers the schedule in conjunction with the calendar app. Specifically, the device automatically generates a schedule based on the activities selected by the user.

[0807] Step 9:

[0808] Matching implementation

[0809] The server uses a matching algorithm to match the user with relevant stores and services. The server provides optimal contact information and detailed information. The matching results are generated and notified to the user. Specifically, the server executes the algorithm and sends the appropriate contact information to the user's device.

[0810] Step 10:

[0811] Contracts and fee collection

[0812] When a contract is concluded between the user and the store or service, the server records that information and collects the fee. The fee is processed using a payment system (e.g., PayPal API or Stripe API). The information about the conclusion of the contract is passed as input data to the payment system, which then processes the fee. Specifically, the server calls the payment API and completes the fee transaction.

[0813] (Application example 2)

[0814] 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."

[0815] There is a lack of methods to suggest optimal activities for retirement based on personal preferences and experiences. There is also a lack of technology that suggests appropriate activities while taking into account the user's emotions. Furthermore, there is a lack of systems that allow users to easily access and schedule suggested activities. Therefore, there is a need for methods to enrich retirement life.

[0816] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an emotion recognition means for recognizing the user's emotions and reflecting them in the proposals, an input means for the user to input their preferences and experiences, an analysis means for analyzing the user's input information using a generative AI model and listing appropriate activities and hobbies, a narrowing down means for narrowing down the listed activities and hobbies based on persona analysis, an information acquisition means for acquiring information related to the narrowed down activities and hobbies, a provision means for providing the acquired information to the user, a notification means for notifying the user of recommended activities, and a schedule setting means for setting a schedule based on the proposed activities. This makes it possible to propose optimal post-retirement activities taking into account the user's personal information and emotions.

[0817] The "input means" is an interface that allows the user to input their own preferences and experiences.

[0818] The "analysis means" is a device that uses a generative AI model to analyze the user's input information and list appropriate activities and hobbies.

[0819] A "narrowing tool" is a device that has the function of further narrowing down the activities and hobbies listed based on persona analysis.

[0820] The "information acquisition means" is a device that acquires information related to the narrowed-down activities and hobbies from a database.

[0821] The "providing means" is a device that provides the acquired information to the user.

[0822] An "emotion recognition means" is a device that recognizes the user's emotions in real time and reflects them in suggestions.

[0823] The "notification means" is a device that has the function of notifying the user of recommended activities.

[0824] A "schedule setting means" is a device that has the function of setting a schedule for a user based on suggested activities.

[0825] To implement the present invention, a system including emotion recognition means, input means, analysis means, narrowing means, information acquisition means, provision means, notification means, and schedule setting means is required.

[0826] System configuration and operation

[0827] The system consists of a user terminal, a server, and related databases. The operation of each component of the system is described in detail below.

[0828] User terminal

[0829] First, users log in to the system using their device (smartphone or tablet). After logging in, they can enter information about their preferences and experiences. An input method is provided, and an interface is prepared for users to enter details about their hobbies, work history, interests, etc.

[0830] server

[0831] The server includes the following means:

[0832] 1. Input Method

[0833] It provides an interface for users to input their preferences and experiences.

[0834] 2. Analysis method

[0835] The server receives the information entered by the user and analyzes it using a generative AI model, resulting in a list of activities and hobbies that are best suited to the user.

[0836] 3. Emotion recognition means

[0837] It includes a software module for recognizing users' emotions in real time, and this emotional data is reflected in the analysis results, improving the accuracy of the proposal activities.

[0838] 4. Narrowing methods

[0839] Based on persona analysis, narrow down the list of activities and hobbies generated to the most suitable items.

[0840] 5. Information acquisition means

[0841] It has the ability to retrieve information related to narrowed-down activities and hobbies (e.g., location, time, price) from a database.

[0842] 6. Means of provision

[0843] This is a means for providing the acquired information to the user. Specifically, it sends the information to the user's terminal and displays it.

[0844] 7. Means of notification

[0845] Notify users about recommended activities.

[0846] 8. Scheduling Methods

[0847] It is a way to set a schedule for the user based on suggested activities, and it also works with notifications to set reminders.

[0848] Hardware and Software

[0849] Emotion Recognition Engine: A software module for recognizing user emotions in real time.

[0850] Generative AI model: A model that analyzes user input and lists optimal activities and hobbies.

[0851] Database: A database that stores information about activities and hobbies and is accessed by information retrieval methods.

[0852] Specific examples

[0853] Suppose a user inputs "cooking" as their hobby, "sales" as their work history, "handicrafts" as their interest, and "slightly tired" as their current emotional state. This information is sent to the server and analyzed by the analysis means. The generative AI model lists activities such as "nearby handicraft classes" and "cooking workshops." The emotion recognition means confirms the emotion of "slightly tired," and prioritizes the relaxing "handicraft classes." The narrowing means selects more accurate activities, and the information acquisition means acquires specific location, time, and price information from the database. The provision means displays the information on the user's terminal, and the notification means notifies the user of recommended activities. Finally, the schedule setting means allows the user to set a schedule for the handicraft classes.

[0854] Prompt Sentence Examples

[0855] User Preferences: ["Cooking", "Crafts"]

[0856] User Experience: "Sales Job"

[0857] Current Emotion: "Slightly tired"

[0858] The above is a specific embodiment for carrying out the invention.

[0859] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0860] Step 1:

[0861] A user logs in to the system using a device. The user accesses the app's login screen and completes the login by entering their personal authentication information. The input data is the user's ID and password, and the output is access permission.

[0862] Step 2:

[0863] The user inputs their interests, experiences, and current emotional state into the terminal. Specifically, they input information such as "cooking" as a hobby, "sales experience," and an interest in "handicrafts." They also input "slightly tired" as their current emotional state. This information is sent to the server as input data.

[0864] Step 3:

[0865] The server inputs the received user information into a generative AI model for analysis. The input data is the user's preferences, experiences, and emotional state, and the output is a list of activities and hobbies that are best suited to the user. The generative AI model analyzes this data and lists activities such as "nearby craft classes" and "cooking workshops."

[0866] Step 4:

[0867] The server analyzes the user's emotional data using an emotion recognition means. The input data is the user's current emotional state, and the output is a list of activities that take emotions into account. Reflecting the emotional data of "slightly tired," the server prioritizes the suggestion of "sewing classes" to relax.

[0868] Step 5:

[0869] The server uses a refinement method to further refine the generated activity list based on persona analysis. The input data is the activity list and emotion recognition data, and the output is the refined activities that are most suitable for the user. Here, "Handicraft class" is particularly recommended from the refined list.

[0870] Step 6:

[0871] The server uses the information acquisition means to acquire detailed information related to the narrowed-down activities from the database. Specifically, it acquires information such as the location, time, and fee of the handicraft class. The input data is the narrowed-down activity name, and the output is the detailed information.

[0872] Step 7:

[0873] The server provides the acquired detailed information to the user terminal. Using the providing means, information such as the location, time, and fee of the handicraft class is displayed on the user terminal. The input data is the detailed information, and the output is the information displayed to the user.

[0874] Step 8:

[0875] The server uses the notification mechanism to notify the user about the recommended activity. The input data is the information provided, and the output is the notification content. The user receives a notification confirming "attend a sewing class."

[0876] Step 9:

[0877] The user selects the suggested activities and sets the schedule. The user confirms the dates and times of the craft classes and inputs the schedule. The input data is the user's schedule information, and the output is the scheduled information.

[0878] Step 10:

[0879] The server uses the schedule setting means to check the user's schedule setting and activate the reminder function, so that the user receives reminder notifications based on the set schedule. The input data is schedule information, and the output is reminder notifications.

[0880] The above is the specific processing flow of the present invention. Through this series of steps, the user can find the most suitable activity based on their personal tastes and feelings, and live a comfortable life after retirement.

[0881] 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.

[0882] 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.

[0883] 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.

[0884] [Third embodiment]

[0885] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0886] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0887] 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).

[0888] 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.

[0889] 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.

[0890] 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).

[0891] 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.

[0892] 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.

[0893] 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.

[0894] 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.

[0895] 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.

[0896] 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."

[0897] This invention relates to an information processing system that uses a generative AI model to suggest post-retirement activities based on personal preferences and experiences. This system is implemented using a user terminal, a server, and related databases. The specific operations of the system's program processing are explained in natural language below.

[0898] System Overview

[0899] The system uses a generative AI model to analyze a user's personal information and suggest optimal Second Life activities and hobbies. The system has the following key features:

[0900] 1. An "input method" that allows users to input their personal preferences and work experience.

[0901] 2. "Analysis means" that analyzes the information entered by the user and lists appropriate activities and hobbies.

[0902] 3. A "refining method" that narrows down the listed activities and hobbies based on persona analysis.

[0903] 4. "Means of information acquisition" to obtain information related to narrowed-down activities and hobbies.

[0904] 5. "Means of provision" that provides the acquired information to the user and performs matching as necessary.

[0905] Program processing

[0906] The specific operation is described below.

[0907] 1. A user logs in from a terminal

[0908] A user logs in using a specific interface and inputs information such as interests and experiences. Specifically, the user inputs information such as hobbies, past work history, and fields of interest.

[0909] 2. Sending input information to the server

[0910] The data entered by the user is transmitted from the terminal to the server.

[0911] 3. Analysis of Information

[0912] The server inputs the received information into a generative AI model for analysis, which then generates a list of appropriate activities and hobbies based on the user's data.

[0913] 4. Narrowing down through persona analysis

[0914] The server uses persona analysis to narrow down the list obtained from the generative AI model and determine the most suitable activity for the user.

[0915] 5. Obtaining related information

[0916] The server retrieves information related to the determined activity from a database, including local activity clubs, events, classes, etc.

[0917] 6. Provision of Information

[0918] The server transmits the acquired information to the user terminal and displays it in a format that the user can intuitively understand.

[0919] 7. Activity Selection and Planning

[0920] The user plans their second life based on the displayed information.

[0921] 8. Matching

[0922] If necessary, the server matches the user with relevant stores and services, allowing the user to actually experience the suggested activities.

[0923] 9. Contracts and Fee Collection

[0924] When a contract is concluded between the user and the store or service, the server collects a fee.

[0925] Specific examples

[0926] Step 1-2: Enter user information

[0927] The user enters into the device, "My hobby is gardening, I used to work in sales, and I'm interested in outdoor activities and community activities."

[0928] The device sends this information to the server.

[0929] Step 3: Analyze the information

[0930] The server passes the data to the generative AI model for analysis.

[0931] The generative AI model lists activities such as "joining a local gardening club" and "joining a nearby cooking class."

[0932] Step 4: Persona Analysis

[0933] The server conducted a persona analysis and specifically selected "joining a local gardening club" and "joining a nearby cooking class."

[0934] Step 5: Obtain relevant information

[0935] The server retrieves from a database information about stores and services related to the proposed activity, such as details of a gardening club or a cooking class schedule.

[0936] Step 6: Provide information

[0937] The server sends the acquired information to the user's terminal and displays it.

[0938] Steps 7-9: Activity selection and contract formation

[0939] The user makes plans based on the suggested activities and, if necessary, enters into contracts with stores and services.

[0940] If the contract is concluded, the server collects the fee.

[0941] In this way, the system suggests activities and hobbies that will help seniors live fulfilling lives after retirement, and supports them in taking concrete actions.

[0942] The processing flow will be explained below.

[0943] Step 1:

[0944] A user logs in from a device. The user enters their profile information, interests, past work experience, etc. This information includes hobbies (e.g., gardening, cooking), past work experience (e.g., sales), and areas of interest (e.g., outdoors, local activities).

[0945] Step 2:

[0946] The terminal transmits the user's input information to the server.

[0947] Step 3:

[0948] The server inputs the received information into a generative AI model for analysis. As a result of this analysis, a list of activities and hobbies that are best suited to the user is generated. For example, information such as "joining a gardening club" or "taking a cooking class" may be listed.

[0949] Step 4:

[0950] The server uses persona analysis to narrow down the list obtained from the generative AI model and determine the activities that are most suitable for the user. For example, persona analysis may specifically recommend "joining a local gardening club" and "attending a nearby cooking class."

