System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting profile information of a non-married person; means for storing the profile information in a database; means for analyzing historical activity data stored in the database to identify user interests; means for suggesting an encounter opportunity based on the analysis; and means for sending the suggested encounter opportunity in a push 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] In modern society, declining birth rates and population decline are serious problems. In order to solve this problem, it is essential to increase the marriage rate. However, many current policies and measures focus on listening to the concerns of families after marriage, and there is a lack of support before marriage, so they are not able to effectively address the declining marriage rate. For this reason, a system is needed to strengthen support for unmarried men and women leading up to marriage and to support effective unions. [Means for solving the problem]

[0005] The present invention provides a system including a means for inputting profile information of unmarried people, a means for saving the profile information in a database, a means for analyzing the behavioral history data saved in the database and identifying the user's interests, a means for proposing dating opportunities based on the analysis results, and a means for sending the proposed dating opportunities via push notification. The system also includes a means for extracting unmarried people who share common hobbies and interests, proposing joint activities to the extracted unmarried people, and sending the joint activities via push notification. The system also includes a means for generating a future forecast based on the user's interest and behavioral data, saving the generated future forecast in a database, and presenting the saved future forecast to the user. This can strengthen support before marriage and improve the marriage rate.

[0006] "Profile Information" refers to personal information such as a user's name, age, gender, hobbies, and interests.

[0007] "Database" refers to a system or platform for storing and managing user profile information and behavioral history data.

[0008] "Behavioral history data" refers to records of various actions taken by users within the app (such as reading articles, participating in events, chatting with friends, etc.).

[0009] "Analysis" refers to the process of extracting useful information from a collection of data and identifying user interests and behavioral patterns.

[0010] "Meeting opportunities" refers to events and activities where unmarried people can naturally interact with each other through common hobbies and interests.

[0011] "Push Notification" means an automated notification message sent from a server to a user's device.

[0012] "Common hobbies and interests" refers to activities and areas of interest shared by unmarried people.

[0013] "Joint activities" refer to specific events or activities that unmarried people with common hobbies or interests undertake together.

[0014] "Future Vision" refers to a concrete image of future life and married life generated from the user's interests and behavioral data.

[0015] "Generative AI" refers to artificial intelligence that performs complex calculations such as data analysis and generating future projections. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10]1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

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

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] This invention is a system that provides various support to unmarried people until they get married. This system uses generative AI to analyze the user's interests and behavioral history, and provides "opportunities to meet people," "unforgettable memories," and "future visions" necessary for marriage. This system consists of three main parts: a server, a terminal, and a user.

[0038] Program processing

[0039] 1. User Registration

[0040] Describe the process by which a user enters profile information:

[0041] Users download the app and install it on their devices.

[0042] Users enter profile information such as their name, age, gender, hobbies, and interests into the device.

[0043] The terminal sends the input data to the server, which stores the information in a database.

[0044] 2. Data Collection and Analysis

[0045] Explain the process for collecting and analyzing user behavior data:

[0046] Within the app, users can read articles, attend events, and chat with friends.

[0047] The terminal transmits this behavior history data to the server.

[0048] The server successively stores and updates the collected behavioral history data in a database.

[0049] The generative AI analyzes behavioral history data and identifies the user's interests and behavioral patterns.

[0050] 3. Providing opportunities for encounters

[0051] Explain the process we use to find the right matchmaking opportunities for you:

[0052] Based on the analysis results of the generative AI, the server selects the most suitable meeting opportunities for the user (for example, events that share similar hobbies or activities that share common interests).

[0053] The server generates specific suggestions for dating opportunities and creates the body of the push notification.

[0054] The device will send a push notification to the user, who will then participate in the suggested event or activity based on the suggestions received.

[0055] 4. Providing a memorable experience

[0056] Describe the process for delivering experiences to users who share common hobbies and interests:

[0057] The server extracts unmarried people who share common hobbies and interests.

[0058] Based on the extracted information between users, the generation AI generates suggestions for joint activities (e.g., cooking classes, camping).

[0059] The server creates the push notification content, and the device sends the push notification to the user.

[0060] Users can participate in the suggested activities and create unforgettable memories through the experience.

[0061] 5. Proposal of a vision for the future

[0062] Describe the process to help users visualize their future life:

[0063] Generative AI generates a future vision (suggestions for newlywed life and relocation destinations) based on the user's interests and behavioral data.

[0064] The server stores the generated future projections in a database.

[0065] The device will present the user with the saved future vision in video and text format.

[0066] Users can use the presented future projections as a reference to imagine and consider their own specific vision of the future.

[0067] As a concrete example, consider a case where a user's hobby is "music." The system analyzes the user's past behavioral history and suggests local music festivals. It also suggests music workshops that users can participate in together with other users who share the same hobby, and suggests future plans for the user to move to a region with a strong music scene.

[0068] In this way, this system aims to improve marriage rates by analyzing users' profile information and behavioral history data and providing various types of support leading up to marriage.

[0069] The processing flow will be explained below.

[0070] Step 1:

[0071] User enters profile information:

[0072] Users download and install the app on their device, and then enter their profile information, such as their name, age, gender, hobbies, and interests, through the device.

[0073] Step 2:

[0074] The device sends the input data to the server:

[0075] The terminal transmits the input profile information to the server, and the server receives the input data.

[0076] Step 3:

[0077] The server stores the profile information in a database:

[0078] The server stores the received profile information in a database.

[0079] Step 4:

[0080] User takes action in the app:

[0081] Within the app, users can read articles, attend events, and chat with friends.

[0082] Step 5:

[0083] The device sends the activity history to the server:

[0084] User activity data (e.g., which articles you read, which events you attended, which users you chatted with) is sent from your device to a server.

[0085] Step 6:

[0086] The server collects and updates the behavioral history data:

[0087] The server sequentially stores and updates the collected behavioral history data in a database.

[0088] Step 7:

[0089] Generative AI analyzes historical behavioral data:

[0090] The generation AI on the server analyzes the stored behavioral history data and identifies the user's interests and behavioral patterns.

[0091] Step 8:

[0092] The server selects the opportunities and creates suggestions:

[0093] Based on the analysis results of the generation AI, the server selects meeting opportunities to suggest (for example, hobby-based events or activities) and generates the suggestions.

[0094] Step 9:

[0095] The server creates the push notification:

[0096] Create the body of the push notification to the user based on the suggestions generated by the server.

[0097] Step 10:

[0098] The device sends a push notification to the user:

[0099] The device sends the push notification created by the server to the user.

[0100] Step 11:

[0101] The user participates in a suggested dating opportunity:

[0102] Users receive push notifications and act on suggested events and activities.

[0103] Step 12:

[0104] The server extracts users with common hobbies and interests:

[0105] The server extracts users with common hobbies and interests from the database.

[0106] Step 13:

[0107] Generative AI suggests collaborative activities:

[0108] Based on the extracted information between users, the generative AI generates suggestions for joint activities (e.g., cooking classes or camping).

[0109] Step 14:

[0110] The server creates a push notification for the collaboration:

[0111] The server creates the text of the push notification for the collaborative activity based on the suggestions made by the generated AI.

[0112] Step 15:

[0113] The device sends a push notification to the user:

[0114] The device sends a push notification of the collaborative activity created by the server to the user.

[0115] Step 16:

[0116] The user participates in a proposed collaborative activity:

[0117] The user receives a push notification and acts on the suggested collaborative activity.

[0118] Step 17:

[0119] Generative AI creates a vision of the future:

[0120] The server's on-board AI generates a future vision (suggestions for newlywed life and relocation destinations) based on the user's interests and behavioral data.

[0121] Step 18:

[0122] The server saves the generated future view:

[0123] The server stores the generated future projections in a database.

[0124] Step 19:

[0125] The device presents the user with a vision of the future:

[0126] The device presents the future vision stored on the server to the user in the form of video and text.

[0127] Step 20:

[0128] Users consider the future:

[0129] Users use the future projections presented to them as a reference to imagine and consider their own specific future.

[0130] Example 1

[0131] 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."

[0132] In the process of getting married, unmarried people face challenges in finding suitable opportunities to meet people, engaging in joint activities, and having a concrete image of their future life. These challenges make it difficult for unmarried people to find a suitable partner based on their own interests and behavioral patterns, leading to a decline in the marriage rate. The present invention aims to solve these challenges and provide effective support to unmarried people.

[0133] 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.

[0134] In this invention, the server includes means for inputting personal information of unmarried people, means for saving the personal information in a storage device, means for analyzing the activity history data saved in the storage device and using a generative artificial intelligence model to identify the user's interests, means for using the generative artificial intelligence model to suggest meeting opportunities based on the analysis results, and means for sending the suggested meeting opportunities via a notification function. This enables unmarried people to receive suggestions for meeting opportunities and joint activities that match their interests and behavioral patterns, and is expected to improve the marriage rate.

[0135] "Single person" refers to an individual who is not married.

[0136] "Personal information" refers to information that identifies and distinguishes an individual, such as name, age, gender, hobbies, and interests.

[0137] "Storage" refers to a hardware device or electronic storage medium that can store data and retrieve it as needed.

[0138] "Activity history data" refers to data about behavior generated while a user uses the app, such as reading articles, attending events, and chatting.

