System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving profile data input by a user; means for generating a plurality of activity candidates suitable for the user based on the profile data; means for presenting the generated activity candidates to the user; means for processing an application for participation in an activity based on the activity selected by the user; means for sending a notification to an associated community or party based on the processed application; and means for providing detailed information about the activity to the user based on the notification.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] After retirement, many people lose their jobs and face the problem of losing their purpose and goals in life. This leads to an increase in the number of elderly people who suffer from social isolation and mental anxiety. Many elderly people also have difficulty finding new activities and communities that suit them. To solve these problems, a system is needed that makes it easy to find appropriate activities that give people meaning in life and that can match them quickly and effectively. [Means for solving the problem]

[0005] The present invention relates to a system designed to help retired people find new meaning in life. The system includes the following means: a means for receiving profile data entered by a user; a means for generating a plurality of candidate activities suitable for the user based on the profile data; a means for presenting the generated candidate activities to the user; a means for processing a request to participate in an activity selected by the user based on the selected activity; and a means for sending a notification to a related community or person based on the processed request to participate. The system also includes a means for providing the user with detailed information about the activity based on the notification. This configuration allows users to easily find activities and communities suitable for them, enabling them to live a fulfilling life with meaning.

[0006] "Users" refer to individuals who use the system to find activities and communities after retirement.

[0007] "Profile data" refers to data entered by a user about their hobbies, interests, skills, location, and other information.

[0008] "Means for receiving" refers to the function of incorporating profile data sent by users into the system.

[0009] "Means for analyzing" refers to a function that analyzes data to find activities and communities that are most suitable for the user based on the received profile data.

[0010] The "means for generating activity candidates" refers to a function for generating multiple activity and community candidates suitable for the user based on the analyzed data.

[0011] The "presentation means" refers to a display function for showing the generated activity candidates to the user.

[0012] "Means for processing participation requests" refers to the function of processing a user's participation request based on the activity selected by the user and making it a formal request within the system.

[0013] "Means for sending notifications" refers to communication facilities for sending notifications to relevant communities or parties based on processed participation applications.

[0014] The "means for providing detailed information" refers to a function that provides the user with detailed information about the activity in which they are participating.

[0015] "Activity" refers to a specific hobby, learning, social, or other event or community in which a user wishes to participate.

[0016] A "community" refers to a group or gathering of people who share a particular hobby or interest.

[0017] "AI algorithm" refers to an artificial intelligence algorithm that analyzes a user's profile data and generates optimal activity suggestions. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

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

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] This invention relates to a system that matches appropriate communities and activities to users who are looking for new meaning in life after retirement. Specifically, it involves a series of processes that exchange data between a server, terminals, and users, and uses AI to suggest optimal activities and communities.

[0040] System configuration

[0041] 1. User fills out profile

[0042] A user accesses a dedicated terminal or web service and enters information about their hobbies, interests, skills, region, etc. As a specific example, consider the case where a user selects gardening, cooking, and travel as hobbies and enters camera photography as a skill.

[0043] 2. The server receives the data

[0044] The server receives the profile data entered by the user and stores it in a temporary database, and it is important that the data is received accurately during this process.

[0045] 3. Data Analysis

[0046] An AI algorithm on the server analyzes the received profile data, for example, searching for active gardening clubs and related events based on the hobby "gardening."

[0047] 4. Generating Matching Candidates

[0048] Based on the analysis results, the server will then list multiple activity options suitable for the user, such as gardening clubs, cooking classes, and travel groups.

[0049] 5. Present candidates to the user

[0050] The device presents the matching candidates sent from the server to the user, and the user's screen displays detailed information about the activity and the profiles of the potential participants.

[0051] 6. User Selection and Participation Application

[0052] The user selects an activity that interests them and submits an application to participate, for example, if the user wishes to join a gardening club, they submit an application to that club.

[0053] 7. Application Processing and Notification

[0054] The server processes the user's request to join and sends a notification to the organizer of the corresponding community, who then receives the new joiner's information.

[0055] 8. Providing more information

[0056] The device will notify the user of participation approval and detailed information, including the event schedule, activities, and meeting place.

[0057] 9. User Participation

[0058] The user then participates in an actual activity based on the information provided, for example, attending the first meeting of a gardening club.

[0059] Through the above process, users can easily find new meaning in life and live a fulfilling life. This system is characterized by the efficient exchange of data between the server, device, and user, and by using AI to perform optimal matching.

[0060] The processing flow will be explained below.

[0061] Step 1:

[0062] Users enter their profile data, such as hobbies, interests, skills, and location, into a form on a dedicated device or web service, and press the "Submit" button. This information is needed for subsequent analysis and matching.

[0063] Step 2:

[0064] The server receives the profile data sent by the user, parses the data sent in the HTTP request, converts it into the required format, and stores it in a temporary database.

[0065] Step 3:

[0066] The AI ​​algorithm on the server analyzes the received profile data. At this stage, it searches the database for activities and communities that match the user's hobbies, interests, and skills. For example, if a user enters "gardening" as a hobby, it will extract community data related to gardening.

[0067] Step 4:

[0068] The server generates multiple activity suggestions suitable for the user based on the analysis results of the AI ​​algorithm. Here, a list of suggested activities is created based on the user's interests and skills. Examples may include gardening clubs, cooking classes, travel circles, etc.

[0069] Step 5:

[0070] The server transmits the generated activity candidate data to the terminal, where the data is converted into a format suitable for display on the user's display screen.

[0071] Step 6:

[0072] The device displays the matching candidates sent from the server to the user, and the user can check the details of the activity, the profiles of the potential participants, the date and time, and the location of the event.

[0073] Step 7:

[0074] The user selects the activity they are interested in and applies to participate. When the user presses the "Apply to participate" button, the information is sent to the server.

[0075] Step 8:

[0076] The server receives and processes the user's participation application data, checks which community the user has applied to join, and sends a notification to the organizer of the corresponding community.

[0077] Step 9:

[0078] The server sends a notification to the organizer and prepares to provide the user with participation acceptance and activity details, including the participation acceptance message, event details, and meeting place information.

[0079] Step 10:

[0080] The terminal notifies the user of the participation approval and detailed information sent from the server, and the user confirms the date, location, and belongings of the activity to be participated in based on this information.

[0081] Step 11:

[0082] The user can then participate in actual activities based on the information provided. For example, by participating in the first meeting of a gardening club, the user has the opportunity to find a new purpose in life.

[0083] Following these detailed steps will help users find new activities and communities that suit them, helping them find meaning in their post-retirement lives.

[0084] Example 1

[0085] 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."

[0086] Users looking for new meaning in life after retirement need to be able to easily find the right community or activity. However, conventional systems often fail to find activities or communities that best suit a user's individual interests and skills. Another issue with these systems is that they require users to manually search through multiple options and select the one that best suits them.

[0087] 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.

[0088] In this invention, the server includes means for receiving profile data input by a user, means for analyzing the profile data, and means for generating a plurality of activity candidates suitable for the user based on the analysis results, thereby enabling the user to easily find activities and communities that best suit their interests and skills.

[0089] "User" refers to an individual who uses the system to enter profile data and find activities and communities that best suit them.

[0090] "Profile Data" refers to information entered by a user, such as hobbies, interests, skills, and location.

[0091] "Means for analyzing" refers to a function that performs calculations to find the activities and communities that are most suitable for the user based on the input profile data.

[0092] "Suggested Activities" refers to activities or communities that may be suggested to a user based on analyzed profile data.

[0093] "Means for generating" refers to the function of listing multiple candidate activities based on the analysis results and making them ready to present to the user.

[0094] The "means for presenting" refers to a function for displaying the generated activity candidates on the screen in a manner that is visible to the user.

[0095] "Means for processing participation applications" refers to the function of accepting a user's intention to participate in an activity selected by the user and processing it within the system.

[0096] "Means for sending notifications" refers to the functionality for sending notifications to relevant communities and stakeholders based on processed participation applications.

[0097] The "means for providing detailed information" refers to a function for notifying the user of specific information regarding activities after participation is approved.

[0098] This invention relates to a system that matches appropriate communities and activities to users who are looking for new meaning in life after retirement. Data is exchanged between a server, a terminal, and the user, and optimal activities and communities are suggested using AI. Specific embodiments of this system are described below.

[0099] System Configuration

[0100] The system mainly consists of the following components:

[0101] 1. Means of receiving your profile data

[0102] 2. Means of analyzing profile data

[0103] 3. A method for generating candidate activities based on the analysis results

[0104] 4. Means of presenting suggested activities to users

[0105] 5. Means of handling user activity selection and participation requests

[0106] 6. Means of sending notifications based on participation requests

[0107] 7. Means of providing users with more information about their activities

[0108] Hardware and Software

[0109] server:

[0110] Hardware: General server equipment (e.g., dual-core or quad-core CPU, 16GB RAM, SSD storage)

[0111] Software: Web frameworks such as Django or Flask, machine learning libraries such as Scikit-learn or TensorFlow, and database systems such as MySQL or PostgreSQL.

[0112] Device:

[0113] Hardware: Personal computers, tablets, smartphones

[0114] Software: Web browser, JavaScript framework (e.g. React)

[0115] Processing flow

[0116] The server receives profile data entered by the user. The user accesses a dedicated terminal or web service and enters information such as hobbies, interests, skills, and location. For example, consider a user entering, "I'm interested in gardening, cooking, and traveling. I'm good at photography."

[0117] The server stores the received profile data in a temporary database. This process requires validation to ensure the accuracy of the data. Implement data validation functionality using a web framework such as Django or Flask.

[0118] Next, AI algorithms in the server analyze the received profile data. For example, based on the hobby "gardening," they search for currently active gardening clubs and related events. This analysis is performed using Python-based machine learning libraries such as Scikit-learn and TensorFlow.

[0119] Based on the analysis results, the server generates multiple activity candidates suitable for the user. These candidates are stored in a database system such as MySQL or PostgreSQL. The generated activity candidates are updated in real time to include the latest activity and event information.

[0120] The user's device presents these activity suggestions sent from the server. Detailed information about the listed activities and profiles of potential participants are displayed on the user's screen. This display is done using the JavaScript framework React.

[0121] Users select an activity they are interested in and submit a participation request. For example, a user may request, "I would like to join the gardening club." This request data is again sent to the server via a RESTful API, and the server processes the user's participation request. This process includes temporarily storing the data required for participation and sending notifications to related communities and stakeholders. Notifications are sent using SendGrid or Firebase Cloud Messaging.

[0122] Finally, the server notifies the user of the approval and detailed information, such as "The first meeting of the gardening club will be held next Saturday at 2:00 PM in the flowerbeds of the park." Based on this information, the user can then participate in the actual activity.

[0123] Specific examples

[0124] Prompt Sentence Examples

[0125] "I'd like to find a new hobby after retirement. I'm interested in gardening, cooking, and traveling. I'm good at photography. Please introduce me to some suitable activities and communities."

[0126] As a result, this system helps users easily find new meaning in life and continue to live a fulfilling life.

[0127] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0128] Step 1:

[0129] The user enters their profile. They access a dedicated device or a web service and enter information such as hobbies, interests, skills, and location. The entered data (e.g., hobbies are gardening, cooking, and travel, and skills are photography) is sent via an HTML form.

[0130] Input: User's hobbies, interests, skills, and location

[0131] Output: Profile data

[0132] Step 2:

[0133] The server receives the data. The server receives the profile data submitted by the user via a RESTful API, stores the data in a temporary database (e.g., SQLite or PostgreSQL), and performs validation to ensure the data is correct.

[0134] Input: Profile data

[0135] Output: Validated data

[0136] Step 3:

[0137] The server analyzes the data. The validated data is then input into a machine learning model to analyze the user's interests and skills. Specifically, it uses Scikit-learn and TensorFlow to generate a list of candidate activities.

[0138] Input: Validated data

[0139] Output: Analysis results (list of activity candidates)

[0140] Step 4:

[0141] The server generates matching candidates. Based on the analysis results, it selects multiple activity candidates suitable for the user and stores them in a database such as MySQL or PostgreSQL. This list includes detailed information about the activities and their profiles.

[0142] Input: Analysis results (list of activity candidates)

[0143] Output: Generated activity candidates

[0144] Step 5:

[0145] The device presents candidates to the user. The activity candidates sent from the server are displayed on the user's screen. The JavaScript framework React is used to display detailed information about the listed activities and profiles of the participants.

[0146] Input: Generated activity candidates

[0147] Output: The screen displayed to the user

[0148] Step 6:

[0149] The user selects an activity they are interested in and submits a participation request. The user selects an activity they are interested in on the system and submits a participation request for the activity. This application data is again sent to the server via the RESTful API.

[0150] Input: User activity selection, participation application

[0151] Output: Participation application data

[0152] Step 7:

[0153] The server processes the participation requests. The server processes the received participation request data and sends notifications to relevant communities and stakeholders. This notification is done using SendGrid or Firebase Cloud Messaging.

[0154] Input: Participation application data

[0155] Output: Send notification

[0156] Step 8:

[0157] The terminal provides detailed information to the user. Based on the content of the notification sent by the server, the user is notified of specific activity information (such as the event schedule and meeting place).

[0158] Input: Notification content

[0159] Output: Provides detailed information

[0160] Step 9:

[0161] The user participates in an activity. The user participates in an actual activity based on the notified activity information. For example, the user heads to a designated flower bed in a park to participate in the first meeting of the gardening club.

[0162] Input:Detailed information

[0163] Output: User activity participation

[0164] (Application example 1)

[0165] 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."

[0166] In modern society, finding a new purpose in life after retirement is important for many people. However, finding suitable communities and activities can be difficult. In particular, physical constraints and a lack of information make it difficult to confirm the content of activities before actually participating. Furthermore, conventional methods have limited ability to suggest optimal activities based on the user's hobbies and skills.

[0167] 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.

[0168] In this invention, the server includes: means for receiving profile data entered by a user; means for generating multiple activity candidates suitable for the user based on the profile data; means for presenting the generated activity candidates to the user; means for processing a request to participate in an activity selected by the user based on the selected activity; means for sending a notification to a related community or related party based on the processed participation request; means for providing the user with detailed information about the activity based on the notification; means for suggesting activity candidates based on the user profile using a generative AI model; and means for the user to virtually experience the suggested activities using a virtual reality device. This allows the user to virtually experience the target activities, making it easier to select an appropriate activity. This makes the process of finding a new purpose in life more efficient and effective.

[0169] Definitions of important words

[0170] "Profile Data" is data entered by a user that includes personal information such as hobbies, interests, skills, and location.

[0171] "Suggested Activities" refers to suitable communities and events based on the user's profile data.

[0172] "Generative AI Model" means an artificial intelligence model used to suggest optimal activities based on a user profile.

[0173] A "virtual reality device" is hardware that enables a user to virtually experience activities in a virtual reality environment, and examples include VR headsets.

[0174] "Visiting" is the process of using virtual reality devices to simulate an activity before participating in it.

[0175] A "notification" is a message sent to a related community or person concerned about the processing result or detailed information of an application to participate in an activity.

[0176] MODE FOR CARRYING OUT THE INVENTION

[0177] The embodiment of the present invention includes the following procedures and hardware / software configurations.

[0178] Hardware and Software Configuration

[0179] Hardware:

[0180] Smartphone

[0181] Head-mounted displays (e.g., Oculus Rift, HTC Vive)

[0182] server

[0183] Database

[0184] software:

[0185] Python

[0186] SQLite3

[0187] OpenAI API

[0188] A web interface (for users to enter their profile data)

[0189] Virtual reality applications (for users to have a virtual experience)

[0190] Process Details

[0191] User fills out profile

[0192] Users access a dedicated terminal or web interface and enter information about their hobbies, interests, skills, location, etc. This information is collected as "profile data" and sent to a server.

[0193] Data reception and storage

[0194] The server receives the profile data entered by the user and stores it in a temporary database (e.g., SQLite3). Input validation and filtering are performed automatically to ensure data accuracy.

[0195] Data analysis

[0196] An AI algorithm on the server analyzes the profile data and lists multiple activity candidates suitable for the user. The analysis is performed using the OpenAI API, and the generative AI model suggests appropriate communities and activities based on the user's hobbies and skills.

[0197] Presentation of match candidates

[0198] The user's terminal or VR device displays the activity candidates sent from the server. The user can view the activity details and select the activity that interests them.

[0199] Trial experience of the activity

[0200] When using a head-mounted display, users can virtually experience the proposed activity, allowing them to check the atmosphere and content of the activity before actually participating.

[0201] Specific examples

[0202] If a user inputs hobbies such as "gardening," "cooking," and "traveling" and "photography skills," the system sends the following prompts to the generative AI model:

[0203] plaintext

[0204] Hobbies: Gardening, Cooking, Traveling, Skills: Photography, Region: Tokyo, please suggest suitable communities and activities.

[0205] The generated activity candidates may look like this:

[0206] 1. Gardening Club

[0207] 2. Cooking Classes

[0208] 3. Travel Circle

[0209] Users can try out these options using a VR device and select the activity that best suits them. For example, experiencing the atmosphere and activities of a gardening club in VR can solidify their desire to participate. Furthermore, users will automatically be notified of the details of their chosen activity and be notified of the necessary participation details.

[0210] This invention allows users to discover more relevant and attractive communities and activities through virtual experiences. Furthermore, by utilizing a generative AI model, it is possible to make recommendations that are optimized for each individual user. This system aims to improve the user experience, which was difficult to achieve with conventional methods.

[0211] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0212] Program processing flow

[0213] Step 1:

[0214] The user accesses a dedicated terminal or web interface and enters their profile data, such as hobbies, interests, skills, and region. The entered data is sent to a temporary database. Input: Hobbies, interests, skills, region Output: User profile data

[0215] Step 2:

[0216] The server receives the profile data entered by the user. The received data undergoes syntax checking and input filtering and is then saved in a temporary database (e.g., SQLite3). Input: User profile data Output: Profile data saved in the database

[0217] Step 3:

[0218] The AI ​​algorithm on the server analyzes the received profile data. At this time, a generative AI model is used to list multiple activity candidates suitable for the user. A prompt statement is sent to the generative AI model to obtain recommended activity candidates. Input: Saved profile data, prompt statement (example: "Based on hobbies: gardening, cooking, travel, skills: photography, and area: Tokyo, please suggest appropriate communities and activities.") Output: Generated list of activity candidates

[0219] Step 4:

[0220] The server sends the generated activity candidate list to the terminal, which then displays it to the user. The user then views detailed information about these activity candidates through a screen or VR device. Input: Activity candidate list Output: Activity candidate details displayed on the user's terminal

[0221] Step 5:

[0222] The user selects an activity that interests them and applies to participate in that activity. The application is sent to the server via the terminal. Input: Activity selected by the user Output: Application to participate

[0223] Step 6:

[0224] The server processes the request and sends notifications to the relevant communities and stakeholders. These notifications include the request and the user's profile data. Input: Request to join. Output: Notifications sent to the relevant communities.