[0951] Step 5:

[0952] The server retrieves information related to the determined activity from the database, including details of the activity and information on related stores and services (e.g., the activity schedule for a gardening club or the dates and times of cooking classes).

[0953] Step 6:

[0954] The server sends the acquired information to the user's terminal and displays it, allowing the user to use it as a reference when making their own plans.

[0955] Step 7:

[0956] Based on the displayed information, the user plans their Second Life by taking into account suggested activities and hobbies. For example, the user may decide to join a gardening club and create a schedule for it.

[0957] Step 8:

[0958] The server then matches the user with relevant stores and services as needed, providing appropriate contact information and detailed information about the activities the user is interested in. At this stage, a point of contact between the user and the store or service is created.

[0959] Step 9:

[0960] When a contract is concluded between a user and a store or service, the server collects a fee. This fee is based on the success of the introduction or match and is used to fund the operation of the service.

[0961] Through the above processing steps, the system can suggest activities and hobbies that will help seniors live fulfilling lives after retirement and support them in taking specific actions.

[0962] Example 1

[0963] 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."

[0964] In modern society, an increasing number of individuals wish to live fulfilling lives in their own way even after retirement. However, it is difficult to determine what activities and hobbies to choose, and it is hard to find the activities that best suit them. Furthermore, because information is scattered, it is time-consuming to obtain detailed information about specific activities. Furthermore, tasks such as matching proposed activities with actual stores and services and collecting fees after contracts are concluded are also cumbersome. There is a need for an efficient information processing device that can solve these problems.

[0965] 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.

[0966] In this invention, the server includes an input means for a user to input their preferences and experiences, an analysis means for analyzing the user's input information using a generative AI model and listing appropriate activities and hobbies, a narrowing down means for narrowing down the listed activities and hobbies based on persona analysis, an information acquisition means for acquiring information related to the narrowed down activities and hobbies, a provision means for providing the acquired information to the user, a matching means for matching the user with relevant stores and services as needed, and a fee collection means for collecting a fee when a contract is concluded between the user and a store or service. This enables the user to efficiently find the optimal post-retirement activities and hobbies, and the provision of specific activity information, matching, and fee collection after the contract is concluded are all carried out in an integrated manner.

[0967] An "information processing device" is a device that refers to the entire system that receives input from a user, analyzes it, and provides the results.

[0968] A "generative AI model" is an artificial intelligence model that generates new information based on a user's preferences and experiences and suggests appropriate activities and hobbies.

[0969] "Input means" refers to an interface or device that allows a user to input their preferences and experiences into the system.

[0970] "Analysis means" refers to the device or software that uses a generative AI model to analyze the user's input information and execute the process of listing activities and hobbies.

[0971] "Refinement methods" refers to the processes or devices used to further refine the activities and hobbies listed by the generative AI model based on persona analysis.

[0972] "Information acquisition means" refers to a device or software for acquiring information related to a narrowed-down activity or hobby from a database.

[0973] "Providing means" refers to an interface or device that provides the acquired information to the user and displays it in a form that the user can intuitively understand.

[0974] "Matching means" refers to a device or software for matching users with related stores or services.

[0975] The term "fee collection means" refers to a device or software for collecting a fee when a contract is concluded between a user and a store or service.

[0976] "Persona analysis" refers to an analytical method for selecting the most suitable activities and hobbies based on a user's attributes and preferences.

[0977] A "database" refers to a system or storage that stores related information and retrieves that information when needed.

[0978] System Overview

[0979] The present invention relates to an information processing device that uses a generative AI model to suggest post-retirement activities based on personal preferences and experiences. This device is implemented using a user terminal, a server, and related databases. Specific operations are described below.

[0980] Hardware and software used

[0981] This system uses the following hardware and software.

[0982] User device: An internet-connected device such as a smartphone, tablet, or PC.

[0983] Server: High performance computing server, cloud server.

[0984] Database: A relational database that stores user information and activity information.

[0985] Generative AI model: A neural network model that performs analysis based on user information.

[0986] Persona analysis software: Dedicated software for conducting persona analysis.

[0987] Communication protocol: Secure data communication using HTTP / HTTPS.

[0988] Specific actions

[0989] 1. A user logs in from a terminal

[0990] Users log in using a web browser or a dedicated app and enter information such as hobbies and experiences.

[0991] 2. Sending input information to the server

[0992] The data entered by the user is sent from the terminal to the server, where it is encrypted and sent securely.

[0993] 3. Analysis of Information

[0994] The server inputs the received information into a generative AI model for analysis, which then lists appropriate activities and hobbies based on the user's data.

[0995] 4. Narrowing down through persona analysis

[0996] The server uses persona analysis to narrow down the list obtained from the generative AI model and determine the most suitable activity for the user.

[0997] 5. Obtaining related information

[0998] The server retrieves information related to the determined activity from a database, including local activity clubs, events, classes, etc.

[0999] 6. Provision of Information

[1000] The server transmits the acquired information to the user terminal and displays it in a format that the user can intuitively understand.

[1001] 7. Activity Selection and Planning

[1002] The user plans their Second Life based on the displayed information. The user selects activities that interest them from the suggested activities and creates a plan.

[1003] 8. Matching

[1004] If necessary, the server matches the user with relevant stores and services, allowing the user to actually experience the suggested activities.

[1005] 9. Contracts and Fee Collection

[1006] When a contract is concluded between the user and the store or service, the server collects a fee. The contract details are managed within the system.

[1007] Specific examples

[1008] Below are some specific examples and prompts:

[1009] Specific examples

[1010] The user enters into the device, "My hobby is gardening, I used to work in sales, and I'm interested in outdoor activities and community activities."

[1011] The device sends this information to the server.

[1012] The server passes the data to a generative AI model for analysis, and lists options such as "joining a local gardening club" and "joining a nearby cooking class."

[1013] The server conducted a persona analysis and specifically selected "joining a local gardening club" and "joining a nearby cooking class."

[1014] The server retrieves from a database information about stores and services related to the proposed activity, examples of which include "gardening club details" and "cooking class schedules."

[1015] The server sends the acquired information to the user's terminal and displays it.

[1016] Prompt Sentence Examples

[1017] "Design a system that uses generative AI models to suggest optimal retirement activities and hobbies based on a user's interests and experiences."

[1018] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1019] System program processing flow

[1020] Step 1:

[1021] The user logs in from their device. They access the login page using a web browser or a dedicated app and enter their user ID and password. After successfully logging in, the user enters information such as their preferences, past work history, and areas of interest. This input information becomes the initial input data for the system.

[1022] Input: User ID, password, preferences, work history, areas of interest

[1023] Output: Login success flag, input information data

[1024] Step 2:

[1025] The information entered by the user is sent from the terminal to the server. During transmission, the data is encrypted and securely transferred to the server.

[1026] Input: Input information data

[1027] Output: A confirmation message sent to the server

[1028] Step 3:

[1029] The server inputs the received information into a generative AI model for analysis. The generative AI model then lists appropriate activities and hobbies based on the user's data. Specifically, it generates the most suitable activity candidates for the user based on data such as hobbies and work history.

[1030] Input: User-entered information data

[1031] Output: List of potential activities

[1032] Step 4:

[1033] The server inputs the list obtained from the generated AI model into persona analysis software to narrow down the list. From the list of candidate activities, persona analysis further selects the activity that best suits the user's attributes and preferences.

[1034] Input: List of possible activities

[1035] Output: A filtered list of activities

[1036] Step 5:

[1037] The server retrieves information related to the determined activity from a database, including local activity clubs, events, courses, etc. It performs a database search to retrieve the latest information related to the proposed activity.

[1038] Input: A filtered list of activities

[1039] Output: Details related to the activity

[1040] Step 6:

[1041] The server sends the acquired information to the user's device and displays it in a format that the user can intuitively understand. Specifically, the server organizes the information, converts it into a format suitable for the user interface, and then sends it.

[1042] Input: Details related to the activity

[1043] Output: Information displayed on the user's terminal

[1044] Step 7:

[1045] The user plans their Second Life based on the displayed information. They select activities that interest them from the suggested activities and formulate a specific plan. The selected information is fed back to the server.

[1046] Input: User-selected activity

[1047] Output: User selection information

[1048] Step 8:

[1049] The server matches the user with relevant stores and services as needed based on the user's selection information, allowing the user to actually experience the suggested activities.

[1050] Input: User selection information

[1051] Output: Matching results

[1052] Step 9:

[1053] When a contract is concluded between the user and the store or service, the server collects the fee. Details of the contract and fee are managed within the system, and a confirmation message is sent to the user and the store.

[1054] Input: Contract conclusion information

[1055] Output: Fee collection and confirmation message

[1056] The above is the specific processing flow of the program of this system.

[1057] (Application example 1)

[1058] 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."

[1059] To enrich the lives of seniors after retirement, there is a need for technology that not only suggests activities and hobbies suitable for seniors, but also provides new ways to enjoy themselves through dining experiences. However, existing systems are limited in the activities and hobbies they suggest based on the user's preferences and experience, making it difficult to translate these suggestions into concrete actions, particularly those such as cooking at home or participating in local cooking events. In addition, arranging ingredients and cooking equipment is complicated, and a simple method for doing this is needed.

[1060] 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.

[1061] In this invention, the server includes an input means for a user to input their preferences and experiences, an analysis means for analyzing the user's input information using a generative AI model to list appropriate activities and hobbies and to list recommended recipes and events to participate in, a narrowing down means for narrowing down the listed activities, hobbies, recommended recipes and events to participate in based on persona analysis, an information acquisition means for acquiring information related to the narrowed down activities, hobbies, recommended recipes and events to participate in, and a provision means for providing the acquired information to the user. This enables users to easily find activities and dining experiences that are best suited to their hobbies and experiences, and to easily arrange the ingredients and cooking utensils for them.

[1062] text

[1063] "Personal preferences and experiences" refers to information such as the user's specific interests, past work history, and areas of interest.

[1064] A "generative AI model" is an artificial intelligence model that analyzes input data and generates optimal suggestions.

[1065] The "input means for the user to input his / her preferences and experiences" is an interface that allows the user to input his / her preferences and experiences into the terminal.

[1066] "Analysis means" refers to a device or software that uses a generative AI model to analyze the user's input information and list appropriate activities, hobbies, recommended recipes, and events to participate in.

[1067] "Persona analysis" is an analytical method for narrowing down the best proposals for a specific target user group based on a typical user profile.

[1068] A "refinement tool" is a device or software that has the ability to optimize activities, hobbies, recommended recipes, or events to attend based on persona analysis.

[1069] The "information acquisition means" is a device or software that has the function of acquiring information related to the narrowed-down activities, hobbies, recommended recipes, and events to attend from a database or external information source.

[1070] The "providing means" is a device or software that has the function of providing the acquired information to the user and displaying it on the user terminal.

[1071] A "delivery means" is a device or software that allows a user to order ingredients and cooking utensils they need and arrange for their delivery.

[1072] text

[1073] The present invention relates to a system that provides a function for proposing post-retirement activities and dining experiences based on a user's preferences and experiences, and delivering the ingredients and cooking utensils required for those activities.

[1074] The system includes the following main components:

[1075] 1. An input method for users to input their preferences and experiences

[1076] 2. A method of analysis that uses a generative AI model to analyze user input and produce a list of appropriate activities, hobbies, recommended recipes, and events to attend.

[1077] 3. A filter to narrow down the activities, hobbies, recommended recipes, and events to attend based on the persona analysis.

[1078] 4. Information acquisition methods for obtaining information related to narrowed-down activities, hobbies, recommended recipes, and events to attend

[1079] 5. Means of providing acquired information to users

[1080] 6. A way for users to have the ingredients and cooking equipment they need delivered

[1081] In terms of the actual program processing, first, the user enters their preferences, past work history, and areas of interest through the interface. This can be done using a smartphone, and React Native can be used to configure the UI. The user's input information is then sent to the server.

[1082] On the server side, a generative AI model (such as GPT-3) and its analysis results are used to create a list of suitable activities, hobbies, recommended recipes, and events to attend. The persona analysis function is then used to refine the list of suggestions. This process uses Node.js and Express as the backend and MongoDB as the database.

[1083] The server retrieves related information from the database based on the filtered information and provides it to the user. This information includes information on local club activities, cooking events, and the ingredients and cooking equipment needed for recommended recipes. Users can check this information on their smartphones and order the necessary ingredients and cooking equipment through a delivery service.