[0139] A "generative artificial intelligence model" refers to an artificial intelligence technology model that performs analysis based on input data and generates output appropriate for the next action.

[0140] "Interests" refer to specific activities or information that a user is interested in or concerned about.

[0141] "Meeting opportunities" refers to events, activities, and other venues where unmarried people can interact with each other and build relationships.

[0142] "Notification Function" refers to a technical means for transmitting information to a recipient in real time, including push notifications.

[0143] This system uses a generative AI model to support unmarried people until they reach marriage. It consists of three main components: a server, a terminal, and a user.

[0144] First, the user downloads and installs the application onto their device. After installation, the user enters profile information such as name, age, gender, hobbies, and interests. This information is sent from the user device to the server, where it is stored in a database.

[0145] Next, behavioral history data is collected as users read articles, attend events, and chat with friends within the app. This data is also sent from the user's device to the server, which stores it in a database and keeps it up to date. Within the server, a generative AI model analyzes this data and processes it to identify the user's interests and behavioral patterns.

[0146] Based on the analysis results, the generative AI model generates information to suggest optimal meeting opportunities to the user. For example, if the user's hobby is music, the model will suggest information about local music festivals and music workshops. The generated suggestions are converted into push notifications on the server and sent to the user's device. Users who receive the notifications can participate in events and activities based on the suggestions.

[0147] Furthermore, the system will select unmarried people who share common hobbies and interests and suggest joint activities to those users. For example, if one of their hobbies is cooking, it will suggest that they join a cooking class. The details of the proposed joint activities will also be sent to the user via push notification.

[0148] Furthermore, to help users visualize their future lives in concrete terms, the generative AI model generates a future vision based on the user's interests and behavioral data. For example, for a user whose hobby is music, the model will create a vision of moving to a music-loving region or newlywed life. The generated future vision is saved on the server and presented in video or text format on the user's device. This allows users to realistically imagine their future and consider it in detail.

[0149] Examples of prompts include:

[0150] "Based on the user's profile information and behavioral data, suggest events that match their hobbies and interests."

[0151] "Please create opportunities for users with common interests to meet and express them as concrete proposals."

[0152] "Create a vision of the future that interests users and generate explanatory text to present it in video or text format."

[0153] As described above, this system utilizes generative AI models and various analytical technologies to provide various types of support to unmarried people, enabling them to obtain optimal dating opportunities and visions for the future based on their interests and behavioral patterns, and supporting them in the process of getting married.

[0154] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0155] Step 1:

[0156] A user downloads an app and installs it on their device. The input is the application download link and the output is the installed application. A user searches for an app in the App Store or Google Play and clicks the download button to install it.

[0157] Step 2:

[0158] The user opens the app and enters personal information such as name, age, gender, hobbies, and interests. The input is the personal information the user entered into the form, and the output is the personal information temporarily stored on the device. The user enters data into each field in the form displayed on the app's registration screen.

[0159] Step 3:

[0160] The device sends the entered personal information to the server. The input is the personal information entered by the user, and the output is the data sent to the server. When the device completes the input form and presses the send button, the data is encrypted and sent to the server.

[0161] Step 4:

[0162] The server stores the received data in a database. The input is the personal information sent from the terminal, and the output is the personal information stored in the database. The server analyzes the received data and stores it in the appropriate field.

[0163] Step 5:

[0164] When a user reads an article, attends an event, or chats with friends within an app, the input is the user's activity and the output is behavioral history data. As the user uses various functions within the app, that behavioral data is automatically collected.

[0165] Step 6:

[0166] The terminal sends the collected behavioral history data to the server. The input is the user's behavioral history data, and the output is the data sent to the server. At regular intervals, the terminal sends the data to the server using batch processing.

[0167] Step 7:

[0168] The server saves the collected behavioral history data in a database and updates it. The input is the behavioral history data sent from the device, and the output is the updated database. The server adds the new data to the database and updates the links and indexes.

[0169] Step 8:

[0170] The generative AI model analyzes behavioral history data and identifies the user's interests and behavioral patterns. The input is behavioral history data, and the output is the analysis results. The generative AI model uses a machine learning algorithm to cluster the data and extract features.

[0171] Step 9:

[0172] The server selects the best meeting opportunities for the user based on the analysis results of the generated AI model. The input is the analysis results, and the output is the selection results of meeting opportunities. The server filters matching events from the event database.

[0173] Step 10:

[0174] The server generates specific matchmaking suggestions and creates the push notification body. The input is the matchmaking selection results, and the output is the push notification body. Templates are used to generate and customize the notification message.

[0175] Step 11:

[0176] The device sends a push notification to the user. The input is the push notification body, and the output is the notification received by the user device. The backend notification server sends the real-time notification to the user device.

[0177] Step 12:

[0178] The server extracts singles who share common hobbies and interests. The input is interest data, and the output is a list of users who share common hobbies. A database query is used to list users who share common tags.

[0179] Step 13:

[0180] The generative AI model generates specific suggestions for joint activities based on the extracted information between users. The input is a list of users with common interests, and the output is suggestions for joint activities. Multiple options are generated based on the user's interests.

[0181] Step 14:

[0182] The server generates collaborative activity suggestions and creates a push notification. The input is the collaborative activity suggestions and the output is the push notification body. A personalized notification is created based on the suggestions.

[0183] Step 15:

[0184] The device sends a push notification to the user. The input is the push notification body, and the output is the notification received by the user device. The notification server sends the notification to the user device in real time.

[0185] Step 16:

[0186] The generative AI model generates a future forecast based on user interest and behavioral data. The input is interest data and behavioral history data, and the output is a future forecast. Scenarios are depicted using simulation models and past data.

[0187] Step 17:

[0188] The server saves the generated future projections in a database. The input is the future projections, and the output is the future projections saved in the database. A future projection customized for each user is saved.

[0189] Step 18:

[0190] The device presents the saved future vision to the user in the form of video or text. The input is the future vision stored in the database, and the output is the content presented to the user. Create a section within the app to display the content of the future vision.

[0191] (Application example 1)

[0192] 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."

[0193] While there are existing systems that provide various support to unmarried people leading up to marriage, there are no systems that promote opportunities for meeting people while traveling in self-driving vehicles. Furthermore, there is a lack of appropriate matching and suggestions for joint activities that utilize users' travel routes and ride-sharing history, as well as a means to concretely visualize their future lives. This makes it difficult for unmarried people to efficiently find opportunities to meet people while traveling.

[0194] 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.

[0195] In this invention, the server includes means for inputting profile information of unmarried people, means for saving the profile information in a database, means for analyzing behavioral history data saved in the database and identifying user interests, means for suggesting meeting opportunities based on the analysis results, means for sending the suggested meeting opportunities by push notification, means for collecting travel routes and ride-sharing histories of autonomous vehicles, means for saving and analyzing the travel routes and ride-sharing histories in a database, and means for matching users heading in the same direction based on the analysis results and sending the results by push notification. This enables unmarried people to efficiently find meeting opportunities while traveling in autonomous vehicles.

[0196] "Profile Information" is personal information about a user, such as their name, age, gender, hobbies, and interests.

[0197] A "database" is a system for organizing, storing, and managing collected information.

[0198] "Behavioral history data" is a record of a user's past activities and behaviors.

[0199] "Analysis" is the process of examining collected data in detail and finding meaning.

[0200] "Interests" refers to the range of interests or concerns a user has about a particular subject.

[0201] "Meeting Opportunities" are situations or events where users can meet new people.

[0202] "Push Notification" means a notification sent to a User's Device in real time.

[0203] An "autonomous vehicle" is a vehicle that operates automatically without a human driver.

[0204] A "travel route" is the route a vehicle takes.

[0205] "Ride-sharing history" is a record of ride-sharing services a user has used in the past.

[0206] "Matching" is the process of connecting users with common interests and goals.

[0207] A "collaborative activity" is an event or activity in which multiple users participate together.

[0208] A "future vision" is a visual or written suggestion that helps users visualize their future life and activities.

[0209] This invention is a matching system for singles that operates inside an autonomous vehicle. The system is designed to enable singles to efficiently enjoy opportunities to meet people while traveling. The system consists of three main parts: a server, a terminal (display or smartphone of the autonomous vehicle), and a user.

[0210] User Registration

[0211] The server provides a means for users to install the application and enter profile information (such as name, age, gender, hobbies, interests, etc.). The profile information entered by the user is sent to the server via the device and stored in a database. This allows the server to centrally manage individual user information.

[0212] Data collection and analysis

[0213] The server collects the autonomous vehicle's route and ride-sharing history data and stores it in a database. Based on this, the generative AI model analyzes the data and identifies the user's behavioral patterns and interests. Specifically, it analyzes the user's past route and ride-sharing history to understand their behavioral trends. For example, if a user frequently participates in a particular event, that tendency can be analyzed and used to suggest encounters.

[0214] Providing opportunities to meet people

[0215] The server then proposes optimal meeting opportunities to users based on the analysis results of the generation AI. In particular, it matches users heading in the same direction to provide meeting opportunities while traveling in an autonomous vehicle. At this time, the server generates a push notification and sends it to the device. The user can view and participate in the proposed meeting opportunities through their device.