[0225] Step 7:

[0226] The server receives participation approval and detailed information from related communities and stakeholders, and sends it to the user's terminal. The detailed information includes the event schedule, activities, meeting place, etc. Input: Approval and detailed information from related communities Output: Detailed information sent to the user's terminal

[0227] Step 8:

[0228] The user uses a head-mounted display to virtually experience the proposed activity. The virtual experience simulates the atmosphere and content of the actual activity in a VR environment. Input: Detailed information about the proposed activity. Output: VR experience of the virtual activity that the user has virtually experienced.

[0229] Step 9:

[0230] The user finally decides which activities they want to participate in, and the server sends a final notification to the relevant community. Input: User's selection after virtual experience Output: Final notification

[0231] 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.

[0232] This invention relates to a system that matches appropriate communities and activities to users who are looking for new meaning in life after retirement. In particular, by incorporating an emotion engine, this system enables matching that takes into account the user's emotional state. Specifically, it involves a series of processes that exchange data between a server, terminal, and user, and uses AI and the emotion engine to suggest optimal activities and communities.

[0233] System configuration

[0234] 1. The user enters their profile data and emotional data.

[0235] A user accesses a dedicated device or web service and enters profile data such as their hobbies, interests, skills, and location. Furthermore, the emotion recognition system inputs or detects their current emotional state. As a concrete example, consider the case where a user selects gardening, cooking, and travel as hobbies and registers camera photography as a skill, and the emotion engine recognizes the emotion as "relaxed."

[0236] 2. The server receives the data

[0237] The server receives the profile data and emotion data entered by the user and stores them in a temporary database. For example, a user who is relaxed may be suited to a gardening club, which has a stress-reducing effect.

[0238] 3. Data Analysis

[0239] The AI ​​algorithm in the server analyzes the received profile and emotional data. At this stage, it searches the database for activities and communities that take into account the user's current emotional state, along with their hobbies, interests, and skills. For example, a user who is "relaxing" will be presented with activities that have a relaxing effect.

[0240] 4. Generating Matching Candidates

[0241] The server generates multiple activity candidates suitable for the user based on the analysis results of the AI ​​and emotion engine. This process lists activities that match the user's current emotional state. For example, it may include gardening clubs, cooking classes, travel circles, etc. that reflect the user's interests and emotional state.

[0242] 5. Present candidates to the user

[0243] The device presents the matching candidates sent from the server to the user, who is then shown detailed information about the activity, the reason for the recommendation based on the user's emotional state, and the profile of the potential participants.

[0244] 6. User Selection and Participation Application

[0245] The user selects an activity that they are interested in and submits an application to participate in. For example, if the user wants to join a gardening club based on the reasons recommended by the emotion engine, they submit an application to join the club.

[0246] 7. Application Processing and Notification

[0247] The server processes the user's request to join and sends a notification to the organizer of the corresponding community, who then receives the new joiner's information.

[0248] 8. Providing more information

[0249] The terminal notifies the user of participation approval and activity details, including a participation approval message, event details, and meeting place information.

[0250] 9. User Participation

[0251] The user can then participate in actual activities based on the information provided. For example, by participating in the first meeting of a gardening club, the user has the opportunity to find a new purpose in life.

[0252] Through this process, users can easily find new activities and communities that suit them, enabling them to live fulfilling lives. This system is characterized by the efficient exchange of data between the server, device, and user, and by using AI and an emotion engine to perform optimal matching.

[0253] The processing flow will be explained below.

[0254] Step 1:

[0255] The user enters their profile data and emotional data. They fill out information such as hobbies, interests, skills, and location on a dedicated device or a form on a web service, and then press the "Submit" button. The emotion recognition system also detects the user's current emotional state, and this data is also sent. For example, if a user selects "gardening," "cooking," and "travel" as their hobbies and inputs camera photography as a skill, their emotional state is recognized as "relaxed."

[0256] Step 2:

[0257] The server receives the profile data and emotion data sent by the user, converts this data into an analyzable format, and stores it in a temporary database.

[0258] Step 3:

[0259] An AI algorithm in the server analyzes the received profile and emotional data. For example, based on the hobby of "gardening" and the emotional state of "relaxation," it searches a database for relaxing activities related to gardening.

[0260] Step 4:

[0261] The server generates multiple activity suggestions suitable for the user based on the analysis results of the AI ​​algorithm and emotion engine, such as a list of relaxing activities such as gardening clubs, cooking classes, and art therapy.

[0262] Step 5:

[0263] The server transmits the generated activity candidate data to the terminal, where the data is converted to a format suitable for display on the user's display screen.

[0264] Step 6:

[0265] The device displays the matching candidates sent from the server to the user. The user's screen displays detailed information about each activity, the reason for the recommendation (for example, because it is expected to have a relaxing effect), and the profiles of the potential participants.

[0266] Step 7:

[0267] The user selects an activity they are interested in and applies to join. For example, the user clicks the "Apply" button to join the gardening club. This information is sent to the server.

[0268] Step 8:

[0269] The server receives and processes the user's participation application data, checks which community the user has applied to join, and sends a notification to the organizer of the corresponding community.

[0270] Step 9:

[0271] The server sends a notification to the organizer and prepares to provide the user with participation acceptance and activity details, including the participation acceptance message, event details, and meeting place information.

[0272] Step 10:

[0273] The terminal notifies the user of the participation approval and detailed information sent from the server, and the user confirms the activity date, location, belongings, etc. based on this information.

[0274] Step 11:

[0275] The user can then participate in actual activities based on the information provided, for example, attending the first meeting of a gardening club, and gaining the opportunity to find a new purpose in life.

[0276] By following these detailed steps, users can easily find new activities and communities that suit them, and find meaning in their post-retirement lives. By combining it with an emotion engine, matching can be performed taking into account the user's emotional state, resulting in more appropriate activities being selected.

[0277] Example 2

[0278] 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."

[0279] In recent years, an increasing number of elderly people are seeking new meaning in life after retirement. However, it is not easy to find communities and activities that suit their individual interests, skills, and mental state. Conventional systems have difficulty proposing activities that take into account the user's emotional state, and as a result, they often present activities that are not in line with the user's interests. There is a need to solve this problem and propose activities that are optimal for users.

[0280] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving profile data and emotion data input by the user, means for generating a plurality of activity candidates suitable for the user based on the profile data and emotion data, and means for presenting the generated activity candidates to the user. This makes it possible to suggest activities that take into account the user's individual interests, skills, and mental state.

[0281] "Profile Data" refers to personal information about a user, such as their hobbies, interests, skills, and location.

[0282] "Emotion data" refers to information indicative of a user's current emotional state that is collected by an emotion recognition system.

[0283] "Means for receiving" refers to the function or method by which the server receives input data from the user.

[0284] "Means of analysis" refers to the functions and methods by which algorithms and programs within the server analyze the received data and extract useful information from it.

[0285] "Means for generating" refers to a function or method for generating multiple activity candidates suitable for the user based on the analysis results.

[0286] The "means for presenting" refers to a function or method for displaying the generated activity candidates to the user and allowing the user to select one.

[0287] "Means for processing participation requests" refers to the functions and methods for accepting, managing, and processing participation requests for the activities selected by the user.

[0288] "Means for sending notifications" refers to the functions and methods for informing relevant communities or stakeholders based on processed participation applications.

[0289] "Means for providing detailed information" refers to a function or method for informing the user of specific information about the activity (e.g., event dates and meeting places) based on the notification.

[0290] "Suggested Activities" refers to a list of activities and communities that a user can participate in that are suggested based on the user's profile data and emotional data.

[0291] "Database" refers to a system for systematically storing and managing information such as profile data, emotional data, analysis results, and potential activities.

[0292] "AI Algorithm" refers to the artificial intelligence technology used to analyze user data and generate optimal activity suggestions.

[0293] An "emotion recognition system" refers to technology that uses sensors such as cameras and microphones to recognize a user's current emotional state.

[0294] This invention relates to a system that matches appropriate communities and activities to users who are looking for a new purpose in life after retirement. By combining this system with an emotion engine, it enables matching that takes into account the user's emotional state, and it exchanges data between the server, terminal, and user, and uses AI and the emotion engine to suggest optimal activities and communities.

[0295] System configuration

[0296] 1. The user enters their profile data and emotional data.

[0297] Users access a dedicated device or web service and enter profile data such as hobbies, interests, skills, and region. An emotion recognition system using a camera and microphone also inputs or detects the user's current emotional state. For example, a scenario is envisioned in which a user selects "gardening," "cooking," and "travel" as hobbies and registers "photography" as a skill, and the emotion recognition system recognizes the emotion as "relaxed."

[0298] 2. The server receives the data

[0299] The server receives profile and emotion data from users via API and stores it in a temporary database. For example, a user who is relaxing might be suited to a "gardening club" that has a stress-reducing effect.

[0300] 3. Data Analysis

[0301] The AI ​​algorithms on the server analyze the received profile data and emotional data. This analysis involves taking into account the user's hobbies, interests, skills, and emotional state, and searching the database for the most suitable activities and communities. For example, if a user is "relaxing," activities that have a relaxing effect will be presented.

[0302] 4. Generating Matching Candidates

[0303] The server generates multiple activity candidates suitable for the user based on the analysis results of the AI ​​and emotion engine. This process lists activities that match the user's current emotional state. Possible activities include "gardening club," "cooking class," and "travel circle," reflecting the user's interests and emotional state.

[0304] 5. Present candidates to the user

[0305] The activity suggestions generated by the server are sent to the terminal and presented to the user on the terminal, where detailed information about the activity, the reason for the recommendation based on the user's emotional state, and the profiles of the potential participants are displayed.

[0306] 6. User Selection and Participation Application

[0307] The user selects an activity they are interested in and submits an application to participate. For example, if the user wishes to join the "gardening club" based on the reasons recommended by the emotion engine, they press the application button to express their intention to participate.

[0308] 7. Application Processing and Notification

[0309] The server processes the user's request to join and sends a notification to the relevant community organizer, who receives the notification and confirms the new member.

[0310] 8. Providing more information

[0311] The terminal notifies the user of the participation acceptance and activity details, including the participation acceptance message, the event schedule, and the meeting place information.

[0312] 9. User Participation

[0313] Users can then take part in real activities based on the information they receive, for example attending the first meeting of a "gardening club" and finding meaning in life through new experiences.

[0314] Examples of specific examples and prompts

[0315] Examples:

[0316] User A selects "gardening," "cooking," and "travel" as hobbies and registers "photography" as a skill on a dedicated device. Based on the emotional state recognized as "relaxed," he / she wishes to join the gardening club.

[0317] Example prompt sentence:

[0318] "If a user has hobbies like gardening, cooking, and traveling, and a skill like photography, and is currently relaxing, please suggest which communities and activities would be suitable. Then, please show the process flow for choosing the best activity and completing the user's participation process."

[0319] The above system allows users to easily find activities and communities that are best suited to them and discover new meaning in life.

[0320] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0321] Step 1:

[0322] The user accesses a dedicated device or web service and enters profile data such as their hobbies, interests, skills, and region into a form. The emotion recognition system then uses a camera and microphone to analyze their current emotions. Specifically, the user selects "gardening" or "cooking" as their hobbies, and the emotion recognition system recognizes the emotion as "relaxation." Inputs include the user's hobbies, interests, skills, and emotional data. This data is then sent to the server via an API.

[0323] Step 2:

[0324] The server receives profile data and emotion data and stores it in a temporary database. The input data includes the hobbies, interests, skills, and emotion data entered by the user. The output is the data stored in the temporary database. The specific operation is to store the received data in the corresponding database table.

[0325] Step 3:

[0326] The AI ​​algorithm in the server analyzes the stored data. The input data includes the user's profile data and emotional data stored on the server. The AI ​​algorithm combines hobbies, interests, skills, and emotional state to search the database for the most suitable activities and communities. The output is a list of suitable activity candidates as a result of the analysis. Specifically, the AI ​​model inputs the data and calculates a matching score.

[0327] Step 4:

[0328] The server generates multiple candidate activities suitable for the user based on the analysis results of the AI ​​and emotion engine. The input data includes the analysis results of the AI ​​algorithm. The output is a list of the candidate activities generated. Specifically, it lists and selects activities that match the user's current emotional state.

[0329] Step 5:

[0330] The server sends the generated activity candidates to the terminal. The input data includes a list of the generated activity candidates. The output is notification information sent to the terminal. Specifically, the system sends the activity candidates to the user terminal in real time via the user interface.

[0331] Step 6:

[0332] The terminal presents the transmitted activity candidates to the user. The input data includes the list of activity candidates transmitted from the server. The output is the candidate list displayed on the user's screen. Specifically, the screen display logic is used to visually present the user with detailed information about the activity, the reason for the recommendation based on the user's emotional state, and profile information about the potential participants.

[0333] Step 7:

[0334] The user selects an activity they are interested in and submits an application to participate. The input data includes the activity the user selected and the reason for their selection. The output is a form in which the application information is sent to the server. The specific operation is to press the participation application button and the information is sent to the server.

[0335] Step 8:

[0336] The server processes user participation requests. Input data includes participation request information from users. Output includes the status of the processed request. Specific operations include receiving the request information, updating it in the database, and managing the status.

[0337] Step 9:

[0338] The server sends a notification to the organizer of the relevant community. The input data includes the user's participation application information. The output is a notification message to the organizer. Specifically, the server obtains the organizer's contact information and sends the notification message.

[0339] Step 10:

[0340] The terminal notifies the user of participation approval and activity details. Input data includes the approval information and details sent from the server. The output is a notification message displayed on the user's screen. Specific operations include displaying the participation approval message, event schedule, and meeting place information to the user.

[0341] Step 11:

[0342] The user participates in the actual activity based on the notified information. The input data includes the notified activity details. The output is a record of the user's actual activity participation. The specific operation is for the user to go to the notified meeting place and participate in the activity.

[0343] (Application example 2)

[0344] 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."

[0345] In order for elderly people to find new meaning in life after retirement, they need to find appropriate activities and communities that take into account not only their hobbies and interests but also their current emotional state. However, existing matching systems do not take these emotional factors into account, making it difficult for users to find activities and communities that truly satisfy them.

[0346] 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 means for receiving profile data and emotion data input by the user, means for generating a plurality of activity candidates suitable for the user based on the profile data and emotion data, and means for presenting the generated activity candidates to the user. This makes it possible to suggest appropriate activities and communities that take into account not only the user's hobbies and interests but also their emotional state.

[0347] "Profile data" refers to basic information such as hobbies, interests, skills, and location that users enter themselves.

[0348] "Emotion data" refers to information that represents the user's current emotional state and is detected by an emotion recognition system.

[0349] "Activity candidates" refers to a list of multiple candidate activities and communities suitable for a user, generated based on the user's profile data and emotion data.

[0350] "Means for generating" refers to methods or techniques for analyzing user input data and listing appropriate activity candidates based on that data.

[0351] The "presentation means" refers to a method or technique for visually or audibly displaying the generated activity candidates to the user.

[0352] "Participation application" refers to the application procedure a user goes through to participate in an activity or community that interests them.

[0353] "Means for sending notifications" refers to the methods and techniques for sending notifications to relevant groups or parties based on a user's participation request.

[0354] "Means for providing detailed information" refers to methods and techniques for providing detailed information about activities and events to users.

[0355] This invention provides a system for helping retired people find new meaning in life, including an application installed on a smartphone or head-mounted display (HMD).

[0356] System configuration

[0357] 1. Entering user profile and emotion data

[0358] Users access the application using their smartphone or HMD and enter their profile data, which includes information such as hobbies, interests, skills, and location.

[0359] Furthermore, users input their current emotional state through images or videos, and emotion data is automatically detected using an emotion recognition system (e.g., emotion_engine library).

[0360] 2. Receipt and storage of data

[0361] The server receives the profile data and emotion data entered by the user and stores them in a database.

[0362] 3. Data analysis and activity candidate generation

[0363] The server's AI matching algorithm (e.g., the ai_matcher library) analyzes the received profile and emotional data to generate optimal activity and community suggestions, taking into account the user's hobbies and skills as well as their current emotional state.

[0364] 4. Suggested activities

[0365] The generated activity candidates are presented to the user on their smartphone or HMD, and the user selects the activity that interests them.

[0366] 5. Application and Notification

[0367] Based on the activity selected by the user, a participation request is sent to the server and notifications are sent to relevant communities and stakeholders.

[0368] The notification includes the user's profile information and details of the selected activity, allowing community organizers to receive new participant information.

[0369] 6. Providing more information

[0370] Users will be provided with activity details based on the notification, including details such as the date, time, and location of the activity, as well as any precautions.

[0371] Specific processing examples

[0372] For example, if a user lists gardening as a hobby and the emotion engine detects that they find it relaxing, the system will suggest gardening-related activities and communities, such as nearby gardening clubs or online workshops.

[0373] Prompt Sentence Examples

[0374] If a user has a particular hobby (gardening) and is detected as relaxed by an emotion recognition system, suggest an appropriate virtual activity. Include details about the activity you are suggesting and the reason for suggesting it.

[0375] In this way, it becomes possible to help users find appropriate activities and communities based on their profile data and emotional data, allowing them to find new meaning in life and live a fulfilling life.

[0376] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0377] Step 1:

[0378] Users access the application using a smartphone or head-mounted display (HMD) and enter their profile data. The profile data includes information such as hobbies, interests, skills, and location. The entered data is sent to the system's database and stored. The input of this step is the user's profile data, and the output is the profile data stored in the database.

[0379] Step 2:

[0380] The user inputs emotional data using a camera. The emotional data is captured in real time from images or videos and analyzed by an emotion recognition system (e.g., emotion_engine). As a result of the analysis, the user's current emotional state is detected and sent to the system and stored in a database. The input of this step is the user's image or video, and the output is the analyzed emotional data.

[0381] Step 3:

[0382] The server receives the profile data and emotion data stored in the database and analyzes them using an AI matching algorithm (e.g., ai_matcher). This analysis includes the user's hobbies, skills, and current emotional state. Based on this, activity candidates suitable for the user are generated. The input of this step is the profile data and emotion data, and the output is the generated activity candidates.

[0383] Step 4:

[0384] The server sends the generated activity candidates to the user's smartphone or HMD for presentation. The user checks the detailed information of the activity candidates displayed on the screen and selects the activity of interest. The input of this step is the generated activity candidates, and the output is the user's selected activity.

[0385] Step 5:

[0386] Based on the user's selected activity, a request to join is made. The request is sent to the server, which processes it and sends a notification to relevant communities and stakeholders. The notification contains the user's profile information and details of the selected activity. The input of this step is the user's request to join, and the output is the notification sent.