[1084] For example, if a user inputs "Hobbies: cooking, travel," "Past work experience: sales," and "Favorite ingredients: tomatoes, pasta," the server will use the generative AI model to suggest "local Italian cooking classes" and "new recipes using pasta." These suggestions are optimized based on persona analysis and displayed to the user.

[1085] An example prompt is:

[1086] "User data: Hobbies: Cooking, traveling; Past work experience: Sales; Favorite ingredients: Tomato, pasta"

[1087] "Cooking Recommendations:"

[1088] In this way, by using the system of the present invention, users can easily find activities and dining experiences that best suit their hobbies and experiences, and easily arrange the ingredients and cooking utensils for them.

[1089] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1090] text

[1091] Step 1:

[1092] Users log in to the system using a device and enter information such as their preferences, past work history, and areas of interest. The entered data is necessary to proceed to the next processing step, and the information entered here forms the basis for the entire system. Specifically, a smartphone is used, and the UI is built using React Native.

[1093] Step 2:

[1094] The terminal sends the data entered by the user to the server. This sent data is input data to be analyzed by subsequent analysis means. Specific data content includes information such as "Hobbies: cooking, travel," "Past work history: sales," and "Favorite ingredients: tomatoes, pasta."

[1095] Step 3:

[1096] The server receives the input data and feeds it into a generative AI model (such as GPT-3) that analyzes the user's data and lists appropriate activities, hobbies, recommended recipes, and events to attend. During the analysis process, the generative AI model treats the input data as prompts.

[1097] Step 4:

[1098] Using the list data obtained from the generative AI model, the server performs persona analysis, which optimizes the listed proposals for specific target users. In this step, data is narrowed down based on a specific persona profile, and the proposals that are most suitable for the user are selected.

[1099] Step 5:

[1100] The server retrieves information related to the user's activities, hobbies, recommended recipes, and events from a database. This information includes details of local clubs, cooking events, and ingredients and utensils used in recipes. This data is retrieved using a database such as MongoDB.

[1101] Step 6:

[1102] The server then sends the acquired information to the user's device and provides it in a format that the user can intuitively understand. Here, the information is displayed on a user interface, allowing the user to check specific proposals.

[1103] Step 7:

[1104] Users select from suggested activities, hobbies, and dining experiences, and then order ingredients and cooking equipment via delivery services. The ordering process is completed by the user on their device, and the server sends the order data to the delivery service. Once the order is confirmed, the desired items are delivered to the user.

[1105] Step 8:

[1106] The server collects a fee when a contract is concluded between the user and the delivery service. This fee collection is performed automatically, and financial transactions between the user and the service provider are carried out smoothly.

[1107] 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.

[1108] This invention relates to an information processing system that combines an information processing device using a generative AI model that suggests post-retirement activities based on personal preferences and experience with an emotion engine that recognizes the user's emotions and reflects them in the activity suggestions. This system is implemented using a user terminal, a server, and devices and related databases required for emotion recognition. The specific operations of the system's program processing are explained below in natural language.

[1109] System Overview

[1110] The system uses a generative AI model and an emotion engine to analyze a user's personal information and suggest optimal Second Life activities and hobbies. The system has the following key features:

[1111] 1. An "input method" that allows users to input their personal preferences and work experience.

[1112] 2. "Analysis method" that analyzes user input information using a generative AI model and lists appropriate activities and hobbies.

[1113] 3. "Emotion recognition means" that recognizes the user's emotions in real time and reflects them in the analysis results.

[1114] 4. "Refining methods" to narrow down the activities and hobbies listed based on persona analysis.

[1115] 5. "Means of information acquisition" to obtain information related to narrowed-down activities and hobbies.

[1116] 6. "Means of provision" that provides the acquired information to the user and performs matching as necessary.

[1117] Program processing

[1118] The specific operation is described below.

[1119] 1. A user logs in from a terminal

[1120] A user logs in using a specific interface and inputs information about their interests, experiences, and emotions. Specifically, the user inputs their hobbies, past work history, areas of interest, and current emotional state.

[1121] 2. Sending input information to the server

[1122] The data entered by the user is transmitted from the terminal to the server.

[1123] 3. Analysis of Information

[1124] The server inputs the received information into a generative AI model for analysis. The generative AI model generates a list of appropriate activities and hobbies based on the user's data. For example, it might list information such as "joining a gardening club" or "attending cooking classes."

[1125] 4. Emotion Recognition by Emotion Engine

[1126] The emotion engine recognizes the user's emotional data in real time and further refines the activities and hobbies listed by the analysis means based on the emotional data. For example, if the user is feeling stressed, relaxing activities will be prioritized.

[1127] 5. Narrowing down through persona analysis

[1128] The server further analyzes the information obtained from the emotion engine using a persona analysis function to determine the most appropriate activity for the user.

[1129] 6. Obtaining related information

[1130] The server retrieves information related to the determined activity from a database, including local activity clubs, events, classes, etc.

[1131] 7. Provision of Information

[1132] The server sends the acquired information to the user's terminal and displays it, allowing the user to create a specific activity plan while referring to the displayed information.

[1133] 8. Activity Selection and Planning

[1134] Based on the displayed information, users can plan their Second Life by taking into account suggested activities and hobbies. For example, a user may decide to join a gardening club and create a schedule for it.

[1135] 9. Matching

[1136] The server then matches the user with relevant stores and services as needed, providing appropriate contact information and detailed information about the activities the user is interested in. At this stage, a point of contact between the user and the store or service is created.

[1137] 10. Contracts and Fee Collection

[1138] When a contract is concluded between a user and a store or service, the server collects a fee. This fee is based on the success of the introduction or match and is used to fund the operation of the service.

[1139] Specific examples

[1140] Step 1-2: Enter user information

[1141] The user types into the device, "My hobby is gardening, and I used to work in sales. I'm interested in outdoor activities and community activities, but recently I've been wanting to do something more relaxing."

[1142] The device sends this information to the server.

[1143] Step 3: Analyze the information

[1144] The server passes the data to the generative AI model for analysis.

[1145] The generative AI model lists activities such as "joining a local gardening club" and "joining a nearby cooking class."

[1146] Step 4: Emotion Recognition with the Emotion Engine

[1147] The emotion engine recognizes the user's emotional data in real time as they input, and prioritizes relaxing activities (e.g., gardening) when stress levels are high.

[1148] Step 5: Persona analysis

[1149] The server conducted a persona analysis and specifically recommended "joining a local gardening club."

[1150] Step 6: Obtain relevant information

[1151] The server retrieves details and activity schedules of local gardening clubs from a database.

[1152] Step 7: Provide information

[1153] The server sends the acquired information to the user's terminal and displays it.

[1154] Step 8: Select and plan your activities

[1155] A user decides to join a gardening club and makes a schedule for it.

[1156] Step 9: Matching

[1157] The server matches users with gardening clubs and provides contact information and details.

[1158] Step 10: Closing the deal and collecting fees

[1159] The user enters into a contract with the gardening club, and the server collects the fee.

[1160] In this way, the system can suggest activities and hobbies that seniors can pursue to live a fulfilling life after retirement, and can also use the emotion engine to make optimal suggestions based on the user's emotions. This makes it possible to provide services that meet individual needs and increase user satisfaction.

[1161] The processing flow will be explained below.

[1162] Step 1:

[1163] The user logs in from a terminal and uses a specific interface to input their preferences, experiences, and current emotional state. For example, they input their hobbies (gardening, cooking), past work history (sales), areas of interest (outdoors, local activities), and current feelings (wanting to relax).

[1164] Step 2:

[1165] The device sends the user's input information, including information about the emotional state, to the server.

[1166] Step 3:

[1167] The server inputs the received information into a generative AI model for analysis. The generative AI model analyzes the user's preferences and experience data and lists appropriate Second Life activities and hobbies. For example, it might list "join a gardening club" or "attend a cooking class."

[1168] Step 4:

[1169] The server uses an emotion engine to recognize the user's emotional data in real time as they input. The emotion engine then refines the activities and hobbies listed by the generative AI model based on the emotional data. For example, if the user is in the mood to relax, "joining a gardening club" will be prioritized.

[1170] Step 5:

[1171] The server performs persona analysis and further analyzes the information obtained from the emotion engine to determine the most suitable activities for the user. Persona analysis selects the best suggestions based on the user's detailed characteristics.

[1172] Step 6:

[1173] The server retrieves information related to the determined activity from a database, such as details about a local gardening club or a cooking class schedule.

[1174] Step 7:

[1175] The server sends the acquired information to the user's terminal and displays it on the screen. The user can select various activities based on the displayed information.

[1176] Step 8:

[1177] Based on the displayed information, the user plans their Second Life by taking into account the suggested activities and hobbies. For example, the user decides to "join a gardening club" and adjusts their schedule accordingly.

[1178] Step 9:

[1179] The server will match the user with relevant businesses and services as needed, for example if the user is interested in a gardening club, providing contact details and details on how to join.

[1180] Step 10:

[1181] When a contract is concluded between a user and a store or service, the server collects a fee. This fee is based on the success of the service introduction and matching, and is used to fund the system's operations.

[1182] Through these processing steps, the system can suggest activities and hobbies that seniors can pursue to lead fulfilling lives after retirement, and use the emotion engine to make optimal suggestions based on the user's emotions. Furthermore, by supporting users to start specific activities, the system can increase overall satisfaction.

[1183] Example 2

[1184] 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."

[1185] When suggesting post-retirement activities and hobbies, it is difficult to provide optimal options while appropriately considering the user's personal information and emotions. Furthermore, there is a need to reduce the effort required to obtain specific information about activities that interest users and to support them in starting activities smoothly. In particular, if suggestions do not reflect the user's emotional state, user satisfaction will decrease, and a system that solves this problem is needed.

[1186] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1187] In this invention, the server includes: an input means for a user to input information about their preferences, experiences, and emotions; a communication means for transmitting the input information to the server; an analysis means for analyzing the user's input information using a generative AI model and listing appropriate activities and hobbies; an emotion recognition means for recognizing the user's emotions and reflecting them in the analysis results; a narrowing down means for narrowing down the listed activities and hobbies based on persona analysis; an information acquisition means for acquiring information related to the narrowed down activities and hobbies; a provision means for providing the acquired information to the user; a matching means for matching the user with relevant stores and services; and a fee collection means for collecting a fee when a contract is concluded between the user and a store or service. This makes it possible to suggest optimal post-retirement activities and hobbies based on the user's individual preferences and emotions, allowing them to start activities smoothly, thereby increasing user satisfaction and improving the convenience of the service.

[1188] "Input means" refers to an interface through which a user inputs information about preferences, experiences, and emotions.

[1189] "Communication means" refers to a data communication function for transmitting information entered by the user to the server.

[1190] "Analysis means" refers to the function that uses a generative AI model to analyze the user's input information and list appropriate activities and hobbies.

[1191] "Emotion recognition means" refers to a function that recognizes the user's emotional state in real time and reflects the results in the analysis results.

[1192] "Refinement tools" refers to the ability to narrow down the activities and hobbies listed based on persona analysis.

[1193] "Information acquisition means" refers to the function of acquiring information related to narrowed-down activities and hobbies from a database.

[1194] "Providing means" refers to a function that provides the acquired information to the user and displays it on the interface.

[1195] "Matching means" refers to a function that matches users with related stores and services.

[1196] The "fee collection means" refers to a function for collecting a fee when a contract is concluded between a user and a store or service.

[1197] The present invention relates to an information processing system that suggests post-retirement activities based on a user's preferences, experiences, and emotions. This system is implemented using a user terminal, a server, an emotion recognition device, and related databases. The specific configuration and operation of the present invention are described in detail below.

[1198] The system includes an "input means" through which a user inputs information about preferences, experiences, and emotions. The input is performed through a terminal interface, such as a text box or drop-down menu, and is implemented using a common computing device, such as a smartphone or PC.

[1199] The information entered by the user is sent to the server via a "communication method." This communication method is realized via network communication, and usually uses the HTTPS protocol. This ensures that the input data is sent securely to the server.