[0216] Specific examples

[0217] When users A and B are traveling long distances to the same area, they discover that they have a common hobby (e.g., music festivals) and suggest an opportunity for them to attend the event together while traveling.

[0218] Providing a memorable experience

[0219] The server extracts singles with common hobbies and interests and generates suggestions for joint activities (e.g., cooking classes, camping) that can be participated in while traveling. These suggestions are automatically generated using AI and sent to users via push notifications on their devices. By participating in the suggested joint activities, users can easily share unforgettable experiences.

[0220] Proposal for a vision of the future

[0221] The server generates a future vision based on the user's interests and behavioral data. For example, generative AI is used to generate specific future images, such as suggestions for newlywed life or where to move. This future vision is stored in a database and presented to the user in video or text format via their device. This allows the user to concretely imagine their future life and make easier plans.

[0222] Prompt Sentence Examples

[0223] “The user is looking to meet someone while traveling long distances. Please suggest attractions and events for the near future. The prompt given to the AI ​​generator is, ‘Please suggest events that the user can enjoy during their trip that share their interests.’”

[0224] This system will enable singles to efficiently find opportunities to meet people while traveling in an autonomous vehicle, and will also provide them with memorable experiences and support in concretely imagining their future lives.

[0225] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0226] Step 1:

[0227] The user enters profile information (such as name, age, gender, hobbies, and interests) into a device (such as a smartphone or the display of an autonomous vehicle). The entered profile information is sent from the device to a server, which receives it and stores it in a database.

[0228] Step 2:

[0229] The user starts traveling in the autonomous vehicle using the application. The terminal collects the vehicle's route and ride-sharing history data in real time and transmits it to the server, which receives it and stores it in a database.

[0230] Step 3:

[0231] The server inputs the behavioral history data stored in the database into the generative AI model to analyze the user's interests. The generative AI model identifies behavioral patterns and hobbies and preferences and outputs the results to the server.

[0232] Step 4:

[0233] The server uses the results of the generative AI model's analysis to suggest optimal meeting opportunities for the user, using an algorithm to determine whether a match with another user heading in the same direction is possible. As a result, an appropriate match is made (e.g., joint attendance at a music festival).

[0234] Step 5:

[0235] The server generates a proposed matchmaking opportunity and sends it as a push notification to the device, which receives the notification and displays it to the user, who then reviews the notification and decides whether to participate in the proposed matchmaking opportunity.

[0236] Step 6:

[0237] The server extracts users with common hobbies and interests and suggests activities they can participate in together (e.g., cooking classes or camping). These suggestions are also automatically generated using a generative AI model and sent to the device as a push notification from the server. The device displays the notification to the user, who then decides whether or not to participate in the activity.

[0238] Step 7:

[0239] The server generates a future vision based on the user's interests and behavioral data and stores it in a database. The generated future vision is presented to the user via their device in the form of video or text. The device displays content that allows the user to concretely imagine what life will be like in the future.

[0240] Step 8:

[0241] To help users visualize their future lives, the generative AI model receives specific prompts, such as "Please suggest events that users can enjoy during their trip that involve common hobbies," and the model receives appropriate output.

[0242] Through these steps, the system will enable singles to efficiently find opportunities to meet people while traveling in an autonomous vehicle, and will also provide them with memorable experiences and support in concretely imagining their future lives.

[0243] 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.

[0244] This invention is a system that provides various support to unmarried people leading up to marriage, and in particular, it is a system that combines an emotion engine that recognizes the user's emotions. This system uses generative AI to analyze the user's interests and behavioral history, and further analyzes the user's emotional data using an emotion engine, to provide more appropriate "opportunities to meet," "unforgettable memories," and "future visions." This system consists of three main parts: a server, a terminal, and the user.

[0245] Program processing

[0246] 1. User Registration

[0247] Describe the process by which a user enters profile information:

[0248] Users download and install the app on their devices, then enter their profile information, such as their name, age, gender, hobbies, and interests, into the device. The device then sends the information to the server, which then stores it in a database.

[0249] 2. Data Collection and Analysis

[0250] Explain the process for collecting and analyzing user behavior data:

[0251] Within the app, users read articles, participate in events, and chat with friends. The device sends this behavioral history data to the server, which then stores and updates the collected behavioral history data in a database. The generation AI analyzes the behavioral history data and identifies the user's interests and behavioral patterns.

[0252] 3. Emotion Recognition and Analysis

[0253] Explain the process of recognizing and analyzing user emotions:

[0254] The device collects facial and voice data when the user uses the app. The device sends this data to the server as emotional data. The server's emotional engine analyzes the emotional data and identifies the user's current emotional state.

[0255] 4. Providing opportunities for encounters

[0256] Explain the process we use to find the right matchmaking opportunities for you:

[0257] The server selects the most suitable meeting opportunities for the user (for example, events that match hobbies or activities that share common interests) based on the analysis results of the generation AI and the emotion engine. The server generates specific suggestions for meeting opportunities and creates the body of the push notification. The device sends the push notification to the user, and the user participates in the suggested events or activities based on the received suggestions.

[0258] 5. Provide a memorable experience

[0259] Describe the process for delivering experiences to users who share common hobbies and interests:

[0260] The server extracts unmarried people who share common hobbies and interests. The generation AI generates suggestions for joint activities (e.g., cooking classes, camping) based on the extracted information about users and their emotions. The server creates the push notification content, and the device sends the push notification to the user. The user participates in the suggested activity and creates unforgettable memories through the experience.

[0261] 6. Proposal of a vision for the future

[0262] Describe the process to help users visualize their future life:

[0263] The AI ​​generates a future vision (suggestions for newlywed life or relocation destinations) based on the user's interests, behavioral data, and emotional data. The server stores the generated future vision in a database. The device presents the saved future vision to the user in video or text format. The user can use the presented future vision as a reference to imagine and consider their own specific vision of the future.

[0264] As a concrete example, consider a case where a user's hobby is "music." The system analyzes the user's past behavioral history and suggests local music festivals. Furthermore, based on the results of the emotion engine's analysis of the user's emotional data, the system makes suggestions to the user at appropriate times. It also suggests music workshops that users can participate in together with other users who share the same hobby, and presents a vision of the future of relocating to a region with a strong music scene.

[0265] In this way, this system aims to improve marriage rates by analyzing users' profile information, behavioral history data, and emotional data, and providing various types of support leading up to marriage.

[0266] The processing flow will be explained below.

[0267] Step 1:

[0268] User enters profile information:

[0269] Users download and install the app on their device, then enter their profile information, such as their name, age, gender, hobbies, and interests.

[0270] Step 2:

[0271] The device sends the input data to the server:

[0272] The terminal transmits the input profile information to the server, and the server receives the input data.

[0273] Step 3:

[0274] The server stores the profile information in a database:

[0275] The server stores the received profile information in a database.

[0276] Step 4:

[0277] User takes action in the app:

[0278] Within the app, users can read articles, attend events, and chat with friends.

[0279] Step 5:

[0280] The device sends the activity history data to the server:

[0281] Data about each user's activity (e.g., articles viewed, events attended, chat history) is sent from the device to the server.

[0282] Step 6:

[0283] The server collects the behavioral history data and stores it in a database:

[0284] The server stores the collected behavioral history data in a database and updates it accordingly.

[0285] Step 7:

[0286] The emotion engine collects emotion data:

[0287] The device collects facial expressions and voice data when the user uses the app and sends it to the server as emotional data.

[0288] Step 8:

[0289] The server analyzes the emotion data:

[0290] An emotion engine in the server analyzes the emotion data and identifies the user's current emotional state.

[0291] Step 9:

[0292] Generative AI analyzes behavioral and emotional data:

[0293] The generation AI on the server analyzes behavioral history data and emotional data to identify the user's interests and behavioral patterns.

[0294] Step 10:

[0295] The server selects the opportunities and creates suggestions:

[0296] Based on the analysis results of the generation AI and emotion engine, the server selects meeting opportunities (e.g., hobby-based events and content) to suggest and generates the proposed content.

[0297] Step 11:

[0298] The server creates the push notification content:

[0299] Create the push notification body based on the suggestions generated by the server.

[0300] Step 12:

[0301] The device sends a push notification to the user:

[0302] The device forwards the contents of the push notification sent from the server to the user.

[0303] Step 13:

[0304] The user participates in a suggested dating opportunity:

[0305] Users receive push notifications and act on suggested events and activities.

[0306] Step 14:

[0307] The server extracts users with common hobbies and interests:

[0308] The server extracts users with common hobbies and interests from the database.

[0309] Step 15:

[0310] Generative AI suggests collaborative activities:

[0311] Based on the extracted information between users, a generation AI on the server generates suggestions for joint activities (e.g., cooking classes, camping).

[0312] Step 16:

[0313] The server creates a push notification for the collaboration:

[0314] The server creates the text of the push notification for the collaborative activity based on the suggestions made by the generation AI.

[0315] Step 17:

[0316] The device sends a push notification to the user about the collaborative activity:

[0317] The terminal forwards the push notification of the collaborative activity sent from the server to the user.