[0387] Step 6:

[0388] The server provides the user with detailed information about the activity based on the notification. This information includes the date, time, location, and important notes of the activity. Based on the information notified, the user participates in the actual activity or event. The input of this step is the detailed information based on the notification, and the output is the detailed information of the activity provided to the user.

[0389] Through these steps, users can find the most suitable activities and communities based on their emotional state and profile data, and discover new meanings in life, which is expected to improve the quality of their lives.

[0390] 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.

[0391] 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.

[0392] 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.

[0393] [Second embodiment]

[0394] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0395] 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.

[0396] 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).

[0397] 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.

[0398] 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.

[0399] 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).

[0400] 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.

[0401] 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.

[0402] 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.

[0403] 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.

[0404] 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.

[0405] 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."

[0406] This invention relates to a system that matches appropriate communities and activities to users who are looking for new meaning in life after retirement. Specifically, it involves a series of processes that exchange data between a server, terminals, and users, and uses AI to suggest optimal activities and communities.

[0407] System configuration

[0408] 1. User fills out profile

[0409] A user accesses a dedicated terminal or web service and enters information about their hobbies, interests, skills, region, etc. As a specific example, consider the case where a user selects gardening, cooking, and travel as hobbies and enters camera photography as a skill.

[0410] 2. The server receives the data

[0411] The server receives the profile data entered by the user and stores it in a temporary database, and it is important that the data is received accurately during this process.

[0412] 3. Data Analysis

[0413] An AI algorithm on the server analyzes the received profile data, for example, searching for active gardening clubs and related events based on the hobby "gardening."

[0414] 4. Generating Matching Candidates

[0415] Based on the analysis results, the server will then list multiple activity options suitable for the user, such as gardening clubs, cooking classes, and travel groups.

[0416] 5. Present candidates to the user

[0417] The device presents the matching candidates sent from the server to the user, and the user's screen displays detailed information about the activity and the profiles of the potential participants.

[0418] 6. User Selection and Participation Application

[0419] The user selects an activity that interests them and submits an application to participate, for example, if the user wishes to join a gardening club, they submit an application to that club.

[0420] 7. Application Processing and Notification

[0421] The server processes the user's request to join and sends a notification to the organizer of the corresponding community, who then receives the new joiner's information.

[0422] 8. Providing more information

[0423] The device will notify the user of participation approval and detailed information, including the event schedule, activities, and meeting place.

[0424] 9. User Participation

[0425] The user then participates in an actual activity based on the information provided, for example, attending the first meeting of a gardening club.

[0426] Through the above process, users can easily find new meaning in life and live a fulfilling life. This system is characterized by the efficient exchange of data between the server, device, and user, and by using AI to perform optimal matching.

[0427] The processing flow will be explained below.

[0428] Step 1:

[0429] Users enter their profile data, such as hobbies, interests, skills, and location, into a form on a dedicated device or web service, and press the "Submit" button. This information is needed for subsequent analysis and matching.

[0430] Step 2:

[0431] The server receives the profile data sent by the user, parses the data sent in the HTTP request, converts it into the required format, and stores it in a temporary database.

[0432] Step 3:

[0433] The AI ​​algorithm on the server analyzes the received profile data. At this stage, it searches the database for activities and communities that match the user's hobbies, interests, and skills. For example, if a user enters "gardening" as a hobby, it will extract community data related to gardening.

[0434] Step 4:

[0435] The server generates multiple activity suggestions suitable for the user based on the analysis results of the AI ​​algorithm. Here, a list of suggested activities is created based on the user's interests and skills. Examples may include gardening clubs, cooking classes, travel circles, etc.

[0436] Step 5:

[0437] The server transmits the generated activity candidate data to the terminal, where the data is converted into a format suitable for display on the user's display screen.

[0438] Step 6:

[0439] The device displays the matching candidates sent from the server to the user, and the user can check the details of the activity, the profiles of the potential participants, the date and time, and the location of the event.

[0440] Step 7:

[0441] The user selects the activity they are interested in and applies to participate. When the user presses the "Apply to participate" button, the information is sent to the server.

[0442] Step 8:

[0443] The server receives and processes the user's participation application data, checks which community the user has applied to join, and sends a notification to the organizer of the corresponding community.

[0444] Step 9:

[0445] The server sends a notification to the organizer and prepares to provide the user with participation acceptance and activity details, including the participation acceptance message, event details, and meeting place information.

[0446] Step 10:

[0447] The terminal notifies the user of the participation approval and detailed information sent from the server, and the user confirms the date, location, and belongings of the activity to be participated in based on this information.

[0448] Step 11:

[0449] The user can then participate in actual activities based on the information provided. For example, by participating in the first meeting of a gardening club, the user has the opportunity to find a new purpose in life.

[0450] Following these detailed steps will help users find new activities and communities that suit them, helping them find meaning in their post-retirement lives.

[0451] Example 1

[0452] 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."

[0453] Users looking for new meaning in life after retirement need to be able to easily find the right community or activity. However, conventional systems often fail to find activities or communities that best suit a user's individual interests and skills. Another issue with these systems is that they require users to manually search through multiple options and select the one that best suits them.

[0454] 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.

[0455] In this invention, the server includes means for receiving profile data input by a user, means for analyzing the profile data, and means for generating a plurality of activity candidates suitable for the user based on the analysis results, thereby enabling the user to easily find activities and communities that best suit their interests and skills.

[0456] "User" refers to an individual who uses the system to enter profile data and find activities and communities that best suit them.

[0457] "Profile Data" refers to information entered by a user, such as hobbies, interests, skills, and location.

[0458] "Means for analyzing" refers to a function that performs calculations to find the activities and communities that are most suitable for the user based on the input profile data.

[0459] "Suggested Activities" refers to activities or communities that may be suggested to a user based on analyzed profile data.

[0460] "Means for generating" refers to the function of listing multiple candidate activities based on the analysis results and making them ready to present to the user.

[0461] The "means for presenting" refers to a function for displaying the generated activity candidates on the screen in a manner that is visible to the user.

[0462] "Means for processing participation applications" refers to the function of accepting a user's intention to participate in an activity selected by the user and processing it within the system.

[0463] "Means for sending notifications" refers to the functionality for sending notifications to relevant communities and stakeholders based on processed participation applications.

[0464] The "means for providing detailed information" refers to a function for notifying the user of specific information regarding activities after participation is approved.

[0465] This invention relates to a system that matches appropriate communities and activities to users who are looking for new meaning in life after retirement. Data is exchanged between a server, a terminal, and the user, and optimal activities and communities are suggested using AI. Specific embodiments of this system are described below.

[0466] System Configuration

[0467] The system mainly consists of the following components:

[0468] 1. Means of receiving your profile data

[0469] 2. Means of analyzing profile data

[0470] 3. A method for generating candidate activities based on the analysis results

[0471] 4. Means of presenting suggested activities to users

[0472] 5. Means of handling user activity selection and participation requests

[0473] 6. Means of sending notifications based on participation requests

[0474] 7. Means of providing users with more information about their activities

[0475] Hardware and Software

[0476] server:

[0477] Hardware: General server equipment (e.g., dual-core or quad-core CPU, 16GB RAM, SSD storage)

[0478] Software: Web frameworks such as Django or Flask, machine learning libraries such as Scikit-learn or TensorFlow, and database systems such as MySQL or PostgreSQL.

[0479] Device:

[0480] Hardware: Personal computers, tablets, smartphones

[0481] Software: Web browser, JavaScript framework (e.g. React)

[0482] Processing flow

[0483] The server receives profile data entered by the user. The user accesses a dedicated terminal or web service and enters information such as hobbies, interests, skills, and location. For example, consider a user entering, "I'm interested in gardening, cooking, and traveling. I'm good at photography."

[0484] The server stores the received profile data in a temporary database. This process requires validation to ensure the accuracy of the data. Implement data validation functionality using a web framework such as Django or Flask.

[0485] Next, AI algorithms in the server analyze the received profile data. For example, based on the hobby "gardening," they search for currently active gardening clubs and related events. This analysis is performed using Python-based machine learning libraries such as Scikit-learn and TensorFlow.

[0486] Based on the analysis results, the server generates multiple activity candidates suitable for the user. These candidates are stored in a database system such as MySQL or PostgreSQL. The generated activity candidates are updated in real time to include the latest activity and event information.

[0487] The user's device presents these activity suggestions sent from the server. Detailed information about the listed activities and profiles of potential participants are displayed on the user's screen. This display is done using the JavaScript framework React.

[0488] Users select an activity they are interested in and submit a participation request. For example, a user may request, "I would like to join the gardening club." This request data is again sent to the server via a RESTful API, and the server processes the user's participation request. This process includes temporarily storing the data required for participation and sending notifications to related communities and stakeholders. Notifications are sent using SendGrid or Firebase Cloud Messaging.

[0489] Finally, the server notifies the user of the approval and detailed information, such as "The first meeting of the gardening club will be held next Saturday at 2:00 PM in the flowerbeds of the park." Based on this information, the user can then participate in the actual activity.

[0490] Specific examples

[0491] Prompt Sentence Examples

[0492] "I'd like to find a new hobby after retirement. I'm interested in gardening, cooking, and traveling. I'm good at photography. Please introduce me to some suitable activities and communities."

[0493] As a result, this system helps users easily find new meaning in life and continue to live a fulfilling life.

[0494] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0495] Step 1:

[0496] The user enters their profile. They access a dedicated device or a web service and enter information such as hobbies, interests, skills, and location. The entered data (e.g., hobbies are gardening, cooking, and travel, and skills are photography) is sent via an HTML form.

[0497] Input: User's hobbies, interests, skills, and location

[0498] Output: Profile data

[0499] Step 2:

[0500] The server receives the data. The server receives the profile data submitted by the user via a RESTful API, stores the data in a temporary database (e.g., SQLite or PostgreSQL), and performs validation to ensure the data is correct.

[0501] Input: Profile data

[0502] Output: Validated data

[0503] Step 3:

[0504] The server analyzes the data. The validated data is then input into a machine learning model to analyze the user's interests and skills. Specifically, it uses Scikit-learn and TensorFlow to generate a list of candidate activities.

[0505] Input: Validated data

[0506] Output: Analysis results (list of activity candidates)

[0507] Step 4:

[0508] The server generates matching candidates. Based on the analysis results, it selects multiple activity candidates suitable for the user and stores them in a database such as MySQL or PostgreSQL. This list includes detailed information about the activities and their profiles.

[0509] Input: Analysis results (list of activity candidates)

[0510] Output: Generated activity candidates

[0511] Step 5:

[0512] The device presents candidates to the user. The activity candidates sent from the server are displayed on the user's screen. The JavaScript framework React is used to display detailed information about the listed activities and profiles of the participants.

[0513] Input: Generated activity candidates

[0514] Output: The screen displayed to the user

[0515] Step 6:

[0516] The user selects an activity they are interested in and submits a participation request. The user selects an activity they are interested in on the system and submits a participation request for the activity. This application data is again sent to the server via the RESTful API.

[0517] Input: User activity selection, participation application

[0518] Output: Participation application data

[0519] Step 7:

[0520] The server processes the participation requests. The server processes the received participation request data and sends notifications to relevant communities and stakeholders. This notification is done using SendGrid or Firebase Cloud Messaging.

[0521] Input: Participation application data

[0522] Output: Send notification

[0523] Step 8:

[0524] The terminal provides detailed information to the user. Based on the content of the notification sent by the server, the user is notified of specific activity information (such as the event schedule and meeting place).

[0525] Input: Notification content

[0526] Output: Provides detailed information

[0527] Step 9:

[0528] The user participates in an activity. The user participates in an actual activity based on the notified activity information. For example, the user heads to a designated flower bed in a park to participate in the first meeting of the gardening club.

[0529] Input:Detailed information

[0530] Output: User activity participation

[0531] (Application example 1)

[0532] 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."

[0533] In modern society, finding a new purpose in life after retirement is important for many people. However, finding suitable communities and activities can be difficult. In particular, physical constraints and a lack of information make it difficult to confirm the content of activities before actually participating. Furthermore, conventional methods have limited ability to suggest optimal activities based on the user's hobbies and skills.

[0534] 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.

[0535] In this invention, the server includes: means for receiving profile data entered by a user; means for generating multiple activity candidates suitable for the user based on the profile data; means for presenting the generated activity candidates to the user; means for processing a request to participate in an activity selected by the user based on the selected activity; means for sending a notification to a related community or related party based on the processed participation request; means for providing the user with detailed information about the activity based on the notification; means for suggesting activity candidates based on the user profile using a generative AI model; and means for the user to virtually experience the suggested activities using a virtual reality device. This allows the user to virtually experience the target activities, making it easier to select an appropriate activity. This makes the process of finding a new purpose in life more efficient and effective.

[0536] Definitions of important words

[0537] "Profile Data" is data entered by a user that includes personal information such as hobbies, interests, skills, and location.

[0538] "Suggested Activities" refers to suitable communities and events based on the user's profile data.

[0539] "Generative AI Model" means an artificial intelligence model used to suggest optimal activities based on a user profile.

[0540] A "virtual reality device" is hardware that enables a user to virtually experience activities in a virtual reality environment, and examples include VR headsets.

[0541] "Visiting" is the process of using virtual reality devices to simulate an activity before participating in it.

[0542] A "notification" is a message sent to a related community or person concerned about the processing result or detailed information of an application to participate in an activity.

[0543] MODE FOR CARRYING OUT THE INVENTION

[0544] The embodiment of the present invention includes the following procedures and hardware / software configurations.

[0545] Hardware and Software Configuration

[0546] Hardware:

[0547] Smartphone

[0548] Head-mounted displays (e.g., Oculus Rift, HTC Vive)

[0549] server

[0550] Database

[0551] software:

[0552] Python

[0553] SQLite3

[0554] OpenAI API

[0555] A web interface (for users to enter their profile data)

[0556] Virtual reality applications (for users to have a virtual experience)

[0557] Process Details

[0558] User fills out profile

[0559] Users access a dedicated terminal or web interface and enter information about their hobbies, interests, skills, location, etc. This information is collected as "profile data" and sent to a server.

[0560] Data reception and storage

[0561] The server receives the profile data entered by the user and stores it in a temporary database (e.g., SQLite3). Input validation and filtering are performed automatically to ensure data accuracy.

[0562] Data analysis

[0563] An AI algorithm on the server analyzes the profile data and lists multiple activity candidates suitable for the user. The analysis is performed using the OpenAI API, and the generative AI model suggests appropriate communities and activities based on the user's hobbies and skills.

[0564] Presentation of match candidates

[0565] The user's terminal or VR device displays the activity candidates sent from the server. The user can view the activity details and select the activity that interests them.

[0566] Trial experience of the activity

[0567] When using a head-mounted display, users can virtually experience the proposed activity, allowing them to check the atmosphere and content of the activity before actually participating.

[0568] Specific examples

[0569] If a user inputs hobbies such as "gardening," "cooking," and "traveling" and "photography skills," the system sends the following prompts to the generative AI model:

[0570] plaintext

[0571] Hobbies: Gardening, Cooking, Traveling, Skills: Photography, Region: Tokyo, please suggest suitable communities and activities.

[0572] The generated activity candidates may look like this:

[0573] 1. Gardening Club

[0574] 2. Cooking Classes

[0575] 3. Travel Circle

[0576] Users can try out these options using a VR device and select the activity that best suits them. For example, experiencing the atmosphere and activities of a gardening club in VR can solidify their desire to participate. Furthermore, users will automatically be notified of the details of their chosen activity and be notified of the necessary participation details.

[0577] This invention allows users to discover more relevant and attractive communities and activities through virtual experiences. Furthermore, by utilizing a generative AI model, it is possible to make recommendations that are optimized for each individual user. This system aims to improve the user experience, which was difficult to achieve with conventional methods.

[0578] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0579] Program processing flow

[0580] Step 1:

[0581] The user accesses a dedicated terminal or web interface and enters their profile data, such as hobbies, interests, skills, and region. The entered data is sent to a temporary database. Input: Hobbies, interests, skills, region Output: User profile data

[0582] Step 2:

[0583] The server receives the profile data entered by the user. The received data undergoes syntax checking and input filtering and is then saved in a temporary database (e.g., SQLite3). Input: User profile data Output: Profile data saved in the database

[0584] Step 3:

[0585] The AI ​​algorithm on the server analyzes the received profile data. At this time, a generative AI model is used to list multiple activity candidates suitable for the user. A prompt statement is sent to the generative AI model to obtain recommended activity candidates. Input: Saved profile data, prompt statement (example: "Based on hobbies: gardening, cooking, travel, skills: photography, and area: Tokyo, please suggest appropriate communities and activities.") Output: Generated list of activity candidates

[0586] Step 4:

[0587] The server sends the generated activity candidate list to the terminal, which then displays it to the user. The user then views detailed information about these activity candidates through a screen or VR device. Input: Activity candidate list Output: Activity candidate details displayed on the user's terminal

[0588] Step 5:

[0589] The user selects an activity that interests them and applies to participate in that activity. The application is sent to the server via the terminal. Input: Activity selected by the user Output: Application to participate

[0590] Step 6:

[0591] The server processes the request and sends notifications to the relevant communities and stakeholders. These notifications include the request and the user's profile data. Input: Request to join. Output: Notifications sent to the relevant communities.

[0592] Step 7:

[0593] The server receives participation approval and detailed information from related communities and stakeholders, and sends it to the user's terminal. The detailed information includes the event schedule, activities, meeting place, etc. Input: Approval and detailed information from related communities Output: Detailed information sent to the user's terminal

[0594] Step 8:

[0595] The user uses a head-mounted display to virtually experience the proposed activity. The virtual experience simulates the atmosphere and content of the actual activity in a VR environment. Input: Detailed information about the proposed activity. Output: VR experience of the virtual activity that the user has virtually experienced.

[0596] Step 9:

[0597] The user finally decides which activities they want to participate in, and the server sends a final notification to the relevant community. Input: User's selection after virtual experience Output: Final notification

[0598] 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.

[0599] This invention relates to a system that matches appropriate communities and activities to users who are looking for new meaning in life after retirement. In particular, by incorporating an emotion engine, this system enables matching that takes into account the user's emotional state. Specifically, it involves a series of processes that exchange data between a server, terminal, and user, and uses AI and the emotion engine to suggest optimal activities and communities.

[0600] System configuration

[0601] 1. The user enters their profile data and emotional data.

[0602] A user accesses a dedicated device or web service and enters profile data such as their hobbies, interests, skills, and location. Furthermore, the emotion recognition system inputs or detects their current emotional state. As a concrete example, consider the case where a user selects gardening, cooking, and travel as hobbies and registers camera photography as a skill, and the emotion engine recognizes the emotion as "relaxed."

[0603] 2. The server receives the data

[0604] The server receives the profile data and emotion data entered by the user and stores them in a temporary database. For example, a user who is relaxed may be suited to a gardening club, which has a stress-reducing effect.