[1200] The server uses an "analysis tool" to pass the user's input information to a generative AI model for analysis. The generative AI model may use Python-based Pytorch or OpenAI's GPT-3, for example. This analysis generates a list of appropriate activities and hobbies based on the user's preferences and experience.

[1201] The system also includes an "emotion recognition mechanism" that uses Microsoft's Emotion API or proprietary emotion recognition algorithms to recognize the user's emotional state in real time. This emotional data is sent to a server and reflected in the analysis results. If the user is feeling stressed, relaxation activities will be prioritized.

[1202] Next, a "refining method" further refines the best activities and hobbies using persona analysis, for example using Scikit-learn or TensorFlow. The server identifies the activities that best fit the user's profile and passes that information on to the next step.

[1203] Using the "information retrieval means," the server retrieves information related to the determined activity or hobby from the database. This information may include local activity clubs, events, classes, etc. Specifically, the server issues an SQL query to retrieve the necessary information from the database.

[1204] The acquired information is sent to the user terminal by the "providing means" and displayed on the user's interface. This allows the user to make specific plans based on the suggested activities. For example, the user may decide to join a gardening club and create a schedule for it.

[1205] Furthermore, the server uses a "matching method" to match users with relevant stores and services. Specifically, it uses a matching algorithm to provide users with the most suitable contact information and detailed information. This information is sent via email, SMS, or in-app notifications.

[1206] Finally, when a contract is concluded between the user and the store or service, the server collects the fee using the "fee collection means." This fee is processed using a payment system (for example, PayPal API or Stripe API) and becomes operating funds for the service.

[1207] Specific examples

[1208] A user logs in using a device and enters information such as, "My hobby is gardening, and I used to work in sales. I'm interested in outdoor activities and local activities, but recently I've been wanting to do something more relaxing." This information is sent to the server and analyzed by the generative AI model. The generative AI model then lists activities such as "joining a local gardening club" and "joining a nearby cooking class."

[1209] The emotional state of the user is also checked using an emotion engine; for example, if the stress level is high, "relaxing activities" are prioritized. Persona analysis is performed to narrow down the activities that are most suitable for the user. The server retrieves detailed information and activity schedules of local gardening clubs from a database and displays them on the user's device. The user decides to join the gardening club and creates a schedule for it.

[1210] The server matches users with gardening clubs, provides contact information and details, and finally, the user enters into a contract with the gardening club, and the server collects the commission.

[1211] This system makes it possible to suggest optimal post-retirement activities and hobbies based on the user's individual tastes and feelings, allowing them to smoothly start their activities, thereby increasing user satisfaction and improving the convenience of the service.

[1212] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1213] Step 1:

[1214] User logs in from terminal

[1215] The user inputs information about their preferences, experiences, and emotions. The device receives this input information and formats the data for transmission. The input data (e.g., "I enjoy gardening as a hobby and used to work in sales. I'm interested in outdoor activities and community activities, but recently I've been wanting to do something more relaxing") is prepared as a transmission request. In concrete terms, the user opens a web browser, accesses a login page, enters their username and password, and clicks the login button.

[1216] Step 2:

[1217] Sending input information to the server

[1218] The input data generated by the device is sent to the server using the HTTPS protocol. An encrypted channel is used for communication. The input data is decoded on the server side and prepared for further processing. Specifically, the user enters information into the input form and clicks the "Submit" button. At that time, the data is sent asynchronously using an AJAX request.

[1219] Step 3:

[1220] Analysis of information

[1221] The server inputs the user's input information into a generative AI model. The generative AI model (e.g., Python's Pytorch or GPT-3) is used to analyze the data and list appropriate activities and hobbies. The input data is passed to the generative AI model, and the analysis results, which are listed as activities and hobbies, are generated in JSON format. Specifically, a Python script is executed, the generative AI model analyzes the data, and the results are output.

[1222] Step 4:

[1223] Emotion recognition by emotion recognition means

[1224] The server receives emotion recognition data (e.g., from a facial recognition camera or Emotion API) and evaluates the user's emotional state. Based on this, the analysis results are prioritized. The emotion data is processed in real time and indicators such as stress levels are calculated. Specifically, the emotion recognition device collects emotion data, and the server analyzes it.

[1225] Step 5:

[1226] Narrowing down through persona analysis

[1227] The server uses the persona analysis function to further narrow down the listed activities and hobbies based on the analysis results and emotional data. A persona analysis algorithm (e.g., Scikit-learn or TensorFlow) is run to determine the best options. The input data and analysis results are passed to the persona analysis algorithm, which outputs the narrowed down results. Specifically, the persona analysis script is run on the server.

[1228] Step 6:

[1229] Obtaining related information

[1230] The server retrieves information related to the narrowed-down activities and hobbies from the database. It issues an SQL query to retrieve the target data and formats it as a response. The narrowed-down activities and hobbies are used in the database query, and the relevant information is returned in JSON format. Specifically, the server executes the SQL query and retrieves the information from the database.

[1231] Step 7:

[1232] Providing information

[1233] The server sends the retrieved relevant information to the user's device and displays it on the user's interface. The data is visually organized and displayed using HTML and CSS, allowing the user to review the information and make decisions. Specifically, the server sends the retrieved data in JSON format to the device, where it is displayed on the device's interface.

[1234] Step 8:

[1235] Activity selection and planning

[1236] The user selects activities and hobbies based on the displayed information and creates a specific plan. The user's selection is passed to the next processing step. On the device interface, the user clicks the "Join" button and registers the schedule in conjunction with the calendar app. Specifically, the device automatically generates a schedule based on the activities selected by the user.

[1237] Step 9:

[1238] Matching implementation

[1239] The server uses a matching algorithm to match the user with relevant stores and services. The server provides optimal contact information and detailed information. The matching results are generated and notified to the user. Specifically, the server executes the algorithm and sends the appropriate contact information to the user's device.

[1240] Step 10:

[1241] Contracts and fee collection

[1242] When a contract is concluded between the user and the store or service, the server records that information and collects the fee. The fee is processed using a payment system (e.g., PayPal API or Stripe API). The information about the conclusion of the contract is passed as input data to the payment system, which then processes the fee. Specifically, the server calls the payment API and completes the fee transaction.

[1243] (Application example 2)

[1244] 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."

[1245] There is a lack of methods to suggest optimal activities for retirement based on personal preferences and experiences. There is also a lack of technology that suggests appropriate activities while taking into account the user's emotions. Furthermore, there is a lack of systems that allow users to easily access and schedule suggested activities. Therefore, there is a need for methods to enrich retirement life.

[1246] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an emotion recognition means for recognizing the user's emotions and reflecting them in the proposals, an input means for the user to input their preferences and experiences, an analysis means for analyzing the user's input information using a generative AI model and listing appropriate activities and hobbies, a narrowing down means for narrowing down the listed activities and hobbies based on persona analysis, an information acquisition means for acquiring information related to the narrowed down activities and hobbies, a provision means for providing the acquired information to the user, a notification means for notifying the user of recommended activities, and a schedule setting means for setting a schedule based on the proposed activities. This makes it possible to propose optimal post-retirement activities taking into account the user's personal information and emotions.

[1247] The "input means" is an interface that allows the user to input their own preferences and experiences.

[1248] The "analysis means" is a device that uses a generative AI model to analyze the user's input information and list appropriate activities and hobbies.

[1249] A "narrowing tool" is a device that has the function of further narrowing down the activities and hobbies listed based on persona analysis.

[1250] The "information acquisition means" is a device that acquires information related to the narrowed-down activities and hobbies from a database.

[1251] The "providing means" is a device that provides the acquired information to the user.

[1252] An "emotion recognition means" is a device that recognizes the user's emotions in real time and reflects them in suggestions.

[1253] The "notification means" is a device that has the function of notifying the user of recommended activities.

[1254] A "schedule setting means" is a device that has the function of setting a schedule for a user based on suggested activities.

[1255] To implement the present invention, a system including emotion recognition means, input means, analysis means, narrowing means, information acquisition means, provision means, notification means, and schedule setting means is required.

[1256] System configuration and operation

[1257] The system consists of a user terminal, a server, and related databases. The operation of each component of the system is described in detail below.

[1258] User terminal

[1259] First, users log in to the system using their device (smartphone or tablet). After logging in, they can enter information about their preferences and experiences. An input method is provided, and an interface is prepared for users to enter details about their hobbies, work history, interests, etc.

[1260] server

[1261] The server includes the following means:

[1262] 1. Input Method

[1263] It provides an interface for users to input their preferences and experiences.

[1264] 2. Analysis method

[1265] The server receives the information entered by the user and analyzes it using a generative AI model, resulting in a list of activities and hobbies that are best suited to the user.

[1266] 3. Emotion recognition means

[1267] It includes a software module for recognizing users' emotions in real time, and this emotional data is reflected in the analysis results, improving the accuracy of the proposal activities.

[1268] 4. Narrowing methods

[1269] Based on persona analysis, narrow down the list of activities and hobbies generated to the most suitable items.

[1270] 5. Information acquisition means

[1271] It has the ability to retrieve information related to narrowed-down activities and hobbies (e.g., location, time, price) from a database.

[1272] 6. Means of provision

[1273] This is a means for providing the acquired information to the user. Specifically, it sends the information to the user's terminal and displays it.

[1274] 7. Means of notification

[1275] Notify users about recommended activities.

[1276] 8. Scheduling Methods

[1277] It is a way to set a schedule for the user based on suggested activities, and it also works with notifications to set reminders.

[1278] Hardware and Software

[1279] Emotion Recognition Engine: A software module for recognizing user emotions in real time.

[1280] Generative AI model: A model that analyzes user input and lists optimal activities and hobbies.

[1281] Database: A database that stores information about activities and hobbies and is accessed by information retrieval methods.

[1282] Specific examples

[1283] Suppose a user inputs "cooking" as their hobby, "sales" as their work history, "handicrafts" as their interest, and "slightly tired" as their current emotional state. This information is sent to the server and analyzed by the analysis means. The generative AI model lists activities such as "nearby handicraft classes" and "cooking workshops." The emotion recognition means confirms the emotion of "slightly tired," and prioritizes the relaxing "handicraft classes." The narrowing means selects more accurate activities, and the information acquisition means acquires specific location, time, and price information from the database. The provision means displays the information on the user's terminal, and the notification means notifies the user of recommended activities. Finally, the schedule setting means allows the user to set a schedule for the handicraft classes.

[1284] Prompt Sentence Examples

[1285] User Preferences: ["Cooking", "Crafts"]

[1286] User Experience: "Sales Job"

[1287] Current Emotion: "Slightly tired"

[1288] The above is a specific embodiment for carrying out the invention.

[1289] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1290] Step 1:

[1291] A user logs in to the system using a device. The user accesses the app's login screen and completes the login by entering their personal authentication information. The input data is the user's ID and password, and the output is access permission.

[1292] Step 2:

[1293] The user inputs their interests, experiences, and current emotional state into the terminal. Specifically, they input information such as "cooking" as a hobby, "sales experience," and an interest in "handicrafts." They also input "slightly tired" as their current emotional state. This information is sent to the server as input data.

[1294] Step 3:

[1295] The server inputs the received user information into a generative AI model for analysis. The input data is the user's preferences, experiences, and emotional state, and the output is a list of activities and hobbies that are best suited to the user. The generative AI model analyzes this data and lists activities such as "nearby craft classes" and "cooking workshops."

[1296] Step 4:

[1297] The server analyzes the user's emotional data using an emotion recognition means. The input data is the user's current emotional state, and the output is a list of activities that take emotions into account. Reflecting the emotional data of "slightly tired," the server prioritizes the suggestion of "sewing classes" to relax.

[1298] Step 5:

[1299] The server uses a refinement method to further refine the generated activity list based on persona analysis. The input data is the activity list and emotion recognition data, and the output is the refined activities that are most suitable for the user. Here, "Handicraft class" is particularly recommended from the refined list.

[1300] Step 6:

[1301] The server uses the information acquisition means to acquire detailed information related to the narrowed-down activities from the database. Specifically, it acquires information such as the location, time, and fee of the handicraft class. The input data is the narrowed-down activity name, and the output is the detailed information.

[1302] Step 7:

[1303] The server provides the acquired detailed information to the user terminal. Using the providing means, information such as the location, time, and fee of the handicraft class is displayed on the user terminal. The input data is the detailed information, and the output is the information displayed to the user.