[0318] Step 18:

[0319] The user participates in a proposed collaborative activity:

[0320] Users receive push notifications and act on suggested collaborative activities.

[0321] Step 19:

[0322] Generative AI creates a vision of the future:

[0323] The generation AI on the server generates a future vision (suggestions for newlywed life and relocation destinations) based on the user's interests, behavioral data, and emotional data.

[0324] Step 20:

[0325] The server saves the generated future view:

[0326] The server stores the generated future projections in a database.

[0327] Step 21:

[0328] The device presents the user with a vision of the future:

[0329] The device presents the future vision stored on the server to the user in video or text format.

[0330] Step 22:

[0331] Users consider the future:

[0332] Users can use the presented future projections to concretely imagine and consider their own future.

[0333] Example 2

[0334] 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."

[0335] Unmarried people face difficulties in finding a partner and building relationships in the process leading up to marriage. In particular, there is no system that can properly grasp a user's interests and emotional state and suggest opportunities to meet or joint activities based on that information, making it difficult for unmarried people to build deep relationships with each other.

[0336] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0337] In this invention, the server includes means for inputting profile information of unmarried people, means for saving the profile information in a database, means for collecting behavioral history data, means for analyzing the behavioral history data saved in the database and identifying the user's interests, means for collecting user emotional data, means for analyzing the emotional data and identifying the user's emotional state, means for suggesting meeting opportunities based on the analysis results, and means for sending the suggested meeting opportunities by push notification. This makes it possible to suggest appropriate meeting opportunities and joint activities based on the user's interests and emotional state.

[0338] "Single" means a person who is not legally married.

[0339] "Profile information" refers to personal information such as name, age, gender, hobbies, and interests.

[0340] A "database" is a digital recording system that stores information in an organized manner and makes it easy to search and manage.

[0341] "Behavioral history data" is a record of various activities and operations performed by users within the app.

[0342] "Interests" are the things or areas that a user is particularly interested in and finds appealing.

[0343] "User" means an individual who uses this system.

[0344] "Emotional data" refers to information about emotions obtained from the user's facial expressions, voice, etc.

[0345] An "emotional state" is the psychological state or feeling a user is experiencing at a given moment.

[0346] "Analysis results" are conclusions or information obtained through data analysis.

[0347] "Dating opportunities" are events and activities that allow singles to meet other singles.

[0348] "Push notification" means a notification that the system sends to a user's device in real time.

[0349] "Joint activities" are events or activities that single people with common hobbies or interests participate in together.

[0350] "Future Visions" are simulations or scenarios that concretely illustrate the user's future possibilities.

[0351] The present invention is a system that provides various support services to unmarried people leading up to marriage, and in particular, it is a system that combines an emotion engine that recognizes the user's emotions. This system is implemented using the following hardware and software.

[0352] Hardware and software used

[0353] Terminal: A device that is directly operated by the user, such as a smartphone, tablet, or PC.

[0354] Server: The server that stores, processes, and notifies data.

[0355] Database: A relational database management system (RDBMS) such as MySQL or PostgreSQL.

[0356] Generative AI model: A machine learning model for analyzing user behavioral history and interests.

[0357] Emotion engine: A software module that analyzes a user's facial expressions and voice data to identify emotions.

[0358] Processing Overview

[0359] 1. User Registration

[0360] Users download and install the app on their devices such as smartphones or tablets. After that, they launch the app and enter their profile information, such as their name, age, gender, hobbies, and interests. The entered information is sent from the device to a server, which then stores it in a database.

[0361] 2. Data Collection and Analysis

[0362] Within the app, users read articles, participate in events, and chat with friends. The device sequentially sends this behavioral history data to the server, which then stores it in a database. The generative AI model analyzes the behavioral history data to identify the user's interests and behavioral patterns.

[0363] 3. Emotion Recognition and Analysis

[0364] When a user uses the app, the device uses the front camera and microphone to collect facial and voice data, which is then sent from the device to a server where an emotion engine analyzes the data to identify the user's current emotional state.

[0365] 4. Providing opportunities for encounters

[0366] The server proposes optimal meeting opportunities to users based on the analysis results of the generative AI model and emotion engine. Specifically, it selects events and activities that match users' interests and sends them to the device as push notifications. Users can then participate in events and activities based on the suggestions they receive.

[0367] 5. Provide a memorable experience

[0368] The server extracts singles with common hobbies and interests from a database and uses a generative AI model to suggest joint activities. The server then creates a push notification, which the device sends to the user. The user then participates in the suggested activities and creates unforgettable memories.

[0369] 6. Proposal of a vision for the future

[0370] The generative AI model generates a future vision based on the user's interests, behavioral data, and emotional data. The server stores the generated future vision in a database, and the device presents it to the user in video or text format. The user can use the presented future vision as a reference to imagine and consider their own specific vision of the future.

[0371] Specific examples

[0372] For example, if a user's hobby is "music," the system will analyze the user's past behavioral history and suggest local music festivals. It will also make appropriate suggestions to the user based on the results of the emotion engine's analysis of their emotional data. It will also suggest music workshops that users can participate in together with other users who share the same hobby, and in the future, it will present a vision of moving to a region with a strong music scene.

[0373] Prompt Sentence Examples

[0374] The following prompt sentences are fed into the generative AI model for analysis:

[0375] "User A's hobby is music. Based on past behavioral history data, would it be appropriate to suggest a local music festival this weekend? Furthermore, how can we suggest joint activities with User B, who shares the same musical interest?"

[0376] As described above, the present invention analyzes a user's profile information, behavioral history data, and emotional data, and provides various types of support leading up to marriage.

[0377] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0378] Step 1: User Registration

[0379] 1. Input: The user downloads the app and installs it on their device.

[0380] 2. Input: The user enters their profile information (name, age, gender, hobbies, interests, etc.).

[0381] 3. Operation: The device sends the entered profile information to the server.

[0382] 4. Output: The server stores the received profile information in a database.

[0383] Example: If a user inputs that their hobby is "music," that hobby information is saved in a database.

[0384] Step 2: Data collection and analysis

[0385] 1. Input: A user reads an article, attends an event, or chats with a friend within the app.

[0386] 2. Operation: The device sequentially sends this behavioral history data to the server.

[0387] 3. Input: The server saves and updates the behavioral history data it receives in the database.

[0388] 4. Action: The generative AI model analyzes historical behavioral data and identifies user interests.

[0389] 5. Output: The analysis results from the generation AI are obtained from the server, and the user's interests and behavioral patterns are identified.

[0390] Example: If a user frequently reads articles about "music festivals," the generative AI will identify that the user is interested in music festivals.

[0391] Step 3: Emotion Recognition and Analysis

[0392] 1. Input: The device collects facial and voice data when the user uses the app.

[0393] 2. Operation: The device sends the collected facial and voice data to the server as emotion data.

[0394] 3. Input: The server passes the received emotion data to the emotion engine.

[0395] 4. Action: The emotion engine analyzes the emotion data and identifies the user's current emotional state.

[0396] 5. Output: The server obtains the analysis results from the emotion engine and identifies the user's emotional state.

[0397] Example: If a smiling expression is detected while a user is reading a music article, the emotion engine identifies the user as "happy."

[0398] Step 4: Providing opportunities for encounters

[0399] 1. Input: The analysis results of the generation AI and emotion engine are integrated on the server.

[0400] 2. Operation: Based on the analysis results, the server suggests the best meeting opportunities to the user.

[0401] 3. Input: Select events and activities that suit your interests as suggestions.

[0402] 4. Action: The server generates specific suggestions for dating opportunities and creates the body of the push notification.

[0403] 5. Output: The device sends a push notification to the user, and the user receives the notification.

[0404] Example: A user receives a push notification saying, "We encourage you to attend the music festival this weekend."

[0405] Step 5: Deliver a memorable experience

[0406] 1. Input: The server extracts from the database singles who share common hobbies and interests.

[0407] 2. Operation: The generative AI model generates suggestions for joint activities based on the extracted information and emotional data between users.

[0408] 3. Input: Suggestions for events and experiences based on common interests are generated.

[0409] 4. Operation: The server creates the push notification content, and the device sends the push notification to the user.

[0410] 5. Output: The user participates in the suggested activity and creates unforgettable memories through the experience.

[0411] Example: A user receives suggestions for cooking classes to join with other users who share the same interests.

[0412] Step 6: Propose a vision for the future

[0413] 1. Input: The generative AI model generates a future forecast based on the user's interests, behavioral data, and emotional data.

[0414] 2. Operation: The server saves the generated future projections in a database.

[0415] 3. Input: The saved future projection is ready to be provided to the user.

[0416] 4. Operation: The device presents the future vision to the user in the form of video and text.

[0417] 5. Output: The user uses the presented future vision as a reference to imagine and consider their own future in concrete terms.

[0418] Example: A user is presented with a plan to move to a music-loving area in the future.

[0419] This allows users to receive suggestions for more suitable encounters, memorable experiences, and future prospects based on their profile information, behavioral history data, and emotional data.

[0420] (Application example 2)

[0421] 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."

[0422] There is a lack of systems to promote marriage among today's unmarried people. In particular, there is a lack of methods to utilize users' emotional and behavioral data to provide them with optimal dating opportunities at the right time, and to use virtual spaces to help users visualize actual married life. This makes it difficult for users to imagine suitable dating opportunities and their future lives, leading to a decline in marriage rates.