[0605] 3. Data Analysis

[0606] The AI ​​algorithm in the server analyzes the received profile and emotional data. At this stage, it searches the database for activities and communities that take into account the user's current emotional state, along with their hobbies, interests, and skills. For example, a user who is "relaxing" will be presented with activities that have a relaxing effect.

[0607] 4. Generating Matching Candidates

[0608] The server generates multiple activity candidates suitable for the user based on the analysis results of the AI ​​and emotion engine. This process lists activities that match the user's current emotional state. For example, it may include gardening clubs, cooking classes, travel circles, etc. that reflect the user's interests and emotional state.

[0609] 5. Present candidates to the user

[0610] The device presents the matching candidates sent from the server to the user, who is then shown detailed information about the activity, the reason for the recommendation based on the user's emotional state, and the profile of the potential participants.

[0611] 6. User Selection and Participation Application

[0612] The user selects an activity that they are interested in and submits an application to participate in. For example, if the user wants to join a gardening club based on the reasons recommended by the emotion engine, they submit an application to join the club.

[0613] 7. Application Processing and Notification

[0614] The server processes the user's request to join and sends a notification to the organizer of the corresponding community, who then receives the new joiner's information.

[0615] 8. Providing more information

[0616] The terminal notifies the user of participation approval and activity details, including a participation approval message, event details, and meeting place information.

[0617] 9. User Participation

[0618] The user can then participate in actual activities based on the information provided. For example, by participating in the first meeting of a gardening club, the user has the opportunity to find a new purpose in life.

[0619] Through this process, users can easily find new activities and communities that suit them, enabling them to live fulfilling lives. This system is characterized by the efficient exchange of data between the server, device, and user, and by using AI and an emotion engine to perform optimal matching.

[0620] The processing flow will be explained below.

[0621] Step 1:

[0622] The user enters their profile data and emotional data. They fill out information such as hobbies, interests, skills, and location on a dedicated device or a form on a web service, and then press the "Submit" button. The emotion recognition system also detects the user's current emotional state, and this data is also sent. For example, if a user selects "gardening," "cooking," and "travel" as their hobbies and inputs camera photography as a skill, their emotional state is recognized as "relaxed."

[0623] Step 2:

[0624] The server receives the profile data and emotion data sent by the user, converts this data into an analyzable format, and stores it in a temporary database.

[0625] Step 3:

[0626] An AI algorithm in the server analyzes the received profile and emotional data. For example, based on the hobby of "gardening" and the emotional state of "relaxation," it searches a database for relaxing activities related to gardening.

[0627] Step 4:

[0628] The server generates multiple activity suggestions suitable for the user based on the analysis results of the AI ​​algorithm and emotion engine, such as a list of relaxing activities such as gardening clubs, cooking classes, and art therapy.

[0629] Step 5:

[0630] The server transmits the generated activity candidate data to the terminal, where the data is converted to a format suitable for display on the user's display screen.

[0631] Step 6:

[0632] The device displays the matching candidates sent from the server to the user. The user's screen displays detailed information about each activity, the reason for the recommendation (for example, because it is expected to have a relaxing effect), and the profiles of the potential participants.

[0633] Step 7:

[0634] The user selects an activity they are interested in and applies to join. For example, the user clicks the "Apply" button to join the gardening club. This information is sent to the server.

[0635] Step 8:

[0636] The server receives and processes the user's participation application data, checks which community the user has applied to join, and sends a notification to the organizer of the corresponding community.

[0637] Step 9:

[0638] The server sends a notification to the organizer and prepares to provide the user with participation acceptance and activity details, including the participation acceptance message, event details, and meeting place information.

[0639] Step 10:

[0640] The terminal notifies the user of the participation approval and detailed information sent from the server, and the user confirms the activity date, location, belongings, etc. based on this information.

[0641] Step 11:

[0642] The user can then participate in actual activities based on the information provided, for example, attending the first meeting of a gardening club, and gaining the opportunity to find a new purpose in life.

[0643] By following these detailed steps, users can easily find new activities and communities that suit them, and find meaning in their post-retirement lives. By combining it with an emotion engine, matching can be performed taking into account the user's emotional state, resulting in more appropriate activities being selected.

[0644] Example 2

[0645] 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."

[0646] In recent years, an increasing number of elderly people are seeking new meaning in life after retirement. However, it is not easy to find communities and activities that suit their individual interests, skills, and mental state. Conventional systems have difficulty proposing activities that take into account the user's emotional state, and as a result, they often present activities that are not in line with the user's interests. There is a need to solve this problem and propose activities that are optimal for users.

[0647] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving profile data and emotion data input by the user, means for generating a plurality of activity candidates suitable for the user based on the profile data and emotion data, and means for presenting the generated activity candidates to the user. This makes it possible to suggest activities that take into account the user's individual interests, skills, and mental state.

[0648] "Profile Data" refers to personal information about a user, such as their hobbies, interests, skills, and location.

[0649] "Emotion data" refers to information indicative of a user's current emotional state that is collected by an emotion recognition system.

[0650] "Means for receiving" refers to the function or method by which the server receives input data from the user.

[0651] "Means of analysis" refers to the functions and methods by which algorithms and programs within the server analyze the received data and extract useful information from it.

[0652] "Means for generating" refers to a function or method for generating multiple activity candidates suitable for the user based on the analysis results.

[0653] The "means for presenting" refers to a function or method for displaying the generated activity candidates to the user and allowing the user to select one.

[0654] "Means for processing participation requests" refers to the functions and methods for accepting, managing, and processing participation requests for the activities selected by the user.

[0655] "Means for sending notifications" refers to the functions and methods for informing relevant communities or stakeholders based on processed participation applications.

[0656] "Means for providing detailed information" refers to a function or method for informing the user of specific information about the activity (e.g., event dates and meeting places) based on the notification.

[0657] "Suggested Activities" refers to a list of activities and communities that a user can participate in that are suggested based on the user's profile data and emotional data.

[0658] "Database" refers to a system for systematically storing and managing information such as profile data, emotional data, analysis results, and potential activities.

[0659] "AI Algorithm" refers to the artificial intelligence technology used to analyze user data and generate optimal activity suggestions.

[0660] An "emotion recognition system" refers to technology that uses sensors such as cameras and microphones to recognize a user's current emotional state.

[0661] This invention relates to a system that matches appropriate communities and activities to users who are looking for a new purpose in life after retirement. By combining this system with an emotion engine, it enables matching that takes into account the user's emotional state, and it exchanges data between the server, terminal, and user, and uses AI and the emotion engine to suggest optimal activities and communities.

[0662] System configuration

[0663] 1. The user enters their profile data and emotional data.

[0664] Users access a dedicated device or web service and enter profile data such as hobbies, interests, skills, and region. An emotion recognition system using a camera and microphone also inputs or detects the user's current emotional state. For example, a scenario is envisioned in which a user selects "gardening," "cooking," and "travel" as hobbies and registers "photography" as a skill, and the emotion recognition system recognizes the emotion as "relaxed."

[0665] 2. The server receives the data

[0666] The server receives profile and emotion data from users via API and stores it in a temporary database. For example, a user who is relaxing might be suited to a "gardening club" that has a stress-reducing effect.

[0667] 3. Data Analysis

[0668] The AI ​​algorithms on the server analyze the received profile data and emotional data. This analysis involves taking into account the user's hobbies, interests, skills, and emotional state, and searching the database for the most suitable activities and communities. For example, if a user is "relaxing," activities that have a relaxing effect will be presented.

[0669] 4. Generating Matching Candidates

[0670] The server generates multiple activity candidates suitable for the user based on the analysis results of the AI ​​and emotion engine. This process lists activities that match the user's current emotional state. Possible activities include "gardening club," "cooking class," and "travel circle," reflecting the user's interests and emotional state.

[0671] 5. Present candidates to the user

[0672] The activity suggestions generated by the server are sent to the terminal and presented to the user on the terminal, where detailed information about the activity, the reason for the recommendation based on the user's emotional state, and the profiles of the potential participants are displayed.

[0673] 6. User Selection and Participation Application

[0674] The user selects an activity they are interested in and submits an application to participate. For example, if the user wishes to join the "gardening club" based on the reasons recommended by the emotion engine, they press the application button to express their intention to participate.

[0675] 7. Application Processing and Notification

[0676] The server processes the user's request to join and sends a notification to the relevant community organizer, who receives the notification and confirms the new member.

[0677] 8. Providing more information

[0678] The terminal notifies the user of the participation acceptance and activity details, including the participation acceptance message, the event schedule, and the meeting place information.

[0679] 9. User Participation

[0680] Users can then take part in real activities based on the information they receive, for example attending the first meeting of a "gardening club" and finding meaning in life through new experiences.

[0681] Examples of specific examples and prompts

[0682] Examples:

[0683] User A selects "gardening," "cooking," and "travel" as hobbies and registers "photography" as a skill on a dedicated device. Based on the emotional state recognized as "relaxed," he / she wishes to join the gardening club.

[0684] Example prompt sentence:

[0685] "If a user has hobbies like gardening, cooking, and traveling, and a skill like photography, and is currently relaxing, please suggest which communities and activities would be suitable. Then, please show the process flow for choosing the best activity and completing the user's participation process."

[0686] The above system allows users to easily find activities and communities that are best suited to them and discover new meaning in life.

[0687] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0688] Step 1:

[0689] The user accesses a dedicated device or web service and enters profile data such as their hobbies, interests, skills, and region into a form. The emotion recognition system then uses a camera and microphone to analyze their current emotions. Specifically, the user selects "gardening" or "cooking" as their hobbies, and the emotion recognition system recognizes the emotion as "relaxation." Inputs include the user's hobbies, interests, skills, and emotional data. This data is then sent to the server via an API.

[0690] Step 2:

[0691] The server receives profile data and emotion data and stores it in a temporary database. The input data includes the hobbies, interests, skills, and emotion data entered by the user. The output is the data stored in the temporary database. The specific operation is to store the received data in the corresponding database table.

[0692] Step 3:

[0693] The AI ​​algorithm in the server analyzes the stored data. The input data includes the user's profile data and emotional data stored on the server. The AI ​​algorithm combines hobbies, interests, skills, and emotional state to search the database for the most suitable activities and communities. The output is a list of suitable activity candidates as a result of the analysis. Specifically, the AI ​​model inputs the data and calculates a matching score.

[0694] Step 4:

[0695] The server generates multiple candidate activities suitable for the user based on the analysis results of the AI ​​and emotion engine. The input data includes the analysis results of the AI ​​algorithm. The output is a list of the candidate activities generated. Specifically, it lists and selects activities that match the user's current emotional state.

[0696] Step 5:

[0697] The server sends the generated activity candidates to the terminal. The input data includes a list of the generated activity candidates. The output is notification information sent to the terminal. Specifically, the system sends the activity candidates to the user terminal in real time via the user interface.

[0698] Step 6:

[0699] The terminal presents the transmitted activity candidates to the user. The input data includes the list of activity candidates transmitted from the server. The output is the candidate list displayed on the user's screen. Specifically, the screen display logic is used to visually present the user with detailed information about the activity, the reason for the recommendation based on the user's emotional state, and profile information about the potential participants.

[0700] Step 7:

[0701] The user selects an activity they are interested in and submits an application to participate. The input data includes the activity the user selected and the reason for their selection. The output is a form in which the application information is sent to the server. The specific operation is to press the participation application button and the information is sent to the server.

[0702] Step 8:

[0703] The server processes user participation requests. Input data includes participation request information from users. Output includes the status of the processed request. Specific operations include receiving the request information, updating it in the database, and managing the status.

[0704] Step 9:

[0705] The server sends a notification to the organizer of the relevant community. The input data includes the user's participation application information. The output is a notification message to the organizer. Specifically, the server obtains the organizer's contact information and sends the notification message.

[0706] Step 10:

[0707] The terminal notifies the user of participation approval and activity details. Input data includes the approval information and details sent from the server. The output is a notification message displayed on the user's screen. Specific operations include displaying the participation approval message, event schedule, and meeting place information to the user.

[0708] Step 11:

[0709] The user participates in the actual activity based on the notified information. The input data includes the notified activity details. The output is a record of the user's actual activity participation. The specific operation is for the user to go to the notified meeting place and participate in the activity.

[0710] (Application example 2)

[0711] 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."

[0712] In order for elderly people to find new meaning in life after retirement, they need to find appropriate activities and communities that take into account not only their hobbies and interests but also their current emotional state. However, existing matching systems do not take these emotional factors into account, making it difficult for users to find activities and communities that truly satisfy them.

[0713] 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 means for receiving profile data and emotion data input by the user, means for generating a plurality of activity candidates suitable for the user based on the profile data and emotion data, and means for presenting the generated activity candidates to the user. This makes it possible to suggest appropriate activities and communities that take into account not only the user's hobbies and interests but also their emotional state.

[0714] "Profile data" refers to basic information such as hobbies, interests, skills, and location that users enter themselves.

[0715] "Emotion data" refers to information that represents the user's current emotional state and is detected by an emotion recognition system.

[0716] "Activity candidates" refers to a list of multiple candidate activities and communities suitable for a user, generated based on the user's profile data and emotion data.

[0717] "Means for generating" refers to methods or techniques for analyzing user input data and listing appropriate activity candidates based on that data.

[0718] The "presentation means" refers to a method or technique for visually or audibly displaying the generated activity candidates to the user.

[0719] "Participation application" refers to the application procedure a user goes through to participate in an activity or community that interests them.

[0720] "Means for sending notifications" refers to the methods and techniques for sending notifications to relevant groups or parties based on a user's participation request.

[0721] "Means for providing detailed information" refers to methods and techniques for providing detailed information about activities and events to users.

[0722] This invention provides a system for helping retired people find new meaning in life, including an application installed on a smartphone or head-mounted display (HMD).

[0723] System configuration

[0724] 1. Entering user profile and emotion data

[0725] Users access the application using their smartphone or HMD and enter their profile data, which includes information such as hobbies, interests, skills, and location.

[0726] Furthermore, users input their current emotional state through images or videos, and emotion data is automatically detected using an emotion recognition system (e.g., emotion_engine library).

[0727] 2. Receipt and storage of data

[0728] The server receives the profile data and emotion data entered by the user and stores them in a database.

[0729] 3. Data analysis and activity candidate generation

[0730] The server's AI matching algorithm (e.g., the ai_matcher library) analyzes the received profile and emotional data to generate optimal activity and community suggestions, taking into account the user's hobbies and skills as well as their current emotional state.

[0731] 4. Suggested activities

[0732] The generated activity candidates are presented to the user on their smartphone or HMD, and the user selects the activity that interests them.

[0733] 5. Application and Notification

[0734] Based on the activity selected by the user, a participation request is sent to the server and notifications are sent to relevant communities and stakeholders.

[0735] The notification includes the user's profile information and details of the selected activity, allowing community organizers to receive new participant information.

[0736] 6. Providing more information

[0737] Users will be provided with activity details based on the notification, including details such as the date, time, and location of the activity, as well as any precautions.

[0738] Specific processing examples

[0739] For example, if a user lists gardening as a hobby and the emotion engine detects that they find it relaxing, the system will suggest gardening-related activities and communities, such as nearby gardening clubs or online workshops.

[0740] Prompt Sentence Examples

[0741] If a user has a particular hobby (gardening) and is detected as relaxed by an emotion recognition system, suggest an appropriate virtual activity. Include details about the activity you are suggesting and the reason for suggesting it.

[0742] In this way, it becomes possible to help users find appropriate activities and communities based on their profile data and emotional data, allowing them to find new meaning in life and live a fulfilling life.

[0743] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0744] Step 1:

[0745] Users access the application using a smartphone or head-mounted display (HMD) and enter their profile data. The profile data includes information such as hobbies, interests, skills, and location. The entered data is sent to the system's database and stored. The input of this step is the user's profile data, and the output is the profile data stored in the database.

[0746] Step 2:

[0747] The user inputs emotional data using a camera. The emotional data is captured in real time from images or videos and analyzed by an emotion recognition system (e.g., emotion_engine). As a result of the analysis, the user's current emotional state is detected and sent to the system and stored in a database. The input of this step is the user's image or video, and the output is the analyzed emotional data.

[0748] Step 3:

[0749] The server receives the profile data and emotion data stored in the database and analyzes them using an AI matching algorithm (e.g., ai_matcher). This analysis includes the user's hobbies, skills, and current emotional state. Based on this, activity candidates suitable for the user are generated. The input of this step is the profile data and emotion data, and the output is the generated activity candidates.

[0750] Step 4:

[0751] The server sends the generated activity candidates to the user's smartphone or HMD for presentation. The user checks the detailed information of the activity candidates displayed on the screen and selects the activity of interest. The input of this step is the generated activity candidates, and the output is the user's selected activity.

[0752] Step 5:

[0753] Based on the user's selected activity, a request to join is made. The request is sent to the server, which processes it and sends a notification to relevant communities and stakeholders. The notification contains the user's profile information and details of the selected activity. The input of this step is the user's request to join, and the output is the notification sent.

[0754] Step 6:

[0755] The server provides the user with detailed information about the activity based on the notification. This information includes the date, time, location, and important notes of the activity. Based on the information notified, the user participates in the actual activity or event. The input of this step is the detailed information based on the notification, and the output is the detailed information of the activity provided to the user.

[0756] Through these steps, users can find the most suitable activities and communities based on their emotional state and profile data, and discover new meanings in life, which is expected to improve the quality of their lives.

[0757] 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.

[0758] 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.

[0759] 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.

[0760] [Third embodiment]

[0761] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0762] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0763] 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).

[0764] 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.

[0765] 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.

[0766] 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).

[0767] 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.

[0768] 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.

[0769] 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.

[0770] 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.

[0771] 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.

[0772] 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."

[0773] This invention relates to a system that matches appropriate communities and activities to users who are looking for new meaning in life after retirement. Specifically, it involves a series of processes that exchange data between a server, terminals, and users, and uses AI to suggest optimal activities and communities.

[0774] System configuration

[0775] 1. User fills out profile

[0776] A user accesses a dedicated terminal or web service and enters information about their hobbies, interests, skills, region, etc. As a specific example, consider the case where a user selects gardening, cooking, and travel as hobbies and enters camera photography as a skill.

[0777] 2. The server receives the data

[0778] The server receives the profile data entered by the user and stores it in a temporary database, and it is important that the data is received accurately during this process.

[0779] 3. Data Analysis

[0780] An AI algorithm on the server analyzes the received profile data, for example, searching for active gardening clubs and related events based on the hobby "gardening."

[0781] 4. Generating Matching Candidates

[0782] Based on the analysis results, the server will then list multiple activity options suitable for the user, such as gardening clubs, cooking classes, and travel groups.

[0783] 5. Present candidates to the user

[0784] The device presents the matching candidates sent from the server to the user, and the user's screen displays detailed information about the activity and the profiles of the potential participants.