[1304] Step 8:

[1305] The server uses the notification mechanism to notify the user about the recommended activity. The input data is the information provided, and the output is the notification content. The user receives a notification confirming "attend a sewing class."

[1306] Step 9:

[1307] The user selects the suggested activities and sets the schedule. The user confirms the dates and times of the craft classes and inputs the schedule. The input data is the user's schedule information, and the output is the scheduled information.

[1308] Step 10:

[1309] The server uses the schedule setting means to check the user's schedule setting and activate the reminder function, so that the user receives reminder notifications based on the set schedule. The input data is schedule information, and the output is reminder notifications.

[1310] The above is the specific processing flow of the present invention. Through this series of steps, the user can find the most suitable activity based on their personal tastes and feelings, and live a comfortable life after retirement.

[1311] 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.

[1312] 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.

[1313] 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.

[1314] [Fourth embodiment]

[1315] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1316] 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.

[1317] 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).

[1318] 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.

[1319] 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.

[1320] 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).

[1321] 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.

[1322] 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.

[1323] 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.

[1324] 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.

[1325] 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.

[1326] 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.

[1327] 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."

[1328] This invention relates to an information processing system that uses a generative AI model to suggest post-retirement activities based on personal preferences and experiences. This system is implemented using a user terminal, a server, and related databases. The specific operations of the system's program processing are explained in natural language below.

[1329] System Overview

[1330] The system uses a generative AI model to analyze a user's personal information and suggest optimal Second Life activities and hobbies. The system has the following key features:

[1331] 1. An "input method" that allows users to input their personal preferences and work experience.

[1332] 2. "Analysis means" that analyzes the information entered by the user and lists appropriate activities and hobbies.

[1333] 3. A "refining method" that narrows down the listed activities and hobbies based on persona analysis.

[1334] 4. "Means of information acquisition" to obtain information related to narrowed-down activities and hobbies.

[1335] 5. "Means of provision" that provides the acquired information to the user and performs matching as necessary.

[1336] Program processing

[1337] The specific operation is described below.

[1338] 1. A user logs in from a terminal

[1339] A user logs in using a specific interface and inputs information such as interests and experiences. Specifically, the user inputs information such as hobbies, past work history, and fields of interest.

[1340] 2. Sending input information to the server

[1341] The data entered by the user is transmitted from the terminal to the server.

[1342] 3. Analysis of Information

[1343] The server inputs the received information into a generative AI model for analysis, which then generates a list of appropriate activities and hobbies based on the user's data.

[1344] 4. Narrowing down through persona analysis

[1345] The server uses persona analysis to narrow down the list obtained from the generative AI model and determine the most suitable activity for the user.

[1346] 5. Obtaining related information

[1347] The server retrieves information related to the determined activity from a database, including local activity clubs, events, classes, etc.

[1348] 6. Provision of Information

[1349] The server transmits the acquired information to the user terminal and displays it in a format that the user can intuitively understand.

[1350] 7. Activity Selection and Planning

[1351] The user plans their second life based on the displayed information.

[1352] 8. Matching

[1353] If necessary, the server matches the user with relevant stores and services, allowing the user to actually experience the suggested activities.

[1354] 9. Contracts and Fee Collection

[1355] When a contract is concluded between the user and the store or service, the server collects a fee.

[1356] Specific examples

[1357] Step 1-2: Enter user information

[1358] The user enters into the device, "My hobby is gardening, I used to work in sales, and I'm interested in outdoor activities and community activities."

[1359] The device sends this information to the server.

[1360] Step 3: Analyze the information

[1361] The server passes the data to the generative AI model for analysis.

[1362] The generative AI model lists activities such as "joining a local gardening club" and "joining a nearby cooking class."

[1363] Step 4: Persona Analysis

[1364] The server conducted a persona analysis and specifically selected "joining a local gardening club" and "joining a nearby cooking class."

[1365] Step 5: Obtain relevant information

[1366] The server retrieves from a database information about stores and services related to the proposed activity, such as details of a gardening club or a cooking class schedule.

[1367] Step 6: Provide information

[1368] The server sends the acquired information to the user's terminal and displays it.

[1369] Steps 7-9: Activity selection and contract formation

[1370] The user makes plans based on the suggested activities and, if necessary, enters into contracts with stores and services.

[1371] If the contract is concluded, the server collects the fee.

[1372] In this way, the system suggests activities and hobbies that will help seniors live fulfilling lives after retirement, and supports them in taking concrete actions.

[1373] The processing flow will be explained below.

[1374] Step 1:

[1375] A user logs in from a device. The user enters their profile information, interests, past work experience, etc. This information includes hobbies (e.g., gardening, cooking), past work experience (e.g., sales), and areas of interest (e.g., outdoors, local activities).

[1376] Step 2:

[1377] The terminal transmits the user's input information to the server.

[1378] Step 3:

[1379] The server inputs the received information into a generative AI model for analysis. As a result of this analysis, a list of activities and hobbies that are best suited to the user is generated. For example, information such as "joining a gardening club" or "taking a cooking class" may be listed.

[1380] Step 4:

[1381] The server uses persona analysis to narrow down the list obtained from the generative AI model and determine the activities that are most suitable for the user. For example, persona analysis may specifically recommend "joining a local gardening club" and "attending a nearby cooking class."

[1382] Step 5:

[1383] The server retrieves information related to the determined activity from the database, including details of the activity and information on related stores and services (e.g., the activity schedule for a gardening club or the dates and times of cooking classes).

[1384] Step 6:

[1385] The server sends the acquired information to the user's terminal and displays it, allowing the user to use it as a reference when making their own plans.

[1386] Step 7:

[1387] Based on the displayed information, the user plans their Second Life by taking into account suggested activities and hobbies. For example, the user may decide to join a gardening club and create a schedule for it.

[1388] Step 8:

[1389] The server then matches the user with relevant stores and services as needed, providing appropriate contact information and detailed information about the activities the user is interested in. At this stage, a point of contact between the user and the store or service is created.

[1390] Step 9:

[1391] When a contract is concluded between a user and a store or service, the server collects a fee. This fee is based on the success of the introduction or match and is used to fund the operation of the service.

[1392] Through the above processing steps, the system can suggest activities and hobbies that will help seniors live fulfilling lives after retirement and support them in taking specific actions.

[1393] Example 1

[1394] 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."

[1395] In modern society, an increasing number of individuals wish to live fulfilling lives in their own way even after retirement. However, it is difficult to determine what activities and hobbies to choose, and it is hard to find the activities that best suit them. Furthermore, because information is scattered, it is time-consuming to obtain detailed information about specific activities. Furthermore, tasks such as matching proposed activities with actual stores and services and collecting fees after contracts are concluded are also cumbersome. There is a need for an efficient information processing device that can solve these problems.

[1396] 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.

[1397] In this invention, the server includes an input means for a user to input their preferences and experiences, an analysis means for analyzing the user's input information using a generative AI model and listing appropriate activities and hobbies, a narrowing down means for narrowing down the listed activities and hobbies based on persona analysis, an information acquisition means for acquiring information related to the narrowed down activities and hobbies, a provision means for providing the acquired information to the user, a matching means for matching the user with relevant stores and services as needed, and a fee collection means for collecting a fee when a contract is concluded between the user and a store or service. This enables the user to efficiently find the optimal post-retirement activities and hobbies, and the provision of specific activity information, matching, and fee collection after the contract is concluded are all carried out in an integrated manner.

[1398] An "information processing device" is a device that refers to the entire system that receives input from a user, analyzes it, and provides the results.

[1399] A "generative AI model" is an artificial intelligence model that generates new information based on a user's preferences and experiences and suggests appropriate activities and hobbies.

[1400] "Input means" refers to an interface or device that allows a user to input their preferences and experiences into the system.

[1401] "Analysis means" refers to the device or software that uses a generative AI model to analyze the user's input information and execute the process of listing activities and hobbies.

[1402] "Refinement methods" refers to the processes or devices used to further refine the activities and hobbies listed by the generative AI model based on persona analysis.

[1403] "Information acquisition means" refers to a device or software for acquiring information related to a narrowed-down activity or hobby from a database.

[1404] "Providing means" refers to an interface or device that provides the acquired information to the user and displays it in a form that the user can intuitively understand.

[1405] "Matching means" refers to a device or software for matching users with related stores or services.

[1406] The term "fee collection means" refers to a device or software for collecting a fee when a contract is concluded between a user and a store or service.

[1407] "Persona analysis" refers to an analytical method for selecting the most suitable activities and hobbies based on a user's attributes and preferences.

[1408] A "database" refers to a system or storage that stores related information and retrieves that information when needed.

[1409] System Overview

[1410] The present invention relates to an information processing device that uses a generative AI model to suggest post-retirement activities based on personal preferences and experiences. This device is implemented using a user terminal, a server, and related databases. Specific operations are described below.

[1411] Hardware and software used

[1412] This system uses the following hardware and software.

[1413] User device: An internet-connected device such as a smartphone, tablet, or PC.

[1414] Server: High performance computing server, cloud server.

[1415] Database: A relational database that stores user information and activity information.

[1416] Generative AI model: A neural network model that performs analysis based on user information.

[1417] Persona analysis software: Dedicated software for conducting persona analysis.

[1418] Communication protocol: Secure data communication using HTTP / HTTPS.

[1419] Specific actions

[1420] 1. A user logs in from a terminal

[1421] Users log in using a web browser or a dedicated app and enter information such as hobbies and experiences.

[1422] 2. Sending input information to the server

[1423] The data entered by the user is sent from the terminal to the server, where it is encrypted and sent securely.

[1424] 3. Analysis of Information

[1425] The server inputs the received information into a generative AI model for analysis, which then lists appropriate activities and hobbies based on the user's data.

[1426] 4. Narrowing down through persona analysis

[1427] The server uses persona analysis to narrow down the list obtained from the generative AI model and determine the most suitable activity for the user.

[1428] 5. Obtaining related information

[1429] The server retrieves information related to the determined activity from a database, including local activity clubs, events, classes, etc.

[1430] 6. Provision of Information

[1431] The server transmits the acquired information to the user terminal and displays it in a format that the user can intuitively understand.

[1432] 7. Activity Selection and Planning

[1433] The user plans their Second Life based on the displayed information. The user selects activities that interest them from the suggested activities and creates a plan.

[1434] 8. Matching

[1435] If necessary, the server matches the user with relevant stores and services, allowing the user to actually experience the suggested activities.

[1436] 9. Contracts and Fee Collection

[1437] When a contract is concluded between the user and the store or service, the server collects a fee. The contract details are managed within the system.

[1438] Specific examples

[1439] Below are some specific examples and prompts:

[1440] Specific examples

[1441] The user enters into the device, "My hobby is gardening, I used to work in sales, and I'm interested in outdoor activities and community activities."

[1442] The device sends this information to the server.

[1443] The server passes the data to a generative AI model for analysis, and lists options such as "joining a local gardening club" and "joining a nearby cooking class."

[1444] The server conducted a persona analysis and specifically selected "joining a local gardening club" and "joining a nearby cooking class."

[1445] The server retrieves from a database information about stores and services related to the proposed activity, examples of which include "gardening club details" and "cooking class schedules."

[1446] The server sends the acquired information to the user's terminal and displays it.

[1447] Prompt Sentence Examples

[1448] "Design a system that uses generative AI models to suggest optimal retirement activities and hobbies based on a user's interests and experiences."

[1449] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1450] System program processing flow

[1451] Step 1:

[1452] The user logs in from their device. They access the login page using a web browser or a dedicated app and enter their user ID and password. After successfully logging in, the user enters information such as their preferences, past work history, and areas of interest. This input information becomes the initial input data for the system.

[1453] Input: User ID, password, preferences, work history, areas of interest

[1454] Output: Login success flag, input information data

[1455] Step 2:

[1456] The information entered by the user is sent from the terminal to the server. During transmission, the data is encrypted and securely transferred to the server.

[1457] Input: Input information data

[1458] Output: A confirmation message sent to the server

[1459] Step 3:

[1460] The server inputs the received information into a generative AI model for analysis. The generative AI model then lists appropriate activities and hobbies based on the user's data. Specifically, it generates the most suitable activity candidates for the user based on data such as hobbies and work history.