[0423] The specification processing by the specification 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 inputting profile information of unmarried people, means for saving the profile information in a database, means for analyzing behavioral history data saved in the database and identifying the user's interests, means for suggesting meeting opportunities based on the analysis results, means for sending the suggested meeting opportunities via push notification, means for collecting and analyzing the user's emotional data, means for suggesting meeting opportunities at optimal times based on the analysis results of the emotional data, means for generating and presenting a future vision based on the user's profile information, behavioral history data, and emotional data, and means for constructing a virtual space and conducting meetings and activities within the virtual space. This makes it possible to appropriately utilize the user's emotional and behavioral data to provide optimal meeting opportunities and allow the user to imagine a concrete future life through the virtual space.

[0424] "Single" refers to someone who is not currently married.

[0425] "Profile Information" refers to basic information that identifies an individual, such as a user's name, age, gender, hobbies, and interests.

[0426] A "database" is a system for organizing and storing data in digital form.

[0427] "Behavioral history data" refers to various activity records generated when a user uses the system.

[0428] "Interests" refers to the interest or concern a user has in a particular activity or topic.

[0429] "Analyzing" refers to the detailed analysis of the data obtained using computational and statistical methods to derive specific information or patterns.

[0430] "Meeting opportunities" refers to events and activities that allow users to communicate with other users and build new relationships.

[0431] "Push notification" refers to a technology that sends specific information or messages directly to a user's device.

[0432] "Emotional data" refers to data that indicates the emotional state of a user analyzed from their facial expressions and voice.

[0433] "Virtual space" refers to a virtual three-dimensional space constructed using computer technology.

[0434] "Future projections" refer to diagrams and images that visually represent future lifestyles and situations, generated based on user data.

[0435] "Joint activities" refer to activities undertaken by multiple users who share a common hobby or interest.

[0436] "Building" refers to designing a system or program and putting it into a working form.

[0437] "Notify" refers to the act of informing a user of specific information.

[0438] The present invention is a system that provides various support services to unmarried people leading up to marriage. By combining a generative AI model and an emotion engine, the system analyzes users' interests, behavioral history, and emotional data to provide more appropriate "opportunities to meet people," "unforgettable memories," and "future projections." Specific embodiments of the present invention are described in detail below.

[0439] composition

[0440] This system consists of three main parts: the server, the terminal, and the user. Each part works together to provide optimal support for the user in their search for a partner.

[0441] Hardware and software used

[0442] Server: AWS (Amazon Web Services) is used, DynamoDB is used as the database, and AWS SNS is used as the notification service.

[0443] Device: The user's smartphone or head-mounted display (HMD) (e.g., Oculus Rift).

[0444] Analysis software:

[0445] We use Google Analytics to collect behavioral history data.

[0446] OpenCV (facial expression recognition) and Librosa (voice analysis) are used for emotion data processing.

[0447] TensorFlow and PyTorch are used for generative AI models.

[0448] User Registration

[0449] After installing the app on a smartphone or HMD, users enter their profile information, which is then sent from the device to the server and stored in DynamoDB.

[0450] Data collection and analysis

[0451] User behavioral history data is collected using Google Analytics. The server stores the collected data and analyzes it using generative AI models (TensorFlow or PyTorch) to identify user interests and behavioral patterns. The results of this analysis are stored in a database and used for future recommendations.

[0452] Emotion Recognition and Analysis

[0453] When a user uses a device (smartphone or HMD), facial expression data is collected using OpenCV and voice data is collected using Librosa. This emotion data is sent to the server and analyzed by the emotion engine. The analysis results are also stored in a database.

[0454] Providing opportunities to meet people

[0455] The server then uses the analysis results of the generative AI model and emotion engine to suggest optimal meeting opportunities for users. For example, it generates events and activities that share common interests and sends them to users as push notifications using AWS SNS.

[0456] Providing a memorable experience

[0457] The server extracts users with common hobbies and interests and uses a generative AI model to generate suggestions for joint activities (e.g., cooking classes or camping). The suggestions are sent to users as push notifications, allowing them to experience these activities in a virtual space. Unity is used to design the virtual space, and Photon is used for real-time communication.

[0458] Proposal for a vision of the future

[0459] A generative AI model generates a future vision based on the user's behavioral and emotional data. This future vision (e.g., a proposal for married life or a new home) is created as a 3D model using Blender and stored in AWS S3. It is then presented to the user's device in the form of a video or text.

[0460] Examples and prompts

[0461] As a specific example, if the user's hobby is "traveling," the following processing is performed.

[0462] 1. Analyze past travel events that users have participated in based on their behavioral history.

[0463] 2. Based on the analysis results and the emotion engine results, we suggest a virtual travel experience with someone who loves to travel.

[0464] 3. Present future travel plans and virtual tours of the city you will live in together as a vision of the future.

[0465] Example prompt for generative AI model:

[0466] The user's profile information states that their hobby is traveling. Based on their past behavior, they have previously been interested in traveling to Northern Europe. Based on their sentiment data, they are currently excited about traveling. Please suggest an event where they can virtually experience a Nordic trip with their travel-loving partner. Also, please create a vision of their future married life in a Nordic city.

[0467] In this way, the system aims to improve marriage rates by analyzing users' profile information, behavioral history data, and emotional data, and providing various types of support leading up to marriage.

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

[0469] Step 1:

[0470] Users install the app on their device (smartphone or HMD) and enter their profile information, which includes their name, age, gender, hobbies, and interests. The entered information is sent from the device to the server and stored in DynamoDB, which registers the user profile in the database.

[0471] Input: User profile information (name, age, gender, hobbies, etc.)

[0472] Output: User profile stored in database

[0473] Step 2:

[0474] When a user uses the app, behavioral history data is collected through Google Analytics. This data includes which events the user participated in, which content the user viewed, etc. The collected behavioral history data is sent to a server and stored in a database.

[0475] Input: User behavioral history data (event participation history, content viewing history, etc.)

[0476] Output: Behavioral history data stored in a database

[0477] Step 3:

[0478] The server uses generative AI models using TensorFlow and PyTorch to analyze the stored behavioral history data, identifying user interests and behavioral patterns and storing the results in a database.

[0479] Input: Behavioral history data stored in the database

[0480] Output: Analysis results of interests and behavioral patterns

[0481] Step 4:

[0482] When a user uses the device, emotion data is collected using facial recognition with OpenCV and voice analysis with Librosa. This emotion data is sent to the server, where it is analyzed by the emotion engine and the results are stored in a database.

[0483] Input: User's facial and voice data

[0484] Output: Analysis results of emotion data stored in the database

[0485] Step 5:

[0486] The server then proposes optimal meeting opportunities to users based on the analysis results of the generative AI model and emotion engine. The proposals are sent to the user's device as push notifications via AWS SNS. For example, it could suggest that users with common interests attend a music festival.

[0487] Input: Analysis results of interests and behavioral patterns and analysis results of emotional data

[0488] Output: Dating opportunities sent via push notification

[0489] Step 6:

[0490] The server extracts users with common hobbies and interests and uses a generative AI model to generate suggestions for joint activities (e.g., cooking classes or camping). These suggestions are sent to users as push notifications, allowing them to experience these activities in a virtual space. The virtual space is designed using Unity and Photon.

[0491] Input: Data of users with common hobbies and interests

[0492] Output: Collaborative activity suggestions sent via push notification

[0493] Step 7:

[0494] A generative AI model generates a future vision based on the user's behavioral and emotional data. This future vision is created as a 3D model using Blender and stored on AWS S3. By presenting it to the user in video and text format, it becomes easier for them to visualize specific future plans.

[0495] Input: User behavioral and emotional data

[0496] Output: A future vision presented to the user (3D model or video format)

[0497] 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.

[0498] 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.

[0499] 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.

[0500] [Second embodiment]

[0501] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0502] 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.

[0503] 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).

[0504] 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.

[0505] 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.

[0506] 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).

[0507] 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.

[0508] 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.

[0509] 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.

[0510] 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.

[0511] In the smart glasses 214, 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.

[0512] 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."

[0513] This invention is a system that provides various support to unmarried people until they get married. This system uses generative AI to analyze the user's interests and behavioral history, and provides "opportunities to meet people," "unforgettable memories," and "future visions" necessary for marriage. This system consists of three main parts: a server, a terminal, and a user.

[0514] Program processing

[0515] 1. User Registration

[0516] Describe the process by which a user enters profile information:

[0517] Users download the app and install it on their devices.

[0518] Users enter profile information such as their name, age, gender, hobbies, and interests into the device.

[0519] The terminal sends the input data to the server, which stores the information in a database.

[0520] 2. Data Collection and Analysis

[0521] Explain the process for collecting and analyzing user behavior data:

[0522] Within the app, users can read articles, attend events, and chat with friends.

[0523] The terminal transmits this behavior history data to the server.

[0524] The server successively stores and updates the collected behavioral history data in a database.

[0525] The generative AI analyzes behavioral history data and identifies the user's interests and behavioral patterns.