[0785] 6. User Selection and Participation Application

[0786] The user selects an activity that interests them and submits an application to participate, for example, if the user wishes to join a gardening club, they submit an application to that club.

[0787] 7. Application Processing and Notification

[0788] The server processes the user's request to join and sends a notification to the organizer of the corresponding community, who then receives the new joiner's information.

[0789] 8. Providing more information

[0790] The device will notify the user of participation approval and detailed information, including the event schedule, activities, and meeting place.

[0791] 9. User Participation

[0792] The user then participates in an actual activity based on the information provided, for example, attending the first meeting of a gardening club.

[0793] Through the above process, users can easily find new meaning in life and live a fulfilling life. This system is characterized by the efficient exchange of data between the server, device, and user, and by using AI to perform optimal matching.

[0794] The processing flow will be explained below.

[0795] Step 1:

[0796] Users enter their profile data, such as hobbies, interests, skills, and location, into a form on a dedicated device or web service, and press the "Submit" button. This information is needed for subsequent analysis and matching.

[0797] Step 2:

[0798] The server receives the profile data sent by the user, parses the data sent in the HTTP request, converts it into the required format, and stores it in a temporary database.

[0799] Step 3:

[0800] The AI ​​algorithm on the server analyzes the received profile data. At this stage, it searches the database for activities and communities that match the user's hobbies, interests, and skills. For example, if a user enters "gardening" as a hobby, it will extract community data related to gardening.

[0801] Step 4:

[0802] The server generates multiple activity suggestions suitable for the user based on the analysis results of the AI ​​algorithm. Here, a list of suggested activities is created based on the user's interests and skills. Examples may include gardening clubs, cooking classes, travel circles, etc.

[0803] Step 5:

[0804] The server transmits the generated activity candidate data to the terminal, where the data is converted into a format suitable for display on the user's display screen.

[0805] Step 6:

[0806] The device displays the matching candidates sent from the server to the user, and the user can check the details of the activity, the profiles of the potential participants, the date and time, and the location of the event.

[0807] Step 7:

[0808] The user selects the activity they are interested in and applies to participate. When the user presses the "Apply to participate" button, the information is sent to the server.

[0809] Step 8:

[0810] The server receives and processes the user's participation application data, checks which community the user has applied to join, and sends a notification to the organizer of the corresponding community.

[0811] Step 9:

[0812] The server sends a notification to the organizer and prepares to provide the user with participation acceptance and activity details, including the participation acceptance message, event details, and meeting place information.

[0813] Step 10:

[0814] The terminal notifies the user of the participation approval and detailed information sent from the server, and the user confirms the date, location, and belongings of the activity to be participated in based on this information.

[0815] Step 11:

[0816] The user can then participate in actual activities based on the information provided. For example, by participating in the first meeting of a gardening club, the user has the opportunity to find a new purpose in life.

[0817] Following these detailed steps will help users find new activities and communities that suit them, helping them find meaning in their post-retirement lives.

[0818] Example 1

[0819] 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."

[0820] Users looking for new meaning in life after retirement need to be able to easily find the right community or activity. However, conventional systems often fail to find activities or communities that best suit a user's individual interests and skills. Another issue with these systems is that they require users to manually search through multiple options and select the one that best suits them.

[0821] 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.

[0822] In this invention, the server includes means for receiving profile data input by a user, means for analyzing the profile data, and means for generating a plurality of activity candidates suitable for the user based on the analysis results, thereby enabling the user to easily find activities and communities that best suit their interests and skills.

[0823] "User" refers to an individual who uses the system to enter profile data and find activities and communities that best suit them.

[0824] "Profile Data" refers to information entered by a user, such as hobbies, interests, skills, and location.

[0825] "Means for analyzing" refers to a function that performs calculations to find the activities and communities that are most suitable for the user based on the input profile data.

[0826] "Suggested Activities" refers to activities or communities that may be suggested to a user based on analyzed profile data.

[0827] "Means for generating" refers to the function of listing multiple candidate activities based on the analysis results and making them ready to present to the user.

[0828] The "means for presenting" refers to a function for displaying the generated activity candidates on the screen in a manner that is visible to the user.

[0829] "Means for processing participation applications" refers to the function of accepting a user's intention to participate in an activity selected by the user and processing it within the system.

[0830] "Means for sending notifications" refers to the functionality for sending notifications to relevant communities and stakeholders based on processed participation applications.

[0831] The "means for providing detailed information" refers to a function for notifying the user of specific information regarding activities after participation is approved.

[0832] This invention relates to a system that matches appropriate communities and activities to users who are looking for new meaning in life after retirement. Data is exchanged between a server, a terminal, and the user, and optimal activities and communities are suggested using AI. Specific embodiments of this system are described below.

[0833] System Configuration

[0834] The system mainly consists of the following components:

[0835] 1. Means of receiving your profile data

[0836] 2. Means of analyzing profile data

[0837] 3. A method for generating candidate activities based on the analysis results

[0838] 4. Means of presenting suggested activities to users

[0839] 5. Means of handling user activity selection and participation requests

[0840] 6. Means of sending notifications based on participation requests

[0841] 7. Means of providing users with more information about their activities

[0842] Hardware and Software

[0843] server:

[0844] Hardware: General server equipment (e.g., dual-core or quad-core CPU, 16GB RAM, SSD storage)

[0845] Software: Web frameworks such as Django or Flask, machine learning libraries such as Scikit-learn or TensorFlow, and database systems such as MySQL or PostgreSQL.

[0846] Device:

[0847] Hardware: Personal computers, tablets, smartphones

[0848] Software: Web browser, JavaScript framework (e.g. React)

[0849] Processing flow

[0850] The server receives profile data entered by the user. The user accesses a dedicated terminal or web service and enters information such as hobbies, interests, skills, and location. For example, consider a user entering, "I'm interested in gardening, cooking, and traveling. I'm good at photography."

[0851] The server stores the received profile data in a temporary database. This process requires validation to ensure the accuracy of the data. Implement data validation functionality using a web framework such as Django or Flask.

[0852] Next, AI algorithms in the server analyze the received profile data. For example, based on the hobby "gardening," they search for currently active gardening clubs and related events. This analysis is performed using Python-based machine learning libraries such as Scikit-learn and TensorFlow.

[0853] Based on the analysis results, the server generates multiple activity candidates suitable for the user. These candidates are stored in a database system such as MySQL or PostgreSQL. The generated activity candidates are updated in real time to include the latest activity and event information.

[0854] The user's device presents these activity suggestions sent from the server. Detailed information about the listed activities and profiles of potential participants are displayed on the user's screen. This display is done using the JavaScript framework React.

[0855] Users select an activity they are interested in and submit a participation request. For example, a user may request, "I would like to join the gardening club." This request data is again sent to the server via a RESTful API, and the server processes the user's participation request. This process includes temporarily storing the data required for participation and sending notifications to related communities and stakeholders. Notifications are sent using SendGrid or Firebase Cloud Messaging.

[0856] Finally, the server notifies the user of the approval and detailed information, such as "The first meeting of the gardening club will be held next Saturday at 2:00 PM in the flowerbeds of the park." Based on this information, the user can then participate in the actual activity.

[0857] Specific examples

[0858] Prompt Sentence Examples

[0859] "I'd like to find a new hobby after retirement. I'm interested in gardening, cooking, and traveling. I'm good at photography. Please introduce me to some suitable activities and communities."

[0860] As a result, this system helps users easily find new meaning in life and continue to live a fulfilling life.

[0861] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0862] Step 1:

[0863] The user enters their profile. They access a dedicated device or a web service and enter information such as hobbies, interests, skills, and location. The entered data (e.g., hobbies are gardening, cooking, and travel, and skills are photography) is sent via an HTML form.

[0864] Input: User's hobbies, interests, skills, and location

[0865] Output: Profile data

[0866] Step 2:

[0867] The server receives the data. The server receives the profile data submitted by the user via a RESTful API, stores the data in a temporary database (e.g., SQLite or PostgreSQL), and performs validation to ensure the data is correct.

[0868] Input: Profile data

[0869] Output: Validated data

[0870] Step 3:

[0871] The server analyzes the data. The validated data is then input into a machine learning model to analyze the user's interests and skills. Specifically, it uses Scikit-learn and TensorFlow to generate a list of candidate activities.

[0872] Input: Validated data

[0873] Output: Analysis results (list of activity candidates)

[0874] Step 4:

[0875] The server generates matching candidates. Based on the analysis results, it selects multiple activity candidates suitable for the user and stores them in a database such as MySQL or PostgreSQL. This list includes detailed information about the activities and their profiles.

[0876] Input: Analysis results (list of activity candidates)

[0877] Output: Generated activity candidates

[0878] Step 5:

[0879] The device presents candidates to the user. The activity candidates sent from the server are displayed on the user's screen. The JavaScript framework React is used to display detailed information about the listed activities and profiles of the participants.

[0880] Input: Generated activity candidates

[0881] Output: The screen displayed to the user

[0882] Step 6:

[0883] The user selects an activity they are interested in and submits a participation request. The user selects an activity they are interested in on the system and submits a participation request for the activity. This application data is again sent to the server via the RESTful API.

[0884] Input: User activity selection, participation application

[0885] Output: Participation application data

[0886] Step 7:

[0887] The server processes the participation requests. The server processes the received participation request data and sends notifications to relevant communities and stakeholders. This notification is done using SendGrid or Firebase Cloud Messaging.

[0888] Input: Participation application data

[0889] Output: Send notification

[0890] Step 8:

[0891] The terminal provides detailed information to the user. Based on the content of the notification sent by the server, the user is notified of specific activity information (such as the event schedule and meeting place).

[0892] Input: Notification content

[0893] Output: Provides detailed information

[0894] Step 9:

[0895] The user participates in an activity. The user participates in an actual activity based on the notified activity information. For example, the user heads to a designated flower bed in a park to participate in the first meeting of the gardening club.

[0896] Input:Detailed information

[0897] Output: User activity participation

[0898] (Application example 1)

[0899] 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."

[0900] In modern society, finding a new purpose in life after retirement is important for many people. However, finding suitable communities and activities can be difficult. In particular, physical constraints and a lack of information make it difficult to confirm the content of activities before actually participating. Furthermore, conventional methods have limited ability to suggest optimal activities based on the user's hobbies and skills.

[0901] 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.

[0902] In this invention, the server includes: means for receiving profile data entered by a user; means for generating multiple activity candidates suitable for the user based on the profile data; means for presenting the generated activity candidates to the user; means for processing a request to participate in an activity selected by the user based on the selected activity; means for sending a notification to a related community or related party based on the processed participation request; means for providing the user with detailed information about the activity based on the notification; means for suggesting activity candidates based on the user profile using a generative AI model; and means for the user to virtually experience the suggested activities using a virtual reality device. This allows the user to virtually experience the target activities, making it easier to select an appropriate activity. This makes the process of finding a new purpose in life more efficient and effective.

[0903] Definitions of important words

[0904] "Profile Data" is data entered by a user that includes personal information such as hobbies, interests, skills, and location.

[0905] "Suggested Activities" refers to suitable communities and events based on the user's profile data.

[0906] "Generative AI Model" means an artificial intelligence model used to suggest optimal activities based on a user profile.

[0907] A "virtual reality device" is hardware that enables a user to virtually experience activities in a virtual reality environment, and examples include VR headsets.

[0908] "Visiting" is the process of using virtual reality devices to simulate an activity before participating in it.

[0909] A "notification" is a message sent to a related community or person concerned about the processing result or detailed information of an application to participate in an activity.

[0910] MODE FOR CARRYING OUT THE INVENTION

[0911] The embodiment of the present invention includes the following procedures and hardware / software configurations.

[0912] Hardware and Software Configuration

[0913] Hardware:

[0914] Smartphone

[0915] Head-mounted displays (e.g., Oculus Rift, HTC Vive)

[0916] server

[0917] Database

[0918] software:

[0919] Python

[0920] SQLite3

[0921] OpenAI API

[0922] A web interface (for users to enter their profile data)

[0923] Virtual reality applications (for users to have a virtual experience)

[0924] Process Details

[0925] User fills out profile

[0926] Users access a dedicated terminal or web interface and enter information about their hobbies, interests, skills, location, etc. This information is collected as "profile data" and sent to a server.

[0927] Data reception and storage

[0928] The server receives the profile data entered by the user and stores it in a temporary database (e.g., SQLite3). Input validation and filtering are performed automatically to ensure data accuracy.

[0929] Data analysis

[0930] An AI algorithm on the server analyzes the profile data and lists multiple activity candidates suitable for the user. The analysis is performed using the OpenAI API, and the generative AI model suggests appropriate communities and activities based on the user's hobbies and skills.

[0931] Presentation of match candidates

[0932] The user's terminal or VR device displays the activity candidates sent from the server. The user can view the activity details and select the activity that interests them.

[0933] Trial experience of the activity

[0934] When using a head-mounted display, users can virtually experience the proposed activity, allowing them to check the atmosphere and content of the activity before actually participating.

[0935] Specific examples

[0936] If a user inputs hobbies such as "gardening," "cooking," and "traveling" and "photography skills," the system sends the following prompts to the generative AI model:

[0937] plaintext

[0938] Hobbies: Gardening, Cooking, Traveling, Skills: Photography, Region: Tokyo, please suggest suitable communities and activities.

[0939] The generated activity candidates may look like this:

[0940] 1. Gardening Club

[0941] 2. Cooking Classes

[0942] 3. Travel Circle

[0943] Users can try out these options using a VR device and select the activity that best suits them. For example, experiencing the atmosphere and activities of a gardening club in VR can solidify their desire to participate. Furthermore, users will automatically be notified of the details of their chosen activity and be notified of the necessary participation details.

[0944] This invention allows users to discover more relevant and attractive communities and activities through virtual experiences. Furthermore, by utilizing a generative AI model, it is possible to make recommendations that are optimized for each individual user. This system aims to improve the user experience, which was difficult to achieve with conventional methods.

[0945] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0946] Program processing flow

[0947] Step 1:

[0948] The user accesses a dedicated terminal or web interface and enters their profile data, such as hobbies, interests, skills, and region. The entered data is sent to a temporary database. Input: Hobbies, interests, skills, region Output: User profile data

[0949] Step 2:

[0950] The server receives the profile data entered by the user. The received data undergoes syntax checking and input filtering and is then saved in a temporary database (e.g., SQLite3). Input: User profile data Output: Profile data saved in the database

[0951] Step 3:

[0952] The AI ​​algorithm on the server analyzes the received profile data. At this time, a generative AI model is used to list multiple activity candidates suitable for the user. A prompt statement is sent to the generative AI model to obtain recommended activity candidates. Input: Saved profile data, prompt statement (example: "Based on hobbies: gardening, cooking, travel, skills: photography, and area: Tokyo, please suggest appropriate communities and activities.") Output: Generated list of activity candidates

[0953] Step 4:

[0954] The server sends the generated activity candidate list to the terminal, which then displays it to the user. The user then views detailed information about these activity candidates through a screen or VR device. Input: Activity candidate list Output: Activity candidate details displayed on the user's terminal

[0955] Step 5:

[0956] The user selects an activity that interests them and applies to participate in that activity. The application is sent to the server via the terminal. Input: Activity selected by the user Output: Application to participate

[0957] Step 6:

[0958] The server processes the request and sends notifications to the relevant communities and stakeholders. These notifications include the request and the user's profile data. Input: Request to join. Output: Notifications sent to the relevant communities.

[0959] Step 7:

[0960] The server receives participation approval and detailed information from related communities and stakeholders, and sends it to the user's terminal. The detailed information includes the event schedule, activities, meeting place, etc. Input: Approval and detailed information from related communities Output: Detailed information sent to the user's terminal

[0961] Step 8:

[0962] The user uses a head-mounted display to virtually experience the proposed activity. The virtual experience simulates the atmosphere and content of the actual activity in a VR environment. Input: Detailed information about the proposed activity. Output: VR experience of the virtual activity that the user has virtually experienced.

[0963] Step 9:

[0964] The user finally decides which activities they want to participate in, and the server sends a final notification to the relevant community. Input: User's selection after virtual experience Output: Final notification

[0965] 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.

[0966] This invention relates to a system that matches appropriate communities and activities to users who are looking for new meaning in life after retirement. In particular, by incorporating an emotion engine, this system enables matching that takes into account the user's emotional state. Specifically, it involves a series of processes that exchange data between a server, terminal, and user, and uses AI and the emotion engine to suggest optimal activities and communities.

[0967] System configuration

[0968] 1. The user enters their profile data and emotional data.

[0969] A user accesses a dedicated device or web service and enters profile data such as their hobbies, interests, skills, and location. Furthermore, the emotion recognition system inputs or detects their current emotional state. As a concrete example, consider the case where a user selects gardening, cooking, and travel as hobbies and registers camera photography as a skill, and the emotion engine recognizes the emotion as "relaxed."

[0970] 2. The server receives the data

[0971] The server receives the profile data and emotion data entered by the user and stores them in a temporary database. For example, a user who is relaxed may be suited to a gardening club, which has a stress-reducing effect.

[0972] 3. Data Analysis

[0973] The AI ​​algorithm in the server analyzes the received profile and emotional data. At this stage, it searches the database for activities and communities that take into account the user's current emotional state, along with their hobbies, interests, and skills. For example, a user who is "relaxing" will be presented with activities that have a relaxing effect.

[0974] 4. Generating Matching Candidates

[0975] The server generates multiple activity candidates suitable for the user based on the analysis results of the AI ​​and emotion engine. This process lists activities that match the user's current emotional state. For example, it may include gardening clubs, cooking classes, travel circles, etc. that reflect the user's interests and emotional state.

[0976] 5. Present candidates to the user

[0977] The device presents the matching candidates sent from the server to the user, who is then shown detailed information about the activity, the reason for the recommendation based on the user's emotional state, and the profile of the potential participants.

[0978] 6. User Selection and Participation Application

[0979] The user selects an activity that they are interested in and submits an application to participate in. For example, if the user wants to join a gardening club based on the reasons recommended by the emotion engine, they submit an application to join the club.

[0980] 7. Application Processing and Notification

[0981] The server processes the user's request to join and sends a notification to the organizer of the corresponding community, who then receives the new joiner's information.

[0982] 8. Providing more information

[0983] The terminal notifies the user of participation approval and activity details, including a participation approval message, event details, and meeting place information.

[0984] 9. User Participation

[0985] The user can then participate in actual activities based on the information provided. For example, by participating in the first meeting of a gardening club, the user has the opportunity to find a new purpose in life.

[0986] Through this process, users can easily find new activities and communities that suit them, enabling them to live fulfilling lives. This system is characterized by the efficient exchange of data between the server, device, and user, and by using AI and an emotion engine to perform optimal matching.

[0987] The processing flow will be explained below.