[1461] Input: User-entered information data

[1462] Output: List of potential activities

[1463] Step 4:

[1464] The server inputs the list obtained from the generated AI model into persona analysis software to narrow down the list. From the list of candidate activities, persona analysis further selects the activity that best suits the user's attributes and preferences.

[1465] Input: List of possible activities

[1466] Output: A filtered list of activities

[1467] Step 5:

[1468] The server retrieves information related to the determined activity from a database, including local activity clubs, events, courses, etc. It performs a database search to retrieve the latest information related to the proposed activity.

[1469] Input: A filtered list of activities

[1470] Output: Details related to the activity

[1471] Step 6:

[1472] The server sends the acquired information to the user's device and displays it in a format that the user can intuitively understand. Specifically, the server organizes the information, converts it into a format suitable for the user interface, and then sends it.

[1473] Input: Details related to the activity

[1474] Output: Information displayed on the user's terminal

[1475] Step 7:

[1476] The user plans their Second Life based on the displayed information. They select activities that interest them from the suggested activities and formulate a specific plan. The selected information is fed back to the server.

[1477] Input: User-selected activity

[1478] Output: User selection information

[1479] Step 8:

[1480] The server matches the user with relevant stores and services as needed based on the user's selection information, allowing the user to actually experience the suggested activities.

[1481] Input: User selection information

[1482] Output: Matching results

[1483] Step 9:

[1484] When a contract is concluded between the user and the store or service, the server collects the fee. Details of the contract and fee are managed within the system, and a confirmation message is sent to the user and the store.

[1485] Input: Contract conclusion information

[1486] Output: Fee collection and confirmation message

[1487] The above is the specific processing flow of the program of this system.

[1488] (Application example 1)

[1489] 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."

[1490] To enrich the lives of seniors after retirement, there is a need for technology that not only suggests activities and hobbies suitable for seniors, but also provides new ways to enjoy themselves through dining experiences. However, existing systems are limited in the activities and hobbies they suggest based on the user's preferences and experience, making it difficult to translate these suggestions into concrete actions, particularly those such as cooking at home or participating in local cooking events. In addition, arranging ingredients and cooking equipment is complicated, and a simple method for doing this is needed.

[1491] 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.

[1492] In this invention, the server includes an input means for a user to input their preferences and experiences, an analysis means for analyzing the user's input information using a generative AI model to list appropriate activities and hobbies and to list recommended recipes and events to participate in, a narrowing down means for narrowing down the listed activities, hobbies, recommended recipes and events to participate in based on persona analysis, an information acquisition means for acquiring information related to the narrowed down activities, hobbies, recommended recipes and events to participate in, and a provision means for providing the acquired information to the user. This enables users to easily find activities and dining experiences that are best suited to their hobbies and experiences, and to easily arrange the ingredients and cooking utensils for them.

[1493] text

[1494] "Personal preferences and experiences" refers to information such as the user's specific interests, past work history, and areas of interest.

[1495] A "generative AI model" is an artificial intelligence model that analyzes input data and generates optimal suggestions.

[1496] The "input means for the user to input his / her preferences and experiences" is an interface that allows the user to input his / her preferences and experiences into the terminal.

[1497] "Analysis means" refers to a device or software that uses a generative AI model to analyze the user's input information and list appropriate activities, hobbies, recommended recipes, and events to participate in.

[1498] "Persona analysis" is an analytical method for narrowing down the best proposals for a specific target user group based on a typical user profile.

[1499] A "refinement tool" is a device or software that has the ability to optimize activities, hobbies, recommended recipes, or events to attend based on persona analysis.

[1500] The "information acquisition means" is a device or software that has the function of acquiring information related to the narrowed-down activities, hobbies, recommended recipes, and events to attend from a database or external information source.

[1501] The "providing means" is a device or software that has the function of providing the acquired information to the user and displaying it on the user terminal.

[1502] A "delivery means" is a device or software that allows a user to order ingredients and cooking utensils they need and arrange for their delivery.

[1503] text

[1504] The present invention relates to a system that provides a function for proposing post-retirement activities and dining experiences based on a user's preferences and experiences, and delivering the ingredients and cooking utensils required for those activities.

[1505] The system includes the following main components:

[1506] 1. An input method for users to input their preferences and experiences

[1507] 2. A method of analysis that uses a generative AI model to analyze user input and produce a list of appropriate activities, hobbies, recommended recipes, and events to attend.

[1508] 3. A filter to narrow down the activities, hobbies, recommended recipes, and events to attend based on the persona analysis.

[1509] 4. Information acquisition methods for obtaining information related to narrowed-down activities, hobbies, recommended recipes, and events to attend

[1510] 5. Means of providing acquired information to users

[1511] 6. A way for users to have the ingredients and cooking equipment they need delivered

[1512] In terms of the actual program processing, first, the user enters their preferences, past work history, and areas of interest through the interface. This can be done using a smartphone, and React Native can be used to configure the UI. The user's input information is then sent to the server.

[1513] On the server side, a generative AI model (such as GPT-3) and its analysis results are used to create a list of suitable activities, hobbies, recommended recipes, and events to attend. The persona analysis function is then used to refine the list of suggestions. This process uses Node.js and Express as the backend and MongoDB as the database.

[1514] The server retrieves related information from the database based on the filtered information and provides it to the user. This information includes information on local club activities, cooking events, and the ingredients and cooking equipment needed for recommended recipes. Users can check this information on their smartphones and order the necessary ingredients and cooking equipment through a delivery service.

[1515] For example, if a user inputs "Hobbies: cooking, travel," "Past work experience: sales," and "Favorite ingredients: tomatoes, pasta," the server will use the generative AI model to suggest "local Italian cooking classes" and "new recipes using pasta." These suggestions are optimized based on persona analysis and displayed to the user.

[1516] An example prompt is:

[1517] "User data: Hobbies: Cooking, traveling; Past work experience: Sales; Favorite ingredients: Tomato, pasta"

[1518] "Cooking Recommendations:"

[1519] In this way, by using the system of the present invention, users can easily find activities and dining experiences that best suit their hobbies and experiences, and easily arrange the ingredients and cooking utensils for them.

[1520] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1521] text

[1522] Step 1:

[1523] Users log in to the system using a device and enter information such as their preferences, past work history, and areas of interest. The entered data is necessary to proceed to the next processing step, and the information entered here forms the basis for the entire system. Specifically, a smartphone is used, and the UI is built using React Native.

[1524] Step 2:

[1525] The terminal sends the data entered by the user to the server. This sent data is input data to be analyzed by subsequent analysis means. Specific data content includes information such as "Hobbies: cooking, travel," "Past work history: sales," and "Favorite ingredients: tomatoes, pasta."

[1526] Step 3:

[1527] The server receives the input data and feeds it into a generative AI model (such as GPT-3) that analyzes the user's data and lists appropriate activities, hobbies, recommended recipes, and events to attend. During the analysis process, the generative AI model treats the input data as prompts.

[1528] Step 4:

[1529] Using the list data obtained from the generative AI model, the server performs persona analysis, which optimizes the listed proposals for specific target users. In this step, data is narrowed down based on a specific persona profile, and the proposals that are most suitable for the user are selected.

[1530] Step 5:

[1531] The server retrieves information related to the user's activities, hobbies, recommended recipes, and events from a database. This information includes details of local clubs, cooking events, and ingredients and utensils used in recipes. This data is retrieved using a database such as MongoDB.

[1532] Step 6:

[1533] The server then sends the acquired information to the user's device and provides it in a format that the user can intuitively understand. Here, the information is displayed on a user interface, allowing the user to check specific proposals.

[1534] Step 7:

[1535] Users select from suggested activities, hobbies, and dining experiences, and then order ingredients and cooking equipment via delivery services. The ordering process is completed by the user on their device, and the server sends the order data to the delivery service. Once the order is confirmed, the desired items are delivered to the user.

[1536] Step 8:

[1537] The server collects a fee when a contract is concluded between the user and the delivery service. This fee collection is performed automatically, and financial transactions between the user and the service provider are carried out smoothly.

[1538] 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.

[1539] This invention relates to an information processing system that combines an information processing device using a generative AI model that suggests post-retirement activities based on personal preferences and experience with an emotion engine that recognizes the user's emotions and reflects them in the activity suggestions. This system is implemented using a user terminal, a server, and devices and related databases required for emotion recognition. The specific operations of the system's program processing are explained below in natural language.

[1540] System Overview

[1541] The system uses a generative AI model and an emotion engine to analyze a user's personal information and suggest optimal Second Life activities and hobbies. The system has the following key features:

[1542] 1. An "input method" that allows users to input their personal preferences and work experience.

[1543] 2. "Analysis method" that analyzes user input information using a generative AI model and lists appropriate activities and hobbies.

[1544] 3. "Emotion recognition means" that recognizes the user's emotions in real time and reflects them in the analysis results.

[1545] 4. "Refining methods" to narrow down the activities and hobbies listed based on persona analysis.

[1546] 5. "Means of information acquisition" to obtain information related to narrowed-down activities and hobbies.

[1547] 6. "Means of provision" that provides the acquired information to the user and performs matching as necessary.

[1548] Program processing

[1549] The specific operation is described below.

[1550] 1. A user logs in from a terminal

[1551] A user logs in using a specific interface and inputs information about their interests, experiences, and emotions. Specifically, the user inputs their hobbies, past work history, areas of interest, and current emotional state.

[1552] 2. Sending input information to the server

[1553] The data entered by the user is transmitted from the terminal to the server.

[1554] 3. Analysis of Information

[1555] The server inputs the received information into a generative AI model for analysis. The generative AI model generates a list of appropriate activities and hobbies based on the user's data. For example, it might list information such as "joining a gardening club" or "attending cooking classes."

[1556] 4. Emotion Recognition by Emotion Engine

[1557] The emotion engine recognizes the user's emotional data in real time and further refines the activities and hobbies listed by the analysis means based on the emotional data. For example, if the user is feeling stressed, relaxing activities will be prioritized.

[1558] 5. Narrowing down through persona analysis

[1559] The server further analyzes the information obtained from the emotion engine using a persona analysis function to determine the most appropriate activity for the user.

[1560] 6. Obtaining related information

[1561] The server retrieves information related to the determined activity from a database, including local activity clubs, events, classes, etc.

[1562] 7. Provision of Information

[1563] The server sends the acquired information to the user's terminal and displays it, allowing the user to create a specific activity plan while referring to the displayed information.

[1564] 8. Activity Selection and Planning

[1565] Based on the displayed information, users can plan their Second Life by taking into account suggested activities and hobbies. For example, a user may decide to join a gardening club and create a schedule for it.

[1566] 9. Matching

[1567] The server then matches the user with relevant stores and services as needed, providing appropriate contact information and detailed information about the activities the user is interested in. At this stage, a point of contact between the user and the store or service is created.

[1568] 10. Contracts and Fee Collection

[1569] When a contract is concluded between a user and a store or service, the server collects a fee. This fee is based on the success of the introduction or match and is used to fund the operation of the service.

[1570] Specific examples

[1571] Step 1-2: Enter user information

[1572] The user types into the device, "My hobby is gardening, and I used to work in sales. I'm interested in outdoor activities and community activities, but recently I've been wanting to do something more relaxing."

[1573] The device sends this information to the server.

[1574] Step 3: Analyze the information

[1575] The server passes the data to the generative AI model for analysis.

[1576] The generative AI model lists activities such as "joining a local gardening club" and "joining a nearby cooking class."

[1577] Step 4: Emotion Recognition with the Emotion Engine

[1578] The emotion engine recognizes the user's emotional data in real time as they input, and prioritizes relaxing activities (e.g., gardening) when stress levels are high.

[1579] Step 5: Persona analysis

[1580] The server conducted a persona analysis and specifically recommended "joining a local gardening club."

[1581] Step 6: Obtain relevant information

[1582] The server retrieves details and activity schedules of local gardening clubs from a database.

[1583] Step 7: Provide information

[1584] The server sends the acquired information to the user's terminal and displays it.

[1585] Step 8: Select and plan your activities

[1586] A user decides to join a gardening club and makes a schedule for it.

[1587] Step 9: Matching

[1588] The server matches users with gardening clubs and provides contact information and details.