[0526] 3. Providing opportunities for encounters

[0527] Explain the process we use to find the right matchmaking opportunities for you:

[0528] Based on the analysis results of the generative AI, the server selects the most suitable meeting opportunities for the user (for example, events that share similar hobbies or activities that share common interests).

[0529] The server generates specific suggestions for dating opportunities and creates the body of the push notification.

[0530] The device will send a push notification to the user, who will then participate in the suggested event or activity based on the suggestions received.

[0531] 4. Providing a memorable experience

[0532] Describe the process for delivering experiences to users who share common hobbies and interests:

[0533] The server extracts unmarried people who share common hobbies and interests.

[0534] Based on the extracted information between users, the generation AI generates suggestions for joint activities (e.g., cooking classes, camping).

[0535] The server creates the push notification content, and the device sends the push notification to the user.

[0536] Users can participate in the suggested activities and create unforgettable memories through the experience.

[0537] 5. Proposal of a vision for the future

[0538] Describe the process to help users visualize their future life:

[0539] Generative AI generates a future vision (suggestions for newlywed life and relocation destinations) based on the user's interests and behavioral data.

[0540] The server stores the generated future projections in a database.

[0541] The device will present the user with the saved future vision in video and text format.

[0542] Users can use the presented future projections as a reference to imagine and consider their own specific vision of the future.

[0543] As a concrete example, consider a case where a user's hobby is "music." The system analyzes the user's past behavioral history and suggests local music festivals. It also suggests music workshops that users can participate in together with other users who share the same hobby, and suggests future plans for the user to move to a region with a strong music scene.

[0544] In this way, this system aims to improve marriage rates by analyzing users' profile information and behavioral history data and providing various types of support leading up to marriage.

[0545] The processing flow will be explained below.

[0546] Step 1:

[0547] User enters profile information:

[0548] Users download and install the app on their device, and then enter their profile information, such as their name, age, gender, hobbies, and interests, through the device.

[0549] Step 2:

[0550] The device sends the input data to the server:

[0551] The terminal transmits the input profile information to the server, and the server receives the input data.

[0552] Step 3:

[0553] The server stores the profile information in a database:

[0554] The server stores the received profile information in a database.

[0555] Step 4:

[0556] User takes action in the app:

[0557] Within the app, users can read articles, attend events, and chat with friends.

[0558] Step 5:

[0559] The device sends the activity history to the server:

[0560] User activity data (e.g., which articles you read, which events you attended, which users you chatted with) is sent from your device to a server.

[0561] Step 6:

[0562] The server collects and updates the behavioral history data:

[0563] The server sequentially stores and updates the collected behavioral history data in a database.

[0564] Step 7:

[0565] Generative AI analyzes historical behavioral data:

[0566] The generation AI on the server analyzes the stored behavioral history data and identifies the user's interests and behavioral patterns.

[0567] Step 8:

[0568] The server selects the opportunities and creates suggestions:

[0569] Based on the analysis results of the generation AI, the server selects meeting opportunities to suggest (for example, hobby-based events or activities) and generates the suggestions.

[0570] Step 9:

[0571] The server creates the push notification:

[0572] Create the body of the push notification to the user based on the suggestions generated by the server.

[0573] Step 10:

[0574] The device sends a push notification to the user:

[0575] The device sends the push notification created by the server to the user.

[0576] Step 11:

[0577] The user participates in a suggested dating opportunity:

[0578] Users receive push notifications and act on suggested events and activities.

[0579] Step 12:

[0580] The server extracts users with common hobbies and interests:

[0581] The server extracts users with common hobbies and interests from the database.

[0582] Step 13:

[0583] Generative AI suggests collaborative activities:

[0584] Based on the extracted information between users, the generative AI generates suggestions for joint activities (e.g., cooking classes or camping).

[0585] Step 14:

[0586] The server creates a push notification for the collaboration:

[0587] The server creates the text of the push notification for the collaborative activity based on the suggestions made by the generated AI.

[0588] Step 15:

[0589] The device sends a push notification to the user:

[0590] The device sends a push notification of the collaborative activity created by the server to the user.

[0591] Step 16:

[0592] The user participates in a proposed collaborative activity:

[0593] The user receives a push notification and acts on the suggested collaborative activity.

[0594] Step 17:

[0595] Generative AI creates a vision of the future:

[0596] The server's on-board AI generates a future vision (suggestions for newlywed life and relocation destinations) based on the user's interests and behavioral data.

[0597] Step 18:

[0598] The server saves the generated future view:

[0599] The server stores the generated future projections in a database.

[0600] Step 19:

[0601] The device presents the user with a vision of the future:

[0602] The device presents the future vision stored on the server to the user in the form of video and text.

[0603] Step 20:

[0604] Users consider the future:

[0605] Users use the future projections presented to them as a reference to imagine and consider their own specific future.

[0606] Example 1

[0607] 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."

[0608] In the process of getting married, unmarried people face challenges in finding suitable opportunities to meet people, engaging in joint activities, and having a concrete image of their future life. These challenges make it difficult for unmarried people to find a suitable partner based on their own interests and behavioral patterns, leading to a decline in the marriage rate. The present invention aims to solve these challenges and provide effective support to unmarried people.

[0609] 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.

[0610] In this invention, the server includes means for inputting personal information of unmarried people, means for saving the personal information in a storage device, means for analyzing the activity history data saved in the storage device and using a generative artificial intelligence model to identify the user's interests, means for using the generative artificial intelligence model to suggest meeting opportunities based on the analysis results, and means for sending the suggested meeting opportunities via a notification function. This enables unmarried people to receive suggestions for meeting opportunities and joint activities that match their interests and behavioral patterns, and is expected to improve the marriage rate.

[0611] "Single person" refers to an individual who is not married.

[0612] "Personal information" refers to information that identifies and distinguishes an individual, such as name, age, gender, hobbies, and interests.

[0613] "Storage" refers to a hardware device or electronic storage medium that can store data and retrieve it as needed.

[0614] "Activity history data" refers to data about behavior generated while a user uses the app, such as reading articles, attending events, and chatting.

[0615] A "generative artificial intelligence model" refers to an artificial intelligence technology model that performs analysis based on input data and generates output appropriate for the next action.

[0616] "Interests" refer to specific activities or information that a user is interested in or concerned about.

[0617] "Meeting opportunities" refers to events, activities, and other venues where unmarried people can interact with each other and build relationships.

[0618] "Notification Function" refers to a technical means for transmitting information to a recipient in real time, including push notifications.

[0619] This system uses a generative AI model to support unmarried people until they reach marriage. It consists of three main components: a server, a terminal, and a user.

[0620] First, the user downloads and installs the application onto their device. After installation, the user enters profile information such as name, age, gender, hobbies, and interests. This information is sent from the user device to the server, where it is stored in a database.

[0621] Next, behavioral history data is collected as users read articles, attend events, and chat with friends within the app. This data is also sent from the user's device to the server, which stores it in a database and keeps it up to date. Within the server, a generative AI model analyzes this data and processes it to identify the user's interests and behavioral patterns.

[0622] Based on the analysis results, the generative AI model generates information to suggest optimal meeting opportunities to the user. For example, if the user's hobby is music, the model will suggest information about local music festivals and music workshops. The generated suggestions are converted into push notifications on the server and sent to the user's device. Users who receive the notifications can participate in events and activities based on the suggestions.

[0623] Furthermore, the system will select unmarried people who share common hobbies and interests and suggest joint activities to those users. For example, if one of their hobbies is cooking, it will suggest that they join a cooking class. The details of the proposed joint activities will also be sent to the user via push notification.

[0624] Furthermore, to help users visualize their future lives in concrete terms, the generative AI model generates a future vision based on the user's interests and behavioral data. For example, for a user whose hobby is music, the model will create a vision of moving to a music-loving region or newlywed life. The generated future vision is saved on the server and presented in video or text format on the user's device. This allows users to realistically imagine their future and consider it in detail.

[0625] Examples of prompts include:

[0626] "Based on the user's profile information and behavioral data, suggest events that match their hobbies and interests."

[0627] "Please create opportunities for users with common interests to meet and express them as concrete proposals."

[0628] "Create a vision of the future that interests users and generate explanatory text to present it in video or text format."

[0629] As described above, this system utilizes generative AI models and various analytical technologies to provide various types of support to unmarried people, enabling them to obtain optimal dating opportunities and visions for the future based on their interests and behavioral patterns, and supporting them in the process of getting married.

[0630] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0631] Step 1:

[0632] A user downloads an app and installs it on their device. The input is the application download link and the output is the installed application. A user searches for an app in the App Store or Google Play and clicks the download button to install it.

[0633] Step 2:

[0634] The user opens the app and enters personal information such as name, age, gender, hobbies, and interests. The input is the personal information the user entered into the form, and the output is the personal information temporarily stored on the device. The user enters data into each field in the form displayed on the app's registration screen.

[0635] Step 3:

[0636] The device sends the entered personal information to the server. The input is the personal information entered by the user, and the output is the data sent to the server. When the device completes the input form and presses the send button, the data is encrypted and sent to the server.

[0637] Step 4:

[0638] The server stores the received data in a database. The input is the personal information sent from the terminal, and the output is the personal information stored in the database. The server analyzes the received data and stores it in the appropriate field.