[0988] Step 1:

[0989] The user enters their profile data and emotional data. They fill out information such as hobbies, interests, skills, and location on a dedicated device or a form on a web service, and then press the "Submit" button. The emotion recognition system also detects the user's current emotional state, and this data is also sent. For example, if a user selects "gardening," "cooking," and "travel" as their hobbies and inputs camera photography as a skill, their emotional state is recognized as "relaxed."

[0990] Step 2:

[0991] The server receives the profile data and emotion data sent by the user, converts this data into an analyzable format, and stores it in a temporary database.

[0992] Step 3:

[0993] An AI algorithm in the server analyzes the received profile and emotional data. For example, based on the hobby of "gardening" and the emotional state of "relaxation," it searches a database for relaxing activities related to gardening.

[0994] Step 4:

[0995] The server generates multiple activity suggestions suitable for the user based on the analysis results of the AI ​​algorithm and emotion engine, such as a list of relaxing activities such as gardening clubs, cooking classes, and art therapy.

[0996] Step 5:

[0997] The server transmits the generated activity candidate data to the terminal, where the data is converted to a format suitable for display on the user's display screen.

[0998] Step 6:

[0999] The device displays the matching candidates sent from the server to the user. The user's screen displays detailed information about each activity, the reason for the recommendation (for example, because it is expected to have a relaxing effect), and the profiles of the potential participants.

[1000] Step 7:

[1001] The user selects an activity they are interested in and applies to join. For example, the user clicks the "Apply" button to join the gardening club. This information is sent to the server.

[1002] Step 8:

[1003] The server receives and processes the user's participation application data, checks which community the user has applied to join, and sends a notification to the organizer of the corresponding community.

[1004] Step 9:

[1005] The server sends a notification to the organizer and prepares to provide the user with participation acceptance and activity details, including the participation acceptance message, event details, and meeting place information.

[1006] Step 10:

[1007] The terminal notifies the user of the participation approval and detailed information sent from the server, and the user confirms the activity date, location, belongings, etc. based on this information.

[1008] Step 11:

[1009] The user can then participate in actual activities based on the information provided, for example, attending the first meeting of a gardening club, and gaining the opportunity to find a new purpose in life.

[1010] By following these detailed steps, users can easily find new activities and communities that suit them, and find meaning in their post-retirement lives. By combining it with an emotion engine, matching can be performed taking into account the user's emotional state, resulting in more appropriate activities being selected.

[1011] Example 2

[1012] 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."

[1013] In recent years, an increasing number of elderly people are seeking new meaning in life after retirement. However, it is not easy to find communities and activities that suit their individual interests, skills, and mental state. Conventional systems have difficulty proposing activities that take into account the user's emotional state, and as a result, they often present activities that are not in line with the user's interests. There is a need to solve this problem and propose activities that are optimal for users.

[1014] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving profile data and emotion data input by the user, means for generating a plurality of activity candidates suitable for the user based on the profile data and emotion data, and means for presenting the generated activity candidates to the user. This makes it possible to suggest activities that take into account the user's individual interests, skills, and mental state.

[1015] "Profile Data" refers to personal information about a user, such as their hobbies, interests, skills, and location.

[1016] "Emotion data" refers to information indicative of a user's current emotional state that is collected by an emotion recognition system.

[1017] "Means for receiving" refers to the function or method by which the server receives input data from the user.

[1018] "Means of analysis" refers to the functions and methods by which algorithms and programs within the server analyze the received data and extract useful information from it.

[1019] "Means for generating" refers to a function or method for generating multiple activity candidates suitable for the user based on the analysis results.

[1020] The "means for presenting" refers to a function or method for displaying the generated activity candidates to the user and allowing the user to select one.

[1021] "Means for processing participation requests" refers to the functions and methods for accepting, managing, and processing participation requests for the activities selected by the user.

[1022] "Means for sending notifications" refers to the functions and methods for informing relevant communities or stakeholders based on processed participation applications.

[1023] "Means for providing detailed information" refers to a function or method for informing the user of specific information about the activity (e.g., event dates and meeting places) based on the notification.

[1024] "Suggested Activities" refers to a list of activities and communities that a user can participate in that are suggested based on the user's profile data and emotional data.

[1025] "Database" refers to a system for systematically storing and managing information such as profile data, emotional data, analysis results, and potential activities.

[1026] "AI Algorithm" refers to the artificial intelligence technology used to analyze user data and generate optimal activity suggestions.

[1027] An "emotion recognition system" refers to technology that uses sensors such as cameras and microphones to recognize a user's current emotional state.

[1028] This invention relates to a system that matches appropriate communities and activities to users who are looking for a new purpose in life after retirement. By combining this system with an emotion engine, it enables matching that takes into account the user's emotional state, and it exchanges data between the server, terminal, and user, and uses AI and the emotion engine to suggest optimal activities and communities.

[1029] System configuration

[1030] 1. The user enters their profile data and emotional data.

[1031] Users access a dedicated device or web service and enter profile data such as hobbies, interests, skills, and region. An emotion recognition system using a camera and microphone also inputs or detects the user's current emotional state. For example, a scenario is envisioned in which a user selects "gardening," "cooking," and "travel" as hobbies and registers "photography" as a skill, and the emotion recognition system recognizes the emotion as "relaxed."

[1032] 2. The server receives the data

[1033] The server receives profile and emotion data from users via API and stores it in a temporary database. For example, a user who is relaxing might be suited to a "gardening club" that has a stress-reducing effect.

[1034] 3. Data Analysis

[1035] The AI ​​algorithms on the server analyze the received profile data and emotional data. This analysis involves taking into account the user's hobbies, interests, skills, and emotional state, and searching the database for the most suitable activities and communities. For example, if a user is "relaxing," activities that have a relaxing effect will be presented.

[1036] 4. Generating Matching Candidates

[1037] The server generates multiple activity candidates suitable for the user based on the analysis results of the AI ​​and emotion engine. This process lists activities that match the user's current emotional state. Possible activities include "gardening club," "cooking class," and "travel circle," reflecting the user's interests and emotional state.

[1038] 5. Present candidates to the user

[1039] The activity suggestions generated by the server are sent to the terminal and presented to the user on the terminal, where detailed information about the activity, the reason for the recommendation based on the user's emotional state, and the profiles of the potential participants are displayed.

[1040] 6. User Selection and Participation Application

[1041] The user selects an activity they are interested in and submits an application to participate. For example, if the user wishes to join the "gardening club" based on the reasons recommended by the emotion engine, they press the application button to express their intention to participate.

[1042] 7. Application Processing and Notification

[1043] The server processes the user's request to join and sends a notification to the relevant community organizer, who receives the notification and confirms the new member.

[1044] 8. Providing more information

[1045] The terminal notifies the user of the participation acceptance and activity details, including the participation acceptance message, the event schedule, and the meeting place information.

[1046] 9. User Participation

[1047] Users can then take part in real activities based on the information they receive, for example attending the first meeting of a "gardening club" and finding meaning in life through new experiences.

[1048] Examples of specific examples and prompts

[1049] Examples:

[1050] User A selects "gardening," "cooking," and "travel" as hobbies and registers "photography" as a skill on a dedicated device. Based on the emotional state recognized as "relaxed," he / she wishes to join the gardening club.

[1051] Example prompt sentence:

[1052] "If a user has hobbies like gardening, cooking, and traveling, and a skill like photography, and is currently relaxing, please suggest which communities and activities would be suitable. Then, please show the process flow for choosing the best activity and completing the user's participation process."

[1053] The above system allows users to easily find activities and communities that are best suited to them and discover new meaning in life.

[1054] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1055] Step 1:

[1056] The user accesses a dedicated device or web service and enters profile data such as their hobbies, interests, skills, and region into a form. The emotion recognition system then uses a camera and microphone to analyze their current emotions. Specifically, the user selects "gardening" or "cooking" as their hobbies, and the emotion recognition system recognizes the emotion as "relaxation." Inputs include the user's hobbies, interests, skills, and emotional data. This data is then sent to the server via an API.

[1057] Step 2:

[1058] The server receives profile data and emotion data and stores it in a temporary database. The input data includes the hobbies, interests, skills, and emotion data entered by the user. The output is the data stored in the temporary database. The specific operation is to store the received data in the corresponding database table.

[1059] Step 3:

[1060] The AI ​​algorithm in the server analyzes the stored data. The input data includes the user's profile data and emotional data stored on the server. The AI ​​algorithm combines hobbies, interests, skills, and emotional state to search the database for the most suitable activities and communities. The output is a list of suitable activity candidates as a result of the analysis. Specifically, the AI ​​model inputs the data and calculates a matching score.

[1061] Step 4:

[1062] The server generates multiple candidate activities suitable for the user based on the analysis results of the AI ​​and emotion engine. The input data includes the analysis results of the AI ​​algorithm. The output is a list of the candidate activities generated. Specifically, it lists and selects activities that match the user's current emotional state.

[1063] Step 5:

[1064] The server sends the generated activity candidates to the terminal. The input data includes a list of the generated activity candidates. The output is notification information sent to the terminal. Specifically, the system sends the activity candidates to the user terminal in real time via the user interface.

[1065] Step 6:

[1066] The terminal presents the transmitted activity candidates to the user. The input data includes the list of activity candidates transmitted from the server. The output is the candidate list displayed on the user's screen. Specifically, the screen display logic is used to visually present the user with detailed information about the activity, the reason for the recommendation based on the user's emotional state, and profile information about the potential participants.

[1067] Step 7:

[1068] The user selects an activity they are interested in and submits an application to participate. The input data includes the activity the user selected and the reason for their selection. The output is a form in which the application information is sent to the server. The specific operation is to press the participation application button and the information is sent to the server.

[1069] Step 8:

[1070] The server processes user participation requests. Input data includes participation request information from users. Output includes the status of the processed request. Specific operations include receiving the request information, updating it in the database, and managing the status.

[1071] Step 9:

[1072] The server sends a notification to the organizer of the relevant community. The input data includes the user's participation application information. The output is a notification message to the organizer. Specifically, the server obtains the organizer's contact information and sends the notification message.

[1073] Step 10:

[1074] The terminal notifies the user of participation approval and activity details. Input data includes the approval information and details sent from the server. The output is a notification message displayed on the user's screen. Specific operations include displaying the participation approval message, event schedule, and meeting place information to the user.

[1075] Step 11:

[1076] The user participates in the actual activity based on the notified information. The input data includes the notified activity details. The output is a record of the user's actual activity participation. The specific operation is for the user to go to the notified meeting place and participate in the activity.

[1077] (Application example 2)

[1078] 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."

[1079] In order for elderly people to find new meaning in life after retirement, they need to find appropriate activities and communities that take into account not only their hobbies and interests but also their current emotional state. However, existing matching systems do not take these emotional factors into account, making it difficult for users to find activities and communities that truly satisfy them.

[1080] 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 means for receiving profile data and emotion data input by the user, means for generating a plurality of activity candidates suitable for the user based on the profile data and emotion data, and means for presenting the generated activity candidates to the user. This makes it possible to suggest appropriate activities and communities that take into account not only the user's hobbies and interests but also their emotional state.

[1081] "Profile data" refers to basic information such as hobbies, interests, skills, and location that users enter themselves.

[1082] "Emotion data" refers to information that represents the user's current emotional state and is detected by an emotion recognition system.

[1083] "Activity candidates" refers to a list of multiple candidate activities and communities suitable for a user, generated based on the user's profile data and emotion data.

[1084] "Means for generating" refers to methods or techniques for analyzing user input data and listing appropriate activity candidates based on that data.

[1085] The "presentation means" refers to a method or technique for visually or audibly displaying the generated activity candidates to the user.

[1086] "Participation application" refers to the application procedure a user goes through to participate in an activity or community that interests them.

[1087] "Means for sending notifications" refers to the methods and techniques for sending notifications to relevant groups or parties based on a user's participation request.

[1088] "Means for providing detailed information" refers to methods and techniques for providing detailed information about activities and events to users.

[1089] This invention provides a system for helping retired people find new meaning in life, including an application installed on a smartphone or head-mounted display (HMD).

[1090] System configuration

[1091] 1. Entering user profile and emotion data

[1092] Users access the application using their smartphone or HMD and enter their profile data, which includes information such as hobbies, interests, skills, and location.

[1093] Furthermore, users input their current emotional state through images or videos, and emotion data is automatically detected using an emotion recognition system (e.g., emotion_engine library).

[1094] 2. Receipt and storage of data

[1095] The server receives the profile data and emotion data entered by the user and stores them in a database.

[1096] 3. Data analysis and activity candidate generation

[1097] The server's AI matching algorithm (e.g., the ai_matcher library) analyzes the received profile and emotional data to generate optimal activity and community suggestions, taking into account the user's hobbies and skills as well as their current emotional state.

[1098] 4. Suggested activities

[1099] The generated activity candidates are presented to the user on their smartphone or HMD, and the user selects the activity that interests them.

[1100] 5. Application and Notification

[1101] Based on the activity selected by the user, a participation request is sent to the server and notifications are sent to relevant communities and stakeholders.

[1102] The notification includes the user's profile information and details of the selected activity, allowing community organizers to receive new participant information.

[1103] 6. Providing more information

[1104] Users will be provided with activity details based on the notification, including details such as the date, time, and location of the activity, as well as any precautions.

[1105] Specific processing examples

[1106] For example, if a user lists gardening as a hobby and the emotion engine detects that they find it relaxing, the system will suggest gardening-related activities and communities, such as nearby gardening clubs or online workshops.

[1107] Prompt Sentence Examples

[1108] If a user has a particular hobby (gardening) and is detected as relaxed by an emotion recognition system, suggest an appropriate virtual activity. Include details about the activity you are suggesting and the reason for suggesting it.

[1109] In this way, it becomes possible to help users find appropriate activities and communities based on their profile data and emotional data, allowing them to find new meaning in life and live a fulfilling life.

[1110] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1111] Step 1:

[1112] Users access the application using a smartphone or head-mounted display (HMD) and enter their profile data. The profile data includes information such as hobbies, interests, skills, and location. The entered data is sent to the system's database and stored. The input of this step is the user's profile data, and the output is the profile data stored in the database.

[1113] Step 2:

[1114] The user inputs emotional data using a camera. The emotional data is captured in real time from images or videos and analyzed by an emotion recognition system (e.g., emotion_engine). As a result of the analysis, the user's current emotional state is detected and sent to the system and stored in a database. The input of this step is the user's image or video, and the output is the analyzed emotional data.

[1115] Step 3:

[1116] The server receives the profile data and emotion data stored in the database and analyzes them using an AI matching algorithm (e.g., ai_matcher). This analysis includes the user's hobbies, skills, and current emotional state. Based on this, activity candidates suitable for the user are generated. The input of this step is the profile data and emotion data, and the output is the generated activity candidates.

[1117] Step 4:

[1118] The server sends the generated activity candidates to the user's smartphone or HMD for presentation. The user checks the detailed information of the activity candidates displayed on the screen and selects the activity of interest. The input of this step is the generated activity candidates, and the output is the user's selected activity.

[1119] Step 5:

[1120] Based on the user's selected activity, a request to join is made. The request is sent to the server, which processes it and sends a notification to relevant communities and stakeholders. The notification contains the user's profile information and details of the selected activity. The input of this step is the user's request to join, and the output is the notification sent.

[1121] Step 6:

[1122] The server provides the user with detailed information about the activity based on the notification. This information includes the date, time, location, and important notes of the activity. Based on the information notified, the user participates in the actual activity or event. The input of this step is the detailed information based on the notification, and the output is the detailed information of the activity provided to the user.

[1123] Through these steps, users can find the most suitable activities and communities based on their emotional state and profile data, and discover new meanings in life, which is expected to improve the quality of their lives.

[1124] 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.

[1125] 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.

[1126] 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.

[1127] [Fourth embodiment]

[1128] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1129] 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.

[1130] 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).

[1131] 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.

[1132] 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.

[1133] 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).

[1134] 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.

[1135] 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.

[1136] 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.

[1137] 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.

[1138] 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.

[1139] 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.

[1140] 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."

[1141] This invention relates to a system that matches appropriate communities and activities to users who are looking for new meaning in life after retirement. Specifically, it involves a series of processes that exchange data between a server, terminals, and users, and uses AI to suggest optimal activities and communities.

[1142] System configuration

[1143] 1. User fills out profile

[1144] A user accesses a dedicated terminal or web service and enters information about their hobbies, interests, skills, region, etc. As a specific example, consider the case where a user selects gardening, cooking, and travel as hobbies and enters camera photography as a skill.

[1145] 2. The server receives the data

[1146] The server receives the profile data entered by the user and stores it in a temporary database, and it is important that the data is received accurately during this process.

[1147] 3. Data Analysis

[1148] An AI algorithm on the server analyzes the received profile data, for example, searching for active gardening clubs and related events based on the hobby "gardening."

[1149] 4. Generating Matching Candidates

[1150] Based on the analysis results, the server will then list multiple activity options suitable for the user, such as gardening clubs, cooking classes, and travel groups.

[1151] 5. Present candidates to the user

[1152] The device presents the matching candidates sent from the server to the user, and the user's screen displays detailed information about the activity and the profiles of the potential participants.

[1153] 6. User Selection and Participation Application

[1154] The user selects an activity that interests them and submits an application to participate, for example, if the user wishes to join a gardening club, they submit an application to that club.

[1155] 7. Application Processing and Notification

[1156] The server processes the user's request to join and sends a notification to the organizer of the corresponding community, who then receives the new joiner's information.

[1157] 8. Providing more information

[1158] The device will notify the user of participation approval and detailed information, including the event schedule, activities, and meeting place.

[1159] 9. User Participation

[1160] The user then participates in an actual activity based on the information provided, for example, attending the first meeting of a gardening club.

[1161] Through the above process, users can easily find new meaning in life and live a fulfilling life. This system is characterized by the efficient exchange of data between the server, device, and user, and by using AI to perform optimal matching.

[1162] The processing flow will be explained below.

[1163] Step 1:

[1164] Users enter their profile data, such as hobbies, interests, skills, and location, into a form on a dedicated device or web service, and press the "Submit" button. This information is needed for subsequent analysis and matching.

[1165] Step 2:

[1166] The server receives the profile data sent by the user, parses the data sent in the HTTP request, converts it into the required format, and stores it in a temporary database.

[1167] Step 3:

[1168] The AI ​​algorithm on the server analyzes the received profile data. At this stage, it searches the database for activities and communities that match the user's hobbies, interests, and skills. For example, if a user enters "gardening" as a hobby, it will extract community data related to gardening.

[1169] Step 4:

[1170] The server generates multiple activity suggestions suitable for the user based on the analysis results of the AI ​​algorithm. Here, a list of suggested activities is created based on the user's interests and skills. Examples may include gardening clubs, cooking classes, travel circles, etc.

[1171] Step 5:

[1172] The server transmits the generated activity candidate data to the terminal, where the data is converted into a format suitable for display on the user's display screen.