[1589] Step 10: Closing the deal and collecting fees

[1590] The user enters into a contract with the gardening club, and the server collects the fee.

[1591] In this way, the system can suggest activities and hobbies that seniors can pursue to live a fulfilling life after retirement, and can also use the emotion engine to make optimal suggestions based on the user's emotions. This makes it possible to provide services that meet individual needs and increase user satisfaction.

[1592] The processing flow will be explained below.

[1593] Step 1:

[1594] The user logs in from a terminal and uses a specific interface to input their preferences, experiences, and current emotional state. For example, they input their hobbies (gardening, cooking), past work history (sales), areas of interest (outdoors, local activities), and current feelings (wanting to relax).

[1595] Step 2:

[1596] The device sends the user's input information, including information about the emotional state, to the server.

[1597] Step 3:

[1598] The server inputs the received information into a generative AI model for analysis. The generative AI model analyzes the user's preferences and experience data and lists appropriate Second Life activities and hobbies. For example, it might list "join a gardening club" or "attend a cooking class."

[1599] Step 4:

[1600] The server uses an emotion engine to recognize the user's emotional data in real time as they input. The emotion engine then refines the activities and hobbies listed by the generative AI model based on the emotional data. For example, if the user is in the mood to relax, "joining a gardening club" will be prioritized.

[1601] Step 5:

[1602] The server performs persona analysis and further analyzes the information obtained from the emotion engine to determine the most suitable activities for the user. Persona analysis selects the best suggestions based on the user's detailed characteristics.

[1603] Step 6:

[1604] The server retrieves information related to the determined activity from a database, such as details about a local gardening club or a cooking class schedule.

[1605] Step 7:

[1606] The server sends the acquired information to the user's terminal and displays it on the screen. The user can select various activities based on the displayed information.

[1607] Step 8:

[1608] Based on the displayed information, the user plans their Second Life by taking into account the suggested activities and hobbies. For example, the user decides to "join a gardening club" and adjusts their schedule accordingly.

[1609] Step 9:

[1610] The server will match the user with relevant businesses and services as needed, for example if the user is interested in a gardening club, providing contact details and details on how to join.

[1611] Step 10:

[1612] When a contract is concluded between a user and a store or service, the server collects a fee. This fee is based on the success of the service introduction and matching, and is used to fund the system's operations.

[1613] Through these processing steps, the system can suggest activities and hobbies that seniors can pursue to lead fulfilling lives after retirement, and use the emotion engine to make optimal suggestions based on the user's emotions. Furthermore, by supporting users to start specific activities, the system can increase overall satisfaction.

[1614] Example 2

[1615] 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."

[1616] When suggesting post-retirement activities and hobbies, it is difficult to provide optimal options while appropriately considering the user's personal information and emotions. Furthermore, there is a need to reduce the effort required to obtain specific information about activities that interest users and to support them in starting activities smoothly. In particular, if suggestions do not reflect the user's emotional state, user satisfaction will decrease, and a system that solves this problem is needed.

[1617] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1618] In this invention, the server includes: an input means for a user to input information about their preferences, experiences, and emotions; a communication means for transmitting the input information to the server; an analysis means for analyzing the user's input information using a generative AI model and listing appropriate activities and hobbies; an emotion recognition means for recognizing the user's emotions and reflecting them in the analysis results; a narrowing down means for narrowing down the listed activities and hobbies based on persona analysis; an information acquisition means for acquiring information related to the narrowed down activities and hobbies; a provision means for providing the acquired information to the user; a matching means for matching the user with relevant stores and services; and a fee collection means for collecting a fee when a contract is concluded between the user and a store or service. This makes it possible to suggest optimal post-retirement activities and hobbies based on the user's individual preferences and emotions, allowing them to start activities smoothly, thereby increasing user satisfaction and improving the convenience of the service.

[1619] "Input means" refers to an interface through which a user inputs information about preferences, experiences, and emotions.

[1620] "Communication means" refers to a data communication function for transmitting information entered by the user to the server.

[1621] "Analysis means" refers to the function that uses a generative AI model to analyze the user's input information and list appropriate activities and hobbies.

[1622] "Emotion recognition means" refers to a function that recognizes the user's emotional state in real time and reflects the results in the analysis results.

[1623] "Refinement tools" refers to the ability to narrow down the activities and hobbies listed based on persona analysis.

[1624] "Information acquisition means" refers to the function of acquiring information related to narrowed-down activities and hobbies from a database.

[1625] "Providing means" refers to a function that provides the acquired information to the user and displays it on the interface.

[1626] "Matching means" refers to a function that matches users with related stores and services.

[1627] The "fee collection means" refers to a function for collecting a fee when a contract is concluded between a user and a store or service.

[1628] The present invention relates to an information processing system that suggests post-retirement activities based on a user's preferences, experiences, and emotions. This system is implemented using a user terminal, a server, an emotion recognition device, and related databases. The specific configuration and operation of the present invention are described in detail below.

[1629] The system includes an "input means" through which a user inputs information about preferences, experiences, and emotions. The input is performed through a terminal interface, such as a text box or drop-down menu, and is implemented using a common computing device, such as a smartphone or PC.

[1630] The information entered by the user is sent to the server via a "communication method." This communication method is realized via network communication, and usually uses the HTTPS protocol. This ensures that the input data is sent securely to the server.

[1631] The server uses an "analysis tool" to pass the user's input information to a generative AI model for analysis. The generative AI model may use Python-based Pytorch or OpenAI's GPT-3, for example. This analysis generates a list of appropriate activities and hobbies based on the user's preferences and experience.

[1632] The system also includes an "emotion recognition mechanism" that uses Microsoft's Emotion API or proprietary emotion recognition algorithms to recognize the user's emotional state in real time. This emotional data is sent to a server and reflected in the analysis results. If the user is feeling stressed, relaxation activities will be prioritized.

[1633] Next, a "refining method" further refines the best activities and hobbies using persona analysis, for example using Scikit-learn or TensorFlow. The server identifies the activities that best fit the user's profile and passes that information on to the next step.

[1634] Using the "information retrieval means," the server retrieves information related to the determined activity or hobby from the database. This information may include local activity clubs, events, classes, etc. Specifically, the server issues an SQL query to retrieve the necessary information from the database.

[1635] The acquired information is sent to the user terminal by the "providing means" and displayed on the user's interface. This allows the user to make specific plans based on the suggested activities. For example, the user may decide to join a gardening club and create a schedule for it.

[1636] Furthermore, the server uses a "matching method" to match users with relevant stores and services. Specifically, it uses a matching algorithm to provide users with the most suitable contact information and detailed information. This information is sent via email, SMS, or in-app notifications.

[1637] Finally, when a contract is concluded between the user and the store or service, the server collects the fee using the "fee collection means." This fee is processed using a payment system (for example, PayPal API or Stripe API) and becomes operating funds for the service.

[1638] Specific examples

[1639] A user logs in using a device and enters information such as, "My hobby is gardening, and I used to work in sales. I'm interested in outdoor activities and local activities, but recently I've been wanting to do something more relaxing." This information is sent to the server and analyzed by the generative AI model. The generative AI model then lists activities such as "joining a local gardening club" and "joining a nearby cooking class."

[1640] The emotional state of the user is also checked using an emotion engine; for example, if the stress level is high, "relaxing activities" are prioritized. Persona analysis is performed to narrow down the activities that are most suitable for the user. The server retrieves detailed information and activity schedules of local gardening clubs from a database and displays them on the user's device. The user decides to join the gardening club and creates a schedule for it.

[1641] The server matches users with gardening clubs, provides contact information and details, and finally, the user enters into a contract with the gardening club, and the server collects the commission.

[1642] This system makes it possible to suggest optimal post-retirement activities and hobbies based on the user's individual tastes and feelings, allowing them to smoothly start their activities, thereby increasing user satisfaction and improving the convenience of the service.

[1643] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1644] Step 1:

[1645] User logs in from terminal

[1646] The user inputs information about their preferences, experiences, and emotions. The device receives this input information and formats the data for transmission. The input data (e.g., "I enjoy gardening as a hobby and used to work in sales. I'm interested in outdoor activities and community activities, but recently I've been wanting to do something more relaxing") is prepared as a transmission request. In concrete terms, the user opens a web browser, accesses a login page, enters their username and password, and clicks the login button.

[1647] Step 2:

[1648] Sending input information to the server

[1649] The input data generated by the device is sent to the server using the HTTPS protocol. An encrypted channel is used for communication. The input data is decoded on the server side and prepared for further processing. Specifically, the user enters information into the input form and clicks the "Submit" button. At that time, the data is sent asynchronously using an AJAX request.

[1650] Step 3:

[1651] Analysis of information

[1652] The server inputs the user's input information into a generative AI model. The generative AI model (e.g., Python's Pytorch or GPT-3) is used to analyze the data and list appropriate activities and hobbies. The input data is passed to the generative AI model, and the analysis results, which are listed as activities and hobbies, are generated in JSON format. Specifically, a Python script is executed, the generative AI model analyzes the data, and the results are output.

[1653] Step 4:

[1654] Emotion recognition by emotion recognition means

[1655] The server receives emotion recognition data (e.g., from a facial recognition camera or Emotion API) and evaluates the user's emotional state. Based on this, the analysis results are prioritized. The emotion data is processed in real time and indicators such as stress levels are calculated. Specifically, the emotion recognition device collects emotion data, and the server analyzes it.

[1656] Step 5:

[1657] Narrowing down through persona analysis

[1658] The server uses the persona analysis function to further narrow down the listed activities and hobbies based on the analysis results and emotional data. A persona analysis algorithm (e.g., Scikit-learn or TensorFlow) is run to determine the best options. The input data and analysis results are passed to the persona analysis algorithm, which outputs the narrowed down results. Specifically, the persona analysis script is run on the server.

[1659] Step 6:

[1660] Obtaining related information

[1661] The server retrieves information related to the narrowed-down activities and hobbies from the database. It issues an SQL query to retrieve the target data and formats it as a response. The narrowed-down activities and hobbies are used in the database query, and the relevant information is returned in JSON format. Specifically, the server executes the SQL query and retrieves the information from the database.

[1662] Step 7:

[1663] Providing information

[1664] The server sends the retrieved relevant information to the user's device and displays it on the user's interface. The data is visually organized and displayed using HTML and CSS, allowing the user to review the information and make decisions. Specifically, the server sends the retrieved data in JSON format to the device, where it is displayed on the device's interface.

[1665] Step 8:

[1666] Activity selection and planning

[1667] The user selects activities and hobbies based on the displayed information and creates a specific plan. The user's selection is passed to the next processing step. On the device interface, the user clicks the "Join" button and registers the schedule in conjunction with the calendar app. Specifically, the device automatically generates a schedule based on the activities selected by the user.

[1668] Step 9:

[1669] Matching implementation

[1670] The server uses a matching algorithm to match the user with relevant stores and services. The server provides optimal contact information and detailed information. The matching results are generated and notified to the user. Specifically, the server executes the algorithm and sends the appropriate contact information to the user's device.

[1671] Step 10:

[1672] Contracts and fee collection

[1673] When a contract is concluded between the user and the store or service, the server records that information and collects the fee. The fee is processed using a payment system (e.g., PayPal API or Stripe API). The information about the conclusion of the contract is passed as input data to the payment system, which then processes the fee. Specifically, the server calls the payment API and completes the fee transaction.

[1674] (Application example 2)

[1675] 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."

[1676] There is a lack of methods to suggest optimal activities for retirement based on personal preferences and experiences. There is also a lack of technology that suggests appropriate activities while taking into account the user's emotions. Furthermore, there is a lack of systems that allow users to easily access and schedule suggested activities. Therefore, there is a need for methods to enrich retirement life.

[1677] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an emotion recognition means for recognizing the user's emotions and reflecting them in the proposals, an input means for the user to input their preferences and experiences, an analysis means for analyzing the user's input information using a generative AI model and listing appropriate activities and hobbies, a narrowing down means for narrowing down the listed activities and hobbies based on persona analysis, an information acquisition means for acquiring information related to the narrowed down activities and hobbies, a provision means for providing the acquired information to the user, a notification means for notifying the user of recommended activities, and a schedule setting means for setting a schedule based on the proposed activities. This makes it possible to propose optimal post-retirement activities taking into account the user's personal information and emotions.