[0639] Step 5:

[0640] When a user reads an article, attends an event, or chats with friends within an app, the input is the user's activity and the output is behavioral history data. As the user uses various functions within the app, that behavioral data is automatically collected.

[0641] Step 6:

[0642] The terminal sends the collected behavioral history data to the server. The input is the user's behavioral history data, and the output is the data sent to the server. At regular intervals, the terminal sends the data to the server using batch processing.

[0643] Step 7:

[0644] The server saves the collected behavioral history data in a database and updates it. The input is the behavioral history data sent from the device, and the output is the updated database. The server adds the new data to the database and updates the links and indexes.

[0645] Step 8:

[0646] The generative AI model analyzes behavioral history data and identifies the user's interests and behavioral patterns. The input is behavioral history data, and the output is the analysis results. The generative AI model uses a machine learning algorithm to cluster the data and extract features.

[0647] Step 9:

[0648] The server selects the best meeting opportunities for the user based on the analysis results of the generated AI model. The input is the analysis results, and the output is the selection results of meeting opportunities. The server filters matching events from the event database.

[0649] Step 10:

[0650] The server generates specific matchmaking suggestions and creates the push notification body. The input is the matchmaking selection results, and the output is the push notification body. Templates are used to generate and customize the notification message.

[0651] Step 11:

[0652] The device sends a push notification to the user. The input is the push notification body, and the output is the notification received by the user device. The backend notification server sends the real-time notification to the user device.

[0653] Step 12:

[0654] The server extracts singles who share common hobbies and interests. The input is interest data, and the output is a list of users who share common hobbies. A database query is used to list users who share common tags.

[0655] Step 13:

[0656] The generative AI model generates specific suggestions for joint activities based on the extracted information between users. The input is a list of users with common interests, and the output is suggestions for joint activities. Multiple options are generated based on the user's interests.

[0657] Step 14:

[0658] The server generates collaborative activity suggestions and creates a push notification. The input is the collaborative activity suggestions and the output is the push notification body. A personalized notification is created based on the suggestions.

[0659] Step 15:

[0660] The device sends a push notification to the user. The input is the push notification body, and the output is the notification received by the user device. The notification server sends the notification to the user device in real time.

[0661] Step 16:

[0662] The generative AI model generates a future forecast based on user interest and behavioral data. The input is interest data and behavioral history data, and the output is a future forecast. Scenarios are depicted using simulation models and past data.

[0663] Step 17:

[0664] The server saves the generated future projections in a database. The input is the future projections, and the output is the future projections saved in the database. A future projection customized for each user is saved.

[0665] Step 18:

[0666] The device presents the saved future vision to the user in the form of video or text. The input is the future vision stored in the database, and the output is the content presented to the user. Create a section within the app to display the content of the future vision.

[0667] (Application example 1)

[0668] 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."

[0669] While there are existing systems that provide various support to unmarried people leading up to marriage, there are no systems that promote opportunities for meeting people while traveling in self-driving vehicles. Furthermore, there is a lack of appropriate matching and suggestions for joint activities that utilize users' travel routes and ride-sharing history, as well as a means to concretely visualize their future lives. This makes it difficult for unmarried people to efficiently find opportunities to meet people while traveling.

[0670] 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.

[0671] In this invention, the server includes means for inputting profile information of unmarried people, means for saving the profile information in a database, means for analyzing behavioral history data saved in the database and identifying user interests, means for suggesting meeting opportunities based on the analysis results, means for sending the suggested meeting opportunities by push notification, means for collecting travel routes and ride-sharing histories of autonomous vehicles, means for saving and analyzing the travel routes and ride-sharing histories in a database, and means for matching users heading in the same direction based on the analysis results and sending the results by push notification. This enables unmarried people to efficiently find meeting opportunities while traveling in autonomous vehicles.

[0672] "Profile Information" is personal information about a user, such as their name, age, gender, hobbies, and interests.

[0673] A "database" is a system for organizing, storing, and managing collected information.

[0674] "Behavioral history data" is a record of a user's past activities and behaviors.

[0675] "Analysis" is the process of examining collected data in detail and finding meaning.

[0676] "Interests" refers to the range of interests or concerns a user has about a particular subject.

[0677] "Meeting Opportunities" are situations or events where users can meet new people.

[0678] "Push Notification" means a notification sent to a User's Device in real time.

[0679] An "autonomous vehicle" is a vehicle that operates automatically without a human driver.

[0680] A "travel route" is the route a vehicle takes.

[0681] "Ride-sharing history" is a record of ride-sharing services a user has used in the past.

[0682] "Matching" is the process of connecting users with common interests and goals.

[0683] A "collaborative activity" is an event or activity in which multiple users participate together.

[0684] A "future vision" is a visual or written suggestion that helps users visualize their future life and activities.

[0685] This invention is a matching system for singles that operates inside an autonomous vehicle. The system is designed to enable singles to efficiently enjoy opportunities to meet people while traveling. The system consists of three main parts: a server, a terminal (display or smartphone of the autonomous vehicle), and a user.

[0686] User Registration

[0687] The server provides a means for users to install the application and enter profile information (such as name, age, gender, hobbies, interests, etc.). The profile information entered by the user is sent to the server via the device and stored in a database. This allows the server to centrally manage individual user information.

[0688] Data collection and analysis

[0689] The server collects the autonomous vehicle's route and ride-sharing history data and stores it in a database. Based on this, the generative AI model analyzes the data and identifies the user's behavioral patterns and interests. Specifically, it analyzes the user's past route and ride-sharing history to understand their behavioral trends. For example, if a user frequently participates in a particular event, that tendency can be analyzed and used to suggest encounters.

[0690] Providing opportunities to meet people

[0691] The server then proposes optimal meeting opportunities to users based on the analysis results of the generation AI. In particular, it matches users heading in the same direction to provide meeting opportunities while traveling in an autonomous vehicle. At this time, the server generates a push notification and sends it to the device. The user can view and participate in the proposed meeting opportunities through their device.

[0692] Specific examples

[0693] When users A and B are traveling long distances to the same area, they discover that they have a common hobby (e.g., music festivals) and suggest an opportunity for them to attend the event together while traveling.

[0694] Providing a memorable experience

[0695] The server extracts singles with common hobbies and interests and generates suggestions for joint activities (e.g., cooking classes, camping) that can be participated in while traveling. These suggestions are automatically generated using AI and sent to users via push notifications on their devices. By participating in the suggested joint activities, users can easily share unforgettable experiences.

[0696] Proposal for a vision of the future

[0697] The server generates a future vision based on the user's interests and behavioral data. For example, generative AI is used to generate specific future images, such as suggestions for newlywed life or where to move. This future vision is stored in a database and presented to the user in video or text format via their device. This allows the user to concretely imagine their future life and make easier plans.

[0698] Prompt Sentence Examples

[0699] “The user is looking to meet someone while traveling long distances. Please suggest attractions and events for the near future. The prompt given to the AI ​​generator is, ‘Please suggest events that the user can enjoy during their trip that share their interests.’”

[0700] This system will enable singles to efficiently find opportunities to meet people while traveling in an autonomous vehicle, and will also provide them with memorable experiences and support in concretely imagining their future lives.

[0701] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0702] Step 1:

[0703] The user enters profile information (such as name, age, gender, hobbies, and interests) into a device (such as a smartphone or the display of an autonomous vehicle). The entered profile information is sent from the device to a server, which receives it and stores it in a database.

[0704] Step 2:

[0705] The user starts traveling in the autonomous vehicle using the application. The terminal collects the vehicle's route and ride-sharing history data in real time and transmits it to the server, which receives it and stores it in a database.

[0706] Step 3:

[0707] The server inputs the behavioral history data stored in the database into the generative AI model to analyze the user's interests. The generative AI model identifies behavioral patterns and hobbies and preferences and outputs the results to the server.

[0708] Step 4:

[0709] The server uses the results of the generative AI model's analysis to suggest optimal meeting opportunities for the user, using an algorithm to determine whether a match with another user heading in the same direction is possible. As a result, an appropriate match is made (e.g., joint attendance at a music festival).

[0710] Step 5:

[0711] The server generates a proposed matchmaking opportunity and sends it as a push notification to the device, which receives the notification and displays it to the user, who then reviews the notification and decides whether to participate in the proposed matchmaking opportunity.

[0712] Step 6:

[0713] The server extracts users with common hobbies and interests and suggests activities they can participate in together (e.g., cooking classes or camping). These suggestions are also automatically generated using a generative AI model and sent to the device as a push notification from the server. The device displays the notification to the user, who then decides whether or not to participate in the activity.

[0714] Step 7:

[0715] The server generates a future vision based on the user's interests and behavioral data and stores it in a database. The generated future vision is presented to the user via their device in the form of video or text. The device displays content that allows the user to concretely imagine what life will be like in the future.

[0716] Step 8:

[0717] To help users visualize their future lives, the generative AI model receives specific prompts, such as "Please suggest events that users can enjoy during their trip that involve common hobbies," and the model receives appropriate output.

[0718] Through these steps, the system will enable singles to efficiently find opportunities to meet people while traveling in an autonomous vehicle, and will also provide them with memorable experiences and support in concretely imagining their future lives.