[1173] Step 6:

[1174] The device displays the matching candidates sent from the server to the user, and the user can check the details of the activity, the profiles of the potential participants, the date and time, and the location of the event.

[1175] Step 7:

[1176] The user selects the activity they are interested in and applies to participate. When the user presses the "Apply to participate" button, the information is sent to the server.

[1177] Step 8:

[1178] The server receives and processes the user's participation application data, checks which community the user has applied to join, and sends a notification to the organizer of the corresponding community.

[1179] Step 9:

[1180] The server sends a notification to the organizer and prepares to provide the user with participation acceptance and activity details, including the participation acceptance message, event details, and meeting place information.

[1181] Step 10:

[1182] The terminal notifies the user of the participation approval and detailed information sent from the server, and the user confirms the date, location, and belongings of the activity to be participated in based on this information.

[1183] Step 11:

[1184] The user can then participate in actual activities based on the information provided. For example, by participating in the first meeting of a gardening club, the user has the opportunity to find a new purpose in life.

[1185] Following these detailed steps will help users find new activities and communities that suit them, helping them find meaning in their post-retirement lives.

[1186] Example 1

[1187] 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."

[1188] Users looking for new meaning in life after retirement need to be able to easily find the right community or activity. However, conventional systems often fail to find activities or communities that best suit a user's individual interests and skills. Another issue with these systems is that they require users to manually search through multiple options and select the one that best suits them.

[1189] 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.

[1190] In this invention, the server includes means for receiving profile data input by a user, means for analyzing the profile data, and means for generating a plurality of activity candidates suitable for the user based on the analysis results, thereby enabling the user to easily find activities and communities that best suit their interests and skills.

[1191] "User" refers to an individual who uses the system to enter profile data and find activities and communities that best suit them.

[1192] "Profile Data" refers to information entered by a user, such as hobbies, interests, skills, and location.

[1193] "Means for analyzing" refers to a function that performs calculations to find the activities and communities that are most suitable for the user based on the input profile data.

[1194] "Suggested Activities" refers to activities or communities that may be suggested to a user based on analyzed profile data.

[1195] "Means for generating" refers to the function of listing multiple candidate activities based on the analysis results and making them ready to present to the user.

[1196] The "means for presenting" refers to a function for displaying the generated activity candidates on the screen in a manner that is visible to the user.

[1197] "Means for processing participation applications" refers to the function of accepting a user's intention to participate in an activity selected by the user and processing it within the system.

[1198] "Means for sending notifications" refers to the functionality for sending notifications to relevant communities and stakeholders based on processed participation applications.

[1199] The "means for providing detailed information" refers to a function for notifying the user of specific information regarding activities after participation is approved.

[1200] This invention relates to a system that matches appropriate communities and activities to users who are looking for new meaning in life after retirement. Data is exchanged between a server, a terminal, and the user, and optimal activities and communities are suggested using AI. Specific embodiments of this system are described below.

[1201] System Configuration

[1202] The system mainly consists of the following components:

[1203] 1. Means of receiving your profile data

[1204] 2. Means of analyzing profile data

[1205] 3. A method for generating candidate activities based on the analysis results

[1206] 4. Means of presenting suggested activities to users

[1207] 5. Means of handling user activity selection and participation requests

[1208] 6. Means of sending notifications based on participation requests

[1209] 7. Means of providing users with more information about their activities

[1210] Hardware and Software

[1211] server:

[1212] Hardware: General server equipment (e.g., dual-core or quad-core CPU, 16GB RAM, SSD storage)

[1213] Software: Web frameworks such as Django or Flask, machine learning libraries such as Scikit-learn or TensorFlow, and database systems such as MySQL or PostgreSQL.

[1214] Device:

[1215] Hardware: Personal computers, tablets, smartphones

[1216] Software: Web browser, JavaScript framework (e.g. React)

[1217] Processing flow

[1218] The server receives profile data entered by the user. The user accesses a dedicated terminal or web service and enters information such as hobbies, interests, skills, and location. For example, consider a user entering, "I'm interested in gardening, cooking, and traveling. I'm good at photography."

[1219] The server stores the received profile data in a temporary database. This process requires validation to ensure the accuracy of the data. Implement data validation functionality using a web framework such as Django or Flask.

[1220] Next, AI algorithms in the server analyze the received profile data. For example, based on the hobby "gardening," they search for currently active gardening clubs and related events. This analysis is performed using Python-based machine learning libraries such as Scikit-learn and TensorFlow.

[1221] Based on the analysis results, the server generates multiple activity candidates suitable for the user. These candidates are stored in a database system such as MySQL or PostgreSQL. The generated activity candidates are updated in real time to include the latest activity and event information.

[1222] The user's device presents these activity suggestions sent from the server. Detailed information about the listed activities and profiles of potential participants are displayed on the user's screen. This display is done using the JavaScript framework React.

[1223] Users select an activity they are interested in and submit a participation request. For example, a user may request, "I would like to join the gardening club." This request data is again sent to the server via a RESTful API, and the server processes the user's participation request. This process includes temporarily storing the data required for participation and sending notifications to related communities and stakeholders. Notifications are sent using SendGrid or Firebase Cloud Messaging.

[1224] Finally, the server notifies the user of the approval and detailed information, such as "The first meeting of the gardening club will be held next Saturday at 2:00 PM in the flowerbeds of the park." Based on this information, the user can then participate in the actual activity.

[1225] Specific examples

[1226] Prompt Sentence Examples

[1227] "I'd like to find a new hobby after retirement. I'm interested in gardening, cooking, and traveling. I'm good at photography. Please introduce me to some suitable activities and communities."

[1228] As a result, this system helps users easily find new meaning in life and continue to live a fulfilling life.

[1229] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1230] Step 1:

[1231] The user enters their profile. They access a dedicated device or a web service and enter information such as hobbies, interests, skills, and location. The entered data (e.g., hobbies are gardening, cooking, and travel, and skills are photography) is sent via an HTML form.

[1232] Input: User's hobbies, interests, skills, and location

[1233] Output: Profile data

[1234] Step 2:

[1235] The server receives the data. The server receives the profile data submitted by the user via a RESTful API, stores the data in a temporary database (e.g., SQLite or PostgreSQL), and performs validation to ensure the data is correct.

[1236] Input: Profile data

[1237] Output: Validated data

[1238] Step 3:

[1239] The server analyzes the data. The validated data is then input into a machine learning model to analyze the user's interests and skills. Specifically, it uses Scikit-learn and TensorFlow to generate a list of candidate activities.

[1240] Input: Validated data

[1241] Output: Analysis results (list of activity candidates)

[1242] Step 4:

[1243] The server generates matching candidates. Based on the analysis results, it selects multiple activity candidates suitable for the user and stores them in a database such as MySQL or PostgreSQL. This list includes detailed information about the activities and their profiles.

[1244] Input: Analysis results (list of activity candidates)

[1245] Output: Generated activity candidates

[1246] Step 5:

[1247] The device presents candidates to the user. The activity candidates sent from the server are displayed on the user's screen. The JavaScript framework React is used to display detailed information about the listed activities and profiles of the participants.

[1248] Input: Generated activity candidates

[1249] Output: The screen displayed to the user

[1250] Step 6:

[1251] The user selects an activity they are interested in and submits a participation request. The user selects an activity they are interested in on the system and submits a participation request for the activity. This application data is again sent to the server via the RESTful API.

[1252] Input: User activity selection, participation application

[1253] Output: Participation application data

[1254] Step 7:

[1255] The server processes the participation requests. The server processes the received participation request data and sends notifications to relevant communities and stakeholders. This notification is done using SendGrid or Firebase Cloud Messaging.

[1256] Input: Participation application data

[1257] Output: Send notification

[1258] Step 8:

[1259] The terminal provides detailed information to the user. Based on the content of the notification sent by the server, the user is notified of specific activity information (such as the event schedule and meeting place).

[1260] Input: Notification content

[1261] Output: Provides detailed information

[1262] Step 9:

[1263] The user participates in an activity. The user participates in an actual activity based on the notified activity information. For example, the user heads to a designated flower bed in a park to participate in the first meeting of the gardening club.

[1264] Input:Detailed information

[1265] Output: User activity participation

[1266] (Application example 1)

[1267] 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."

[1268] In modern society, finding a new purpose in life after retirement is important for many people. However, finding suitable communities and activities can be difficult. In particular, physical constraints and a lack of information make it difficult to confirm the content of activities before actually participating. Furthermore, conventional methods have limited ability to suggest optimal activities based on the user's hobbies and skills.

[1269] 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.

[1270] In this invention, the server includes: means for receiving profile data entered by a user; means for generating multiple activity candidates suitable for the user based on the profile data; means for presenting the generated activity candidates to the user; means for processing a request to participate in an activity selected by the user based on the selected activity; means for sending a notification to a related community or related party based on the processed participation request; means for providing the user with detailed information about the activity based on the notification; means for suggesting activity candidates based on the user profile using a generative AI model; and means for the user to virtually experience the suggested activities using a virtual reality device. This allows the user to virtually experience the target activities, making it easier to select an appropriate activity. This makes the process of finding a new purpose in life more efficient and effective.

[1271] Definitions of important words

[1272] "Profile Data" is data entered by a user that includes personal information such as hobbies, interests, skills, and location.

[1273] "Suggested Activities" refers to suitable communities and events based on the user's profile data.

[1274] "Generative AI Model" means an artificial intelligence model used to suggest optimal activities based on a user profile.

[1275] A "virtual reality device" is hardware that enables a user to virtually experience activities in a virtual reality environment, and examples include VR headsets.

[1276] "Visiting" is the process of using virtual reality devices to simulate an activity before participating in it.

[1277] A "notification" is a message sent to a related community or person concerned about the processing result or detailed information of an application to participate in an activity.

[1278] MODE FOR CARRYING OUT THE INVENTION

[1279] The embodiment of the present invention includes the following procedures and hardware / software configurations.

[1280] Hardware and Software Configuration

[1281] Hardware:

[1282] Smartphone

[1283] Head-mounted displays (e.g., Oculus Rift, HTC Vive)

[1284] server

[1285] Database

[1286] software:

[1287] Python

[1288] SQLite3

[1289] OpenAI API

[1290] A web interface (for users to enter their profile data)

[1291] Virtual reality applications (for users to have a virtual experience)

[1292] Process Details

[1293] User fills out profile

[1294] Users access a dedicated terminal or web interface and enter information about their hobbies, interests, skills, location, etc. This information is collected as "profile data" and sent to a server.

[1295] Data reception and storage

[1296] The server receives the profile data entered by the user and stores it in a temporary database (e.g., SQLite3). Input validation and filtering are performed automatically to ensure data accuracy.

[1297] Data analysis

[1298] An AI algorithm on the server analyzes the profile data and lists multiple activity candidates suitable for the user. The analysis is performed using the OpenAI API, and the generative AI model suggests appropriate communities and activities based on the user's hobbies and skills.

[1299] Presentation of match candidates

[1300] The user's terminal or VR device displays the activity candidates sent from the server. The user can view the activity details and select the activity that interests them.

[1301] Trial experience of the activity

[1302] When using a head-mounted display, users can virtually experience the proposed activity, allowing them to check the atmosphere and content of the activity before actually participating.

[1303] Specific examples

[1304] If a user inputs hobbies such as "gardening," "cooking," and "traveling" and "photography skills," the system sends the following prompts to the generative AI model:

[1305] plaintext

[1306] Hobbies: Gardening, Cooking, Traveling, Skills: Photography, Region: Tokyo, please suggest suitable communities and activities.

[1307] The generated activity candidates may look like this:

[1308] 1. Gardening Club

[1309] 2. Cooking Classes

[1310] 3. Travel Circle

[1311] Users can try out these options using a VR device and select the activity that best suits them. For example, experiencing the atmosphere and activities of a gardening club in VR can solidify their desire to participate. Furthermore, users will automatically be notified of the details of their chosen activity and be notified of the necessary participation details.

[1312] This invention allows users to discover more relevant and attractive communities and activities through virtual experiences. Furthermore, by utilizing a generative AI model, it is possible to make recommendations that are optimized for each individual user. This system aims to improve the user experience, which was difficult to achieve with conventional methods.

[1313] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1314] Program processing flow

[1315] Step 1:

[1316] The user accesses a dedicated terminal or web interface and enters their profile data, such as hobbies, interests, skills, and region. The entered data is sent to a temporary database. Input: Hobbies, interests, skills, region Output: User profile data

[1317] Step 2:

[1318] The server receives the profile data entered by the user. The received data undergoes syntax checking and input filtering and is then saved in a temporary database (e.g., SQLite3). Input: User profile data Output: Profile data saved in the database

[1319] Step 3:

[1320] The AI ​​algorithm on the server analyzes the received profile data. At this time, a generative AI model is used to list multiple activity candidates suitable for the user. A prompt statement is sent to the generative AI model to obtain recommended activity candidates. Input: Saved profile data, prompt statement (example: "Based on hobbies: gardening, cooking, travel, skills: photography, and area: Tokyo, please suggest appropriate communities and activities.") Output: Generated list of activity candidates

[1321] Step 4:

[1322] The server sends the generated activity candidate list to the terminal, which then displays it to the user. The user then views detailed information about these activity candidates through a screen or VR device. Input: Activity candidate list Output: Activity candidate details displayed on the user's terminal

[1323] Step 5:

[1324] The user selects an activity that interests them and applies to participate in that activity. The application is sent to the server via the terminal. Input: Activity selected by the user Output: Application to participate

[1325] Step 6:

[1326] The server processes the request and sends notifications to the relevant communities and stakeholders. These notifications include the request and the user's profile data. Input: Request to join. Output: Notifications sent to the relevant communities.

[1327] Step 7:

[1328] The server receives participation approval and detailed information from related communities and stakeholders, and sends it to the user's terminal. The detailed information includes the event schedule, activities, meeting place, etc. Input: Approval and detailed information from related communities Output: Detailed information sent to the user's terminal

[1329] Step 8:

[1330] The user uses a head-mounted display to virtually experience the proposed activity. The virtual experience simulates the atmosphere and content of the actual activity in a VR environment. Input: Detailed information about the proposed activity. Output: VR experience of the virtual activity that the user has virtually experienced.

[1331] Step 9:

[1332] The user finally decides which activities they want to participate in, and the server sends a final notification to the relevant community. Input: User's selection after virtual experience Output: Final notification

[1333] 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.

[1334] This invention relates to a system that matches appropriate communities and activities to users who are looking for new meaning in life after retirement. In particular, by incorporating an emotion engine, this system enables matching that takes into account the user's emotional state. Specifically, it involves a series of processes that exchange data between a server, terminal, and user, and uses AI and the emotion engine to suggest optimal activities and communities.

[1335] System configuration

[1336] 1. The user enters their profile data and emotional data.

[1337] A user accesses a dedicated device or web service and enters profile data such as their hobbies, interests, skills, and location. Furthermore, the emotion recognition system inputs or detects their current emotional state. As a concrete example, consider the case where a user selects gardening, cooking, and travel as hobbies and registers camera photography as a skill, and the emotion engine recognizes the emotion as "relaxed."

[1338] 2. The server receives the data

[1339] The server receives the profile data and emotion data entered by the user and stores them in a temporary database. For example, a user who is relaxed may be suited to a gardening club, which has a stress-reducing effect.

[1340] 3. Data Analysis

[1341] The AI ​​algorithm in the server analyzes the received profile and emotional data. At this stage, it searches the database for activities and communities that take into account the user's current emotional state, along with their hobbies, interests, and skills. For example, a user who is "relaxing" will be presented with activities that have a relaxing effect.

[1342] 4. Generating Matching Candidates

[1343] The server generates multiple activity candidates suitable for the user based on the analysis results of the AI ​​and emotion engine. This process lists activities that match the user's current emotional state. For example, it may include gardening clubs, cooking classes, travel circles, etc. that reflect the user's interests and emotional state.

[1344] 5. Present candidates to the user

[1345] The device presents the matching candidates sent from the server to the user, who is then shown detailed information about the activity, the reason for the recommendation based on the user's emotional state, and the profile of the potential participants.

[1346] 6. User Selection and Participation Application

[1347] The user selects an activity that they are interested in and submits an application to participate in. For example, if the user wants to join a gardening club based on the reasons recommended by the emotion engine, they submit an application to join the club.

[1348] 7. Application Processing and Notification

[1349] The server processes the user's request to join and sends a notification to the organizer of the corresponding community, who then receives the new joiner's information.

[1350] 8. Providing more information

[1351] The terminal notifies the user of participation approval and activity details, including a participation approval message, event details, and meeting place information.

[1352] 9. User Participation

[1353] The user can then participate in actual activities based on the information provided. For example, by participating in the first meeting of a gardening club, the user has the opportunity to find a new purpose in life.

[1354] Through this process, users can easily find new activities and communities that suit them, enabling them to live fulfilling lives. This system is characterized by the efficient exchange of data between the server, device, and user, and by using AI and an emotion engine to perform optimal matching.

[1355] The processing flow will be explained below.

[1356] Step 1:

[1357] The user enters their profile data and emotional data. They fill out information such as hobbies, interests, skills, and location on a dedicated device or a form on a web service, and then press the "Submit" button. The emotion recognition system also detects the user's current emotional state, and this data is also sent. For example, if a user selects "gardening," "cooking," and "travel" as their hobbies and inputs camera photography as a skill, their emotional state is recognized as "relaxed."

[1358] Step 2:

[1359] The server receives the profile data and emotion data sent by the user, converts this data into an analyzable format, and stores it in a temporary database.

[1360] Step 3:

[1361] An AI algorithm in the server analyzes the received profile and emotional data. For example, based on the hobby of "gardening" and the emotional state of "relaxation," it searches a database for relaxing activities related to gardening.

[1362] Step 4:

[1363] The server generates multiple activity suggestions suitable for the user based on the analysis results of the AI ​​algorithm and emotion engine, such as a list of relaxing activities such as gardening clubs, cooking classes, and art therapy.

[1364] Step 5:

[1365] The server transmits the generated activity candidate data to the terminal, where the data is converted to a format suitable for display on the user's display screen.

[1366] Step 6:

[1367] The device displays the matching candidates sent from the server to the user. The user's screen displays detailed information about each activity, the reason for the recommendation (for example, because it is expected to have a relaxing effect), and the profiles of the potential participants.

[1368] Step 7:

[1369] The user selects an activity they are interested in and applies to join. For example, the user clicks the "Apply" button to join the gardening club. This information is sent to the server.

[1370] Step 8:

[1371] The server receives and processes the user's participation application data, checks which community the user has applied to join, and sends a notification to the organizer of the corresponding community.

[1372] Step 9:

[1373] The server sends a notification to the organizer and prepares to provide the user with participation acceptance and activity details, including the participation acceptance message, event details, and meeting place information.