[1678] The "input means" is an interface that allows the user to input their own preferences and experiences.

[1679] The "analysis means" is a device that uses a generative AI model to analyze the user's input information and list appropriate activities and hobbies.

[1680] A "narrowing tool" is a device that has the function of further narrowing down the activities and hobbies listed based on persona analysis.

[1681] The "information acquisition means" is a device that acquires information related to the narrowed-down activities and hobbies from a database.

[1682] The "providing means" is a device that provides the acquired information to the user.

[1683] An "emotion recognition means" is a device that recognizes the user's emotions in real time and reflects them in suggestions.

[1684] The "notification means" is a device that has the function of notifying the user of recommended activities.

[1685] A "schedule setting means" is a device that has the function of setting a schedule for a user based on suggested activities.

[1686] To implement the present invention, a system including emotion recognition means, input means, analysis means, narrowing means, information acquisition means, provision means, notification means, and schedule setting means is required.

[1687] System configuration and operation

[1688] The system consists of a user terminal, a server, and related databases. The operation of each component of the system is described in detail below.

[1689] User terminal

[1690] First, users log in to the system using their device (smartphone or tablet). After logging in, they can enter information about their preferences and experiences. An input method is provided, and an interface is prepared for users to enter details about their hobbies, work history, interests, etc.

[1691] server

[1692] The server includes the following means:

[1693] 1. Input Method

[1694] It provides an interface for users to input their preferences and experiences.

[1695] 2. Analysis method

[1696] The server receives the information entered by the user and analyzes it using a generative AI model, resulting in a list of activities and hobbies that are best suited to the user.

[1697] 3. Emotion recognition means

[1698] It includes a software module for recognizing users' emotions in real time, and this emotional data is reflected in the analysis results, improving the accuracy of the proposal activities.

[1699] 4. Narrowing methods

[1700] Based on persona analysis, narrow down the list of activities and hobbies generated to the most suitable items.

[1701] 5. Information acquisition means

[1702] It has the ability to retrieve information related to narrowed-down activities and hobbies (e.g., location, time, price) from a database.

[1703] 6. Means of provision

[1704] This is a means for providing the acquired information to the user. Specifically, it sends the information to the user's terminal and displays it.

[1705] 7. Means of notification

[1706] Notify users about recommended activities.

[1707] 8. Scheduling Methods

[1708] It is a way to set a schedule for the user based on suggested activities, and it also works with notifications to set reminders.

[1709] Hardware and Software

[1710] Emotion Recognition Engine: A software module for recognizing user emotions in real time.

[1711] Generative AI model: A model that analyzes user input and lists optimal activities and hobbies.

[1712] Database: A database that stores information about activities and hobbies and is accessed by information retrieval methods.

[1713] Specific examples

[1714] Suppose a user inputs "cooking" as their hobby, "sales" as their work history, "handicrafts" as their interest, and "slightly tired" as their current emotional state. This information is sent to the server and analyzed by the analysis means. The generative AI model lists activities such as "nearby handicraft classes" and "cooking workshops." The emotion recognition means confirms the emotion of "slightly tired," and prioritizes the relaxing "handicraft classes." The narrowing means selects more accurate activities, and the information acquisition means acquires specific location, time, and price information from the database. The provision means displays the information on the user's terminal, and the notification means notifies the user of recommended activities. Finally, the schedule setting means allows the user to set a schedule for the handicraft classes.

[1715] Prompt Sentence Examples

[1716] User Preferences: ["Cooking", "Crafts"]

[1717] User Experience: "Sales Job"

[1718] Current Emotion: "Slightly tired"

[1719] The above is a specific embodiment for carrying out the invention.

[1720] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1721] Step 1:

[1722] A user logs in to the system using a device. The user accesses the app's login screen and completes the login by entering their personal authentication information. The input data is the user's ID and password, and the output is access permission.

[1723] Step 2:

[1724] The user inputs their interests, experiences, and current emotional state into the terminal. Specifically, they input information such as "cooking" as a hobby, "sales experience," and an interest in "handicrafts." They also input "slightly tired" as their current emotional state. This information is sent to the server as input data.

[1725] Step 3:

[1726] The server inputs the received user information into a generative AI model for analysis. The input data is the user's preferences, experiences, and emotional state, and the output is a list of activities and hobbies that are best suited to the user. The generative AI model analyzes this data and lists activities such as "nearby craft classes" and "cooking workshops."

[1727] Step 4:

[1728] The server analyzes the user's emotional data using an emotion recognition means. The input data is the user's current emotional state, and the output is a list of activities that take emotions into account. Reflecting the emotional data of "slightly tired," the server prioritizes the suggestion of "sewing classes" to relax.

[1729] Step 5:

[1730] The server uses a refinement method to further refine the generated activity list based on persona analysis. The input data is the activity list and emotion recognition data, and the output is the refined activities that are most suitable for the user. Here, "Handicraft class" is particularly recommended from the refined list.

[1731] Step 6:

[1732] The server uses the information acquisition means to acquire detailed information related to the narrowed-down activities from the database. Specifically, it acquires information such as the location, time, and fee of the handicraft class. The input data is the narrowed-down activity name, and the output is the detailed information.

[1733] Step 7:

[1734] The server provides the acquired detailed information to the user terminal. Using the providing means, information such as the location, time, and fee of the handicraft class is displayed on the user terminal. The input data is the detailed information, and the output is the information displayed to the user.

[1735] Step 8:

[1736] The server uses the notification mechanism to notify the user about the recommended activity. The input data is the information provided, and the output is the notification content. The user receives a notification confirming "attend a sewing class."

[1737] Step 9:

[1738] The user selects the suggested activities and sets the schedule. The user confirms the dates and times of the craft classes and inputs the schedule. The input data is the user's schedule information, and the output is the scheduled information.

[1739] Step 10:

[1740] The server uses the schedule setting means to check the user's schedule setting and activate the reminder function, so that the user receives reminder notifications based on the set schedule. The input data is schedule information, and the output is reminder notifications.

[1741] The above is the specific processing flow of the present invention. Through this series of steps, the user can find the most suitable activity based on their personal tastes and feelings, and live a comfortable life after retirement.

[1742] 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.

[1743] 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.

[1744] 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.

[1745] 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.

[1746] 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.

[1747] 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.

[1748] 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).

[1749] 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.

[1750] 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."

[1751] 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.

[1752] 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).

[1753] 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.

[1754] 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.

[1755] 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.

[1756] 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.

[1757] 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.

[1758] 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.

[1759] 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.

[1760] 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.

[1761] 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.

[1762] 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.

[1763] The following is further disclosed regarding the above embodiment.

[1764] (Claim 1)

[1765] An information processing device using a generative AI model that suggests post-retirement activities based on personal preferences and experiences.

[1766] an input means for a user to input preferences and experiences;

[1767] An analytical method that uses a generative AI model to analyze user input information and create a list of appropriate activities and hobbies;

[1768] A means of narrowing down the activities and hobbies listed based on persona analysis;

[1769] an information acquisition means for acquiring information related to the narrowed-down activities or hobbies;

[1770] and providing means for providing the acquired information to a user.

[1771] (Claim 2)

[1772] 2. The system according to claim 1, wherein the information acquisition means provides the user with detailed information about stores and services that will enable the user to realize the activity.

[1773] (Claim 3)

[1774] 2. The system according to claim 1, wherein the providing means collects a fee when a contract is concluded between the user and the store or service.

[1775] "Example 1"

[1776] (Claim 1)

[1777] an input means for a user to input preferences and experiences;

[1778] An analytical method that uses a generative AI model to analyze user input information and create a list of appropriate activities and hobbies;

[1779] A means of narrowing down the activities and hobbies listed based on persona analysis;

[1780] an information acquisition means for acquiring information related to the narrowed-down activities or hobbies;

[1781] providing means for providing the acquired information to a user;

[1782] A matching means for matching users with relevant stores and services as needed;

[1783] A fee collection means for collecting a fee when a contract is concluded between the user and a store or service;

[1784] A system including:

[1785] (Claim 2)

[1786] 2. The system according to claim 1, wherein the information acquisition means provides the user with detailed information for realizing the activity.

[1787] (Claim 3)

[1788] 2. The system according to claim 1, wherein the providing means includes an interface that transmits the relevant information to the user terminal and displays it in a form that can be intuitively understood by the user.

[1789] "Application Example 1"

[1790] text

[1791] (Claim 1)

[1792] An information processing device using a generative AI model that suggests post-retirement activities and dining experiences based on personal preferences and experiences.

[1793] an input means for a user to input preferences and experiences;

[1794] An analytical method that uses a generative AI model to analyze the user's input information, list appropriate activities and hobbies, and list recommended recipes and events to participate in;

[1795] A filtering method to narrow down the activities, hobbies, recommended recipes, and events to attend that are listed based on persona analysis;

[1796] an information acquisition means for acquiring information related to the narrowed-down activities, hobbies, recommended recipes, and participating events;

[1797] providing means for providing the acquired information to a user;

[1798] A means for users to have the ingredients and cooking equipment they need delivered;

[1799] A system including:

[1800] (Claim 2)

[1801] 2. The system according to claim 1, wherein the information acquisition means provides the user with detailed information about stores and services, and necessary ingredients and cooking utensils for carrying out the activity.

[1802] (Claim 3)

[1803] 2. The system according to claim 1, wherein the providing means collects a fee when a contract is concluded between the user and a store or service, or between the user and a delivery service.

[1804] "Example 2: Combining Emotion Engines"

[1805] (Claim 1)

[1806] an input means for a user to input information about preferences, experiences, and emotions;

[1807] a communication means for transmitting input information to a server;

[1808] An analytical method that uses a generative AI model to analyze user input information and create a list of appropriate activities and hobbies;

[1809] emotion recognition means for recognizing the user's emotion and reflecting it in the analysis result;

[1810] A means of narrowing down the activities and hobbies listed based on persona analysis;

[1811] an information acquisition means for acquiring information related to the narrowed-down activities or hobbies;

[1812] providing means for providing the acquired information to a user;

[1813] A matching means for matching users with relevant stores and services;

[1814] A fee collection means for collecting a fee when a contract is concluded between the user and a store or service;

[1815] A system including:

[1816] (Claim 2)

[1817] 2. The system according to claim 1, wherein the information acquisition means provides the user with detailed information about stores and services that will enable the user to realize the activity.

[1818] (Claim 3)

[1819] 2. The system according to claim 1, wherein the providing means collects a fee when a contract is concluded between the user and the store or service.

[1820] "Application example 2 when combining emotion engines"

[1821] (Claim 1)

[1822] An information processing device using a generative AI model that suggests post-retirement activities based on personal preferences and experiences.

[1823] an input means for a user to input preferences and experiences;

[1824] An analytical method that uses a generative AI model to analyze user input information and create a list of appropriate activities and hobbies;

[1825] A means of narrowing down the activities and hobbies listed based on persona analysis;

[1826] an information acquisition means for acquiring information related to the narrowed-down activities or hobbies;

[1827] providing means for providing the acquired information to a user;

[1828] an emotion recognition means for recognizing a user's emotion and reflecting it in suggestions;

[1829] A notification method to notify users of recommended activities;

[1830] a scheduling means for setting a schedule based on the proposed activities;

[1831] A system including:

[1832] (Claim 2)

[1833] 2. The system according to claim 1, wherein the information acquisition means provides the user with detailed information about places and services for realizing the activity.

[1834] (Claim 3)

[1835] 2. The system according to claim 1, wherein the providing means collects a fee when a contract is concluded between the user and the location or service. [Explanation of symbols]

[1836] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. An information processing device using a generative AI model that suggests post-retirement activities based on personal preferences and experiences. an input means for a user to input preferences and experiences; An analytical method that uses a generative AI model to analyze user input information and create a list of appropriate activities and hobbies; A means of narrowing down the activities and hobbies listed based on persona analysis; an information acquisition means for acquiring information related to the narrowed-down activities or hobbies; and providing means for providing the acquired information to a user.

2. 2. The system according to claim 1, wherein the information acquisition means provides the user with detailed information about stores and services for realizing the activity.

3. 2. The system according to claim 1, wherein the providing means collects a fee when a contract is concluded between the user and the store or service.

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