[0719] 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.

[0720] This invention is a system that provides various support to unmarried people leading up to marriage, and in particular, it is a system that combines an emotion engine that recognizes the user's emotions. This system uses generative AI to analyze the user's interests and behavioral history, and further analyzes the user's emotional data using an emotion engine, to provide more appropriate "opportunities to meet," "unforgettable memories," and "future visions." This system consists of three main parts: a server, a terminal, and the user.

[0721] Program processing

[0722] 1. User Registration

[0723] Describe the process by which a user enters profile information:

[0724] Users download and install the app on their devices, then enter their profile information, such as their name, age, gender, hobbies, and interests, into the device. The device then sends the information to the server, which then stores it in a database.

[0725] 2. Data Collection and Analysis

[0726] Explain the process for collecting and analyzing user behavior data:

[0727] Within the app, users read articles, participate in events, and chat with friends. The device sends this behavioral history data to the server, which then stores and updates the collected behavioral history data in a database. The generation AI analyzes the behavioral history data and identifies the user's interests and behavioral patterns.

[0728] 3. Emotion Recognition and Analysis

[0729] Explain the process of recognizing and analyzing user emotions:

[0730] The device collects facial and voice data when the user uses the app. The device sends this data to the server as emotional data. The server's emotional engine analyzes the emotional data and identifies the user's current emotional state.

[0731] 4. Providing opportunities for encounters

[0732] Explain the process we use to find the right matchmaking opportunities for you:

[0733] The server selects the most suitable meeting opportunities for the user (for example, events that match hobbies or activities that share common interests) based on the analysis results of the generation AI and the emotion engine. The server generates specific suggestions for meeting opportunities and creates the body of the push notification. The device sends the push notification to the user, and the user participates in the suggested events or activities based on the received suggestions.

[0734] 5. Provide a memorable experience

[0735] Describe the process for delivering experiences to users who share common hobbies and interests:

[0736] The server extracts unmarried people who share common hobbies and interests. The generation AI generates suggestions for joint activities (e.g., cooking classes, camping) based on the extracted information about users and their emotions. The server creates the push notification content, and the device sends the push notification to the user. The user participates in the suggested activity and creates unforgettable memories through the experience.

[0737] 6. Proposal of a vision for the future

[0738] Describe the process to help users visualize their future life:

[0739] The AI ​​generates a future vision (suggestions for newlywed life or relocation destinations) based on the user's interests, behavioral data, and emotional data. The server stores the generated future vision in a database. The device presents the saved future vision to the user in video or text format. The user can use the presented future vision as a reference to imagine and consider their own specific vision of the future.

[0740] As a concrete example, consider a case where a user's hobby is "music." The system analyzes the user's past behavioral history and suggests local music festivals. Furthermore, based on the results of the emotion engine's analysis of the user's emotional data, the system makes suggestions to the user at appropriate times. It also suggests music workshops that users can participate in together with other users who share the same hobby, and presents a vision of the future of relocating to a region with a strong music scene.

[0741] In this way, this system aims to improve marriage rates by analyzing users' profile information, behavioral history data, and emotional data, and providing various types of support leading up to marriage.

[0742] The processing flow will be explained below.

[0743] Step 1:

[0744] User enters profile information:

[0745] Users download and install the app on their device, then enter their profile information, such as their name, age, gender, hobbies, and interests.

[0746] Step 2:

[0747] The device sends the input data to the server:

[0748] The terminal transmits the input profile information to the server, and the server receives the input data.

[0749] Step 3:

[0750] The server stores the profile information in a database:

[0751] The server stores the received profile information in a database.

[0752] Step 4:

[0753] User takes action in the app:

[0754] Within the app, users can read articles, attend events, and chat with friends.

[0755] Step 5:

[0756] The device sends the activity history data to the server:

[0757] Data about each user's activity (e.g., articles viewed, events attended, chat history) is sent from the device to the server.

[0758] Step 6:

[0759] The server collects the behavioral history data and stores it in a database:

[0760] The server stores the collected behavioral history data in a database and updates it accordingly.

[0761] Step 7:

[0762] The emotion engine collects emotion data:

[0763] The device collects facial expressions and voice data when the user uses the app and sends it to the server as emotional data.

[0764] Step 8:

[0765] The server analyzes the emotion data:

[0766] An emotion engine in the server analyzes the emotion data and identifies the user's current emotional state.

[0767] Step 9:

[0768] Generative AI analyzes behavioral and emotional data:

[0769] The generation AI on the server analyzes behavioral history data and emotional data to identify the user's interests and behavioral patterns.

[0770] Step 10:

[0771] The server selects the opportunities and creates suggestions:

[0772] Based on the analysis results of the generation AI and emotion engine, the server selects meeting opportunities (e.g., hobby-based events and content) to suggest and generates the proposed content.

[0773] Step 11:

[0774] The server creates the push notification content:

[0775] Create the push notification body based on the suggestions generated by the server.

[0776] Step 12:

[0777] The device sends a push notification to the user:

[0778] The device forwards the contents of the push notification sent from the server to the user.

[0779] Step 13:

[0780] The user participates in a suggested dating opportunity:

[0781] Users receive push notifications and act on suggested events and activities.

[0782] Step 14:

[0783] The server extracts users with common hobbies and interests:

[0784] The server extracts users with common hobbies and interests from the database.

[0785] Step 15:

[0786] Generative AI suggests collaborative activities:

[0787] Based on the extracted information between users, a generation AI on the server generates suggestions for joint activities (e.g., cooking classes, camping).

[0788] Step 16:

[0789] The server creates a push notification for the collaboration:

[0790] The server creates the text of the push notification for the collaborative activity based on the suggestions made by the generation AI.

[0791] Step 17:

[0792] The device sends a push notification to the user about the collaborative activity:

[0793] The terminal forwards the push notification of the collaborative activity sent from the server to the user.

[0794] Step 18:

[0795] The user participates in a proposed collaborative activity:

[0796] Users receive push notifications and act on suggested collaborative activities.

[0797] Step 19:

[0798] Generative AI creates a vision of the future:

[0799] The generation AI on the server generates a future vision (suggestions for newlywed life and relocation destinations) based on the user's interests, behavioral data, and emotional data.

[0800] Step 20:

[0801] The server saves the generated future view:

[0802] The server stores the generated future projections in a database.

[0803] Step 21:

[0804] The device presents the user with a vision of the future:

[0805] The device presents the future vision stored on the server to the user in video or text format.

[0806] Step 22:

[0807] Users consider the future:

[0808] Users can use the presented future projections to concretely imagine and consider their own future.

[0809] Example 2

[0810] 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."

[0811] Unmarried people face difficulties in finding a partner and building relationships in the process leading up to marriage. In particular, there is no system that can properly grasp a user's interests and emotional state and suggest opportunities to meet or joint activities based on that information, making it difficult for unmarried people to build deep relationships with each other.

[0812] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0813] In this invention, the server includes means for inputting profile information of unmarried people, means for saving the profile information in a database, means for collecting behavioral history data, means for analyzing the behavioral history data saved in the database and identifying the user's interests, means for collecting user emotional data, means for analyzing the emotional data and identifying the user's emotional state, means for suggesting meeting opportunities based on the analysis results, and means for sending the suggested meeting opportunities by push notification. This makes it possible to suggest appropriate meeting opportunities and joint activities based on the user's interests and emotional state.

[0814] "Single" means a person who is not legally married.

[0815] "Profile information" refers to personal information such as name, age, gender, hobbies, and interests.

[0816] A "database" is a digital recording system that stores information in an organized manner and makes it easy to search and manage.

[0817] "Behavioral history data" is a record of various activities and operations performed by users within the app.

[0818] "Interests" are the things or areas that a user is particularly interested in and finds appealing.

[0819] "User" means an individual who uses this system.

[0820] "Emotional data" refers to information about emotions obtained from the user's facial expressions, voice, etc.

[0821] An "emotional state" is the psychological state or feeling a user is experiencing at a given moment.

[0822] "Analysis results" are conclusions or information obtained through data analysis.

[0823] "Dating opportunities" are events and activities that allow singles to meet other singles.

[0824] "Push notification" means a notification that the system sends to a user's device in real time.

[0825] "Joint activities" are events or activities that single people with common hobbies or interests participate in together.

[0826] "Future Visions" are simulations or scenarios that concretely illustrate the user's future possibilities.

[0827] The present invention is a system that provides various support services to unmarried people leading up to marriage, and in particular, it is a system that combines an emotion engine that recognizes the user's emotions. This system is implemented using the following hardware and software.

[0828] Hardware and software used

[0829] Terminal: A device that is directly operated by the user, such as a smartphone, tablet, or PC.

[0830] Server: The server that stores, processes, and notifies data.

[0831] Database: A relational database management system (RDBMS) such as MySQL or PostgreSQL.

[0832] Generative AI model: A machine learning model for analyzing user behavioral history and interests.

[0833] Emotion engine: A software module that analyzes a user's facial expressions and voice data to identify emotions.

[0834] Processing Overview

[0835] 1. User Registration

[0836] Users download and install the app on their devices such as smartphones or