[1374] Step 10:

[1375] The terminal notifies the user of the participation approval and detailed information sent from the server, and the user confirms the activity date, location, belongings, etc. based on this information.

[1376] Step 11:

[1377] The user can then participate in actual activities based on the information provided, for example, attending the first meeting of a gardening club, and gaining the opportunity to find a new purpose in life.

[1378] By following these detailed steps, users can easily find new activities and communities that suit them, and find meaning in their post-retirement lives. By combining it with an emotion engine, matching can be performed taking into account the user's emotional state, resulting in more appropriate activities being selected.

[1379] Example 2

[1380] 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."

[1381] In recent years, an increasing number of elderly people are seeking new meaning in life after retirement. However, it is not easy to find communities and activities that suit their individual interests, skills, and mental state. Conventional systems have difficulty proposing activities that take into account the user's emotional state, and as a result, they often present activities that are not in line with the user's interests. There is a need to solve this problem and propose activities that are optimal for users.

[1382] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving profile data and emotion data input by the user, means for generating a plurality of activity candidates suitable for the user based on the profile data and emotion data, and means for presenting the generated activity candidates to the user. This makes it possible to suggest activities that take into account the user's individual interests, skills, and mental state.

[1383] "Profile Data" refers to personal information about a user, such as their hobbies, interests, skills, and location.

[1384] "Emotion data" refers to information indicative of a user's current emotional state that is collected by an emotion recognition system.

[1385] "Means for receiving" refers to the function or method by which the server receives input data from the user.

[1386] "Means of analysis" refers to the functions and methods by which algorithms and programs within the server analyze the received data and extract useful information from it.

[1387] "Means for generating" refers to a function or method for generating multiple activity candidates suitable for the user based on the analysis results.

[1388] The "means for presenting" refers to a function or method for displaying the generated activity candidates to the user and allowing the user to select one.

[1389] "Means for processing participation requests" refers to the functions and methods for accepting, managing, and processing participation requests for the activities selected by the user.

[1390] "Means for sending notifications" refers to the functions and methods for informing relevant communities or stakeholders based on processed participation applications.

[1391] "Means for providing detailed information" refers to a function or method for informing the user of specific information about the activity (e.g., event dates and meeting places) based on the notification.

[1392] "Suggested Activities" refers to a list of activities and communities that a user can participate in that are suggested based on the user's profile data and emotional data.

[1393] "Database" refers to a system for systematically storing and managing information such as profile data, emotional data, analysis results, and potential activities.

[1394] "AI Algorithm" refers to the artificial intelligence technology used to analyze user data and generate optimal activity suggestions.

[1395] An "emotion recognition system" refers to technology that uses sensors such as cameras and microphones to recognize a user's current emotional state.

[1396] This invention relates to a system that matches appropriate communities and activities to users who are looking for a new purpose in life after retirement. By combining this system with an emotion engine, it enables matching that takes into account the user's emotional state, and it exchanges data between the server, terminal, and user, and uses AI and the emotion engine to suggest optimal activities and communities.

[1397] System configuration

[1398] 1. The user enters their profile data and emotional data.

[1399] Users access a dedicated device or web service and enter profile data such as hobbies, interests, skills, and region. An emotion recognition system using a camera and microphone also inputs or detects the user's current emotional state. For example, a scenario is envisioned in which a user selects "gardening," "cooking," and "travel" as hobbies and registers "photography" as a skill, and the emotion recognition system recognizes the emotion as "relaxed."

[1400] 2. The server receives the data

[1401] The server receives profile and emotion data from users via API and stores it in a temporary database. For example, a user who is relaxing might be suited to a "gardening club" that has a stress-reducing effect.

[1402] 3. Data Analysis

[1403] The AI ​​algorithms on the server analyze the received profile data and emotional data. This analysis involves taking into account the user's hobbies, interests, skills, and emotional state, and searching the database for the most suitable activities and communities. For example, if a user is "relaxing," activities that have a relaxing effect will be presented.

[1404] 4. Generating Matching Candidates

[1405] The server generates multiple activity candidates suitable for the user based on the analysis results of the AI ​​and emotion engine. This process lists activities that match the user's current emotional state. Possible activities include "gardening club," "cooking class," and "travel circle," reflecting the user's interests and emotional state.

[1406] 5. Present candidates to the user

[1407] The activity suggestions generated by the server are sent to the terminal and presented to the user on the terminal, where detailed information about the activity, the reason for the recommendation based on the user's emotional state, and the profiles of the potential participants are displayed.

[1408] 6. User Selection and Participation Application

[1409] The user selects an activity they are interested in and submits an application to participate. For example, if the user wishes to join the "gardening club" based on the reasons recommended by the emotion engine, they press the application button to express their intention to participate.

[1410] 7. Application Processing and Notification

[1411] The server processes the user's request to join and sends a notification to the relevant community organizer, who receives the notification and confirms the new member.

[1412] 8. Providing more information

[1413] The terminal notifies the user of the participation acceptance and activity details, including the participation acceptance message, the event schedule, and the meeting place information.

[1414] 9. User Participation

[1415] Users can then take part in real activities based on the information they receive, for example attending the first meeting of a "gardening club" and finding meaning in life through new experiences.

[1416] Examples of specific examples and prompts

[1417] Examples:

[1418] User A selects "gardening," "cooking," and "travel" as hobbies and registers "photography" as a skill on a dedicated device. Based on the emotional state recognized as "relaxed," he / she wishes to join the gardening club.

[1419] Example prompt sentence:

[1420] "If a user has hobbies like gardening, cooking, and traveling, and a skill like photography, and is currently relaxing, please suggest which communities and activities would be suitable. Then, please show the process flow for choosing the best activity and completing the user's participation process."

[1421] The above system allows users to easily find activities and communities that are best suited to them and discover new meaning in life.

[1422] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1423] Step 1:

[1424] The user accesses a dedicated device or web service and enters profile data such as their hobbies, interests, skills, and region into a form. The emotion recognition system then uses a camera and microphone to analyze their current emotions. Specifically, the user selects "gardening" or "cooking" as their hobbies, and the emotion recognition system recognizes the emotion as "relaxation." Inputs include the user's hobbies, interests, skills, and emotional data. This data is then sent to the server via an API.

[1425] Step 2:

[1426] The server receives profile data and emotion data and stores it in a temporary database. The input data includes the hobbies, interests, skills, and emotion data entered by the user. The output is the data stored in the temporary database. The specific operation is to store the received data in the corresponding database table.

[1427] Step 3:

[1428] The AI ​​algorithm in the server analyzes the stored data. The input data includes the user's profile data and emotional data stored on the server. The AI ​​algorithm combines hobbies, interests, skills, and emotional state to search the database for the most suitable activities and communities. The output is a list of suitable activity candidates as a result of the analysis. Specifically, the AI ​​model inputs the data and calculates a matching score.

[1429] Step 4:

[1430] The server generates multiple candidate activities suitable for the user based on the analysis results of the AI ​​and emotion engine. The input data includes the analysis results of the AI ​​algorithm. The output is a list of the candidate activities generated. Specifically, it lists and selects activities that match the user's current emotional state.

[1431] Step 5:

[1432] The server sends the generated activity candidates to the terminal. The input data includes a list of the generated activity candidates. The output is notification information sent to the terminal. Specifically, the system sends the activity candidates to the user terminal in real time via the user interface.

[1433] Step 6:

[1434] The terminal presents the transmitted activity candidates to the user. The input data includes the list of activity candidates transmitted from the server. The output is the candidate list displayed on the user's screen. Specifically, the screen display logic is used to visually present the user with detailed information about the activity, the reason for the recommendation based on the user's emotional state, and profile information about the potential participants.

[1435] Step 7:

[1436] The user selects an activity they are interested in and submits an application to participate. The input data includes the activity the user selected and the reason for their selection. The output is a form in which the application information is sent to the server. The specific operation is to press the participation application button and the information is sent to the server.

[1437] Step 8:

[1438] The server processes user participation requests. Input data includes participation request information from users. Output includes the status of the processed request. Specific operations include receiving the request information, updating it in the database, and managing the status.

[1439] Step 9:

[1440] The server sends a notification to the organizer of the relevant community. The input data includes the user's participation application information. The output is a notification message to the organizer. Specifically, the server obtains the organizer's contact information and sends the notification message.

[1441] Step 10:

[1442] The terminal notifies the user of participation approval and activity details. Input data includes the approval information and details sent from the server. The output is a notification message displayed on the user's screen. Specific operations include displaying the participation approval message, event schedule, and meeting place information to the user.

[1443] Step 11:

[1444] The user participates in the actual activity based on the notified information. The input data includes the notified activity details. The output is a record of the user's actual activity participation. The specific operation is for the user to go to the notified meeting place and participate in the activity.

[1445] (Application example 2)

[1446] 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."

[1447] In order for elderly people to find new meaning in life after retirement, they need to find appropriate activities and communities that take into account not only their hobbies and interests but also their current emotional state. However, existing matching systems do not take these emotional factors into account, making it difficult for users to find activities and communities that truly satisfy them.

[1448] 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 means for receiving profile data and emotion data input by the user, means for generating a plurality of activity candidates suitable for the user based on the profile data and emotion data, and means for presenting the generated activity candidates to the user. This makes it possible to suggest appropriate activities and communities that take into account not only the user's hobbies and interests but also their emotional state.

[1449] "Profile data" refers to basic information such as hobbies, interests, skills, and location that users enter themselves.

[1450] "Emotion data" refers to information that represents the user's current emotional state and is detected by an emotion recognition system.

[1451] "Activity candidates" refers to a list of multiple candidate activities and communities suitable for a user, generated based on the user's profile data and emotion data.

[1452] "Means for generating" refers to methods or techniques for analyzing user input data and listing appropriate activity candidates based on that data.

[1453] The "presentation means" refers to a method or technique for visually or audibly displaying the generated activity candidates to the user.

[1454] "Participation application" refers to the application procedure a user goes through to participate in an activity or community that interests them.

[1455] "Means for sending notifications" refers to the methods and techniques for sending notifications to relevant groups or parties based on a user's participation request.

[1456] "Means for providing detailed information" refers to methods and techniques for providing detailed information about activities and events to users.

[1457] This invention provides a system for helping retired people find new meaning in life, including an application installed on a smartphone or head-mounted display (HMD).

[1458] System configuration

[1459] 1. Entering user profile and emotion data

[1460] Users access the application using their smartphone or HMD and enter their profile data, which includes information such as hobbies, interests, skills, and location.

[1461] Furthermore, users input their current emotional state through images or videos, and emotion data is automatically detected using an emotion recognition system (e.g., emotion_engine library).

[1462] 2. Receipt and storage of data

[1463] The server receives the profile data and emotion data entered by the user and stores them in a database.

[1464] 3. Data analysis and activity candidate generation

[1465] The server's AI matching algorithm (e.g., the ai_matcher library) analyzes the received profile and emotional data to generate optimal activity and community suggestions, taking into account the user's hobbies and skills as well as their current emotional state.

[1466] 4. Suggested activities

[1467] The generated activity candidates are presented to the user on their smartphone or HMD, and the user selects the activity that interests them.

[1468] 5. Application and Notification

[1469] Based on the activity selected by the user, a participation request is sent to the server and notifications are sent to relevant communities and stakeholders.

[1470] The notification includes the user's profile information and details of the selected activity, allowing community organizers to receive new participant information.

[1471] 6. Providing more information

[1472] Users will be provided with activity details based on the notification, including details such as the date, time, and location of the activity, as well as any precautions.

[1473] Specific processing examples

[1474] For example, if a user lists gardening as a hobby and the emotion engine detects that they find it relaxing, the system will suggest gardening-related activities and communities, such as nearby gardening clubs or online workshops.

[1475] Prompt Sentence Examples

[1476] If a user has a particular hobby (gardening) and is detected as relaxed by an emotion recognition system, suggest an appropriate virtual activity. Include details about the activity you are suggesting and the reason for suggesting it.

[1477] In this way, it becomes possible to help users find appropriate activities and communities based on their profile data and emotional data, allowing them to find new meaning in life and live a fulfilling life.

[1478] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1479] Step 1:

[1480] Users access the application using a smartphone or head-mounted display (HMD) and enter their profile data. The profile data includes information such as hobbies, interests, skills, and location. The entered data is sent to the system's database and stored. The input of this step is the user's profile data, and the output is the profile data stored in the database.

[1481] Step 2:

[1482] The user inputs emotional data using a camera. The emotional data is captured in real time from images or videos and analyzed by an emotion recognition system (e.g., emotion_engine). As a result of the analysis, the user's current emotional state is detected and sent to the system and stored in a database. The input of this step is the user's image or video, and the output is the analyzed emotional data.

[1483] Step 3:

[1484] The server receives the profile data and emotion data stored in the database and analyzes them using an AI matching algorithm (e.g., ai_matcher). This analysis includes the user's hobbies, skills, and current emotional state. Based on this, activity candidates suitable for the user are generated. The input of this step is the profile data and emotion data, and the output is the generated activity candidates.

[1485] Step 4:

[1486] The server sends the generated activity candidates to the user's smartphone or HMD for presentation. The user checks the detailed information of the activity candidates displayed on the screen and selects the activity of interest. The input of this step is the generated activity candidates, and the output is the user's selected activity.

[1487] Step 5:

[1488] Based on the user's selected activity, a request to join is made. The request is sent to the server, which processes it and sends a notification to relevant communities and stakeholders. The notification contains the user's profile information and details of the selected activity. The input of this step is the user's request to join, and the output is the notification sent.

[1489] Step 6:

[1490] The server provides the user with detailed information about the activity based on the notification. This information includes the date, time, location, and important notes of the activity. Based on the information notified, the user participates in the actual activity or event. The input of this step is the detailed information based on the notification, and the output is the detailed information of the activity provided to the user.

[1491] Through these steps, users can find the most suitable activities and communities based on their emotional state and profile data, and discover new meanings in life, which is expected to improve the quality of their lives.

[1492] 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.

[1493] 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.

[1494] 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.

[1495] 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.

[1496] 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.

[1497] 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.

[1498] 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).

[1499] 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.

[1500] 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."

[1501] 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.

[1502] 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).

[1503] 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.

[1504] 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.

[1505] 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.

[1506] 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.

[1507] 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.

[1508] 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.

[1509] 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.

[1510] 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.

[1511] 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.

[1512] 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.

[1513] The following is further disclosed regarding the above embodiment.

[1514] (Claim 1)

[1515] means for receiving profile data entered by a user;

[1516] means for generating a plurality of candidate activities suitable for the user based on the profile data;

[1517] means for presenting the generated activity candidates to a user;

[1518] means for processing requests to participate in an activity based on the activity selected by the user;

[1519] means for sending notifications to relevant communities or stakeholders based on processed participation applications;

[1520] means for providing detailed information about the activity to the user based on the notification;

[1521] A system including:

[1522] (Claim 2)

[1523] 10. The system of claim 1, further comprising means for analyzing profile data entered by a user.

[1524] (Claim 3)

[1525] 10. The system of claim 1, further comprising means for generating suggested activities based on the profile data and past user behavior data.

[1526] "Example 1"

[1527] (Claim 1)

[1528] means for receiving profile data entered by a user;

[1529] means for analyzing the profile data;

[1530] means for generating a plurality of candidate activities suitable for the user based on the analysis results;

[1531] means for presenting the generated activity candidates to a user;

[1532] means for processing requests to participate in an activity based on the activity selected by the user;

[1533] means for sending notifications to relevant communities or stakeholders based on processed participation applications;

[1534] means for providing detailed information about the activity to the user based on the notification;

[1535] A system including:

[1536] (Claim 2)

[1537] 10. The system of claim 1, further comprising means for analyzing said profile data using an AI algorithm.

[1538] (Claim 3)

[1539] 10. The system of claim 1, further comprising means for generating suggested activities based on the profile data and past user behavior data.

[1540] "Application Example 1"

[1541] New Claims

[1542] (Claim 1)

[1543] means for receiving profile data entered by a user;

[1544] means for generating a plurality of candidate activities suitable for the user based on the profile data;

[1545] means for presenting the generated activity candidates to a user;

[1546] means for processing requests to participate in an activity based on the activity selected by the user;

[1547] means for sending notifications to relevant communities or stakeholders based on processed participation applications;

[1548] means for providing detailed information about the activity to the user based on the notification;

[1549] a means for suggesting suggested activities based on a user profile using a generative AI model;

[1550] a means for the user to virtually experience the proposed activity using a virtual reality device;

[1551] A system including:

[1552] (Claim 2)

[1553] 10. The system of claim 1, further comprising means for analyzing profile data entered by a user.

[1554] (Claim 3)

[1555] 10. The system of claim 1, further comprising means for generating suggested activities based on the profile data and past user behavior data.

[1556] "Example 2: Combining Emotion Engines"

[1557] (Claim 1)

[1558] means for receiving profile data and emotion data input by a user;

[1559] means for generating a plurality of candidate activities suitable for the user based on the profile data and emotion data;

[1560] means for presenting the generated activity candidates to a user;

[1561] means for processing requests to participate in an activity based on the activity selected by the user;

[1562] means for sending notifications to relevant communities or stakeholders based on processed participation applications;

[1563] means for providing detailed information about the activity to the user based on the notification;

[1564] A system including:

[1565] (Claim 2)

[1566] 10. The system of claim 1, further comprising means for analyzing profile data and emotion data entered by a user.

[1567] (Claim 3)

[1568] 10. The system of claim 1, further comprising means for generating activity candidates based on the profile data and emotion data and past user behavior data.

[1569] "Application example 2 when combining emotion engines"

[1570] (Claim 1)

[1571] means for receiving profile data and emotion data input by a user;

[1572] means for generating a plurality of candidate activities suitable for the user based on the profile data and emotion data;

[1573] means for presenting the generated activity candidates to a user;

[1574] means for processing requests to participate in an activity based on the activity selected by the user;

[1575] a means for sending notifications to relevant classes or parties based on processed participation applications;

[1576] means for providing detailed information about the activity to the user based on the notification;

[1577] A system including:

[1578] (Claim 2)

[1579] 10. The system of claim 1, further comprising means for analyzing profile data and emotion data entered by a user.

[1580] (Claim 3)

[1581] 10. The system of claim 1, further comprising means for generating activity suggestions based on the profile data and emotion data and past user behavior data. [Explanation of symbols]

[1582] 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. means for receiving profile data entered by a user; means for generating a plurality of candidate activities suitable for the user based on the profile data; means for presenting the generated activity candidates to a user; means for processing requests to participate in an activity based on the activity selected by the user; means for sending notifications to relevant communities or stakeholders based on processed participation applications; means for providing detailed information about the activity to the user based on the notification; A system including:

2. 10. The system of claim 1, further comprising means for analyzing profile data entered by a user.

3. The system of claim 1 , further comprising means for generating suggested activities based on the profile data and past user behavior data.

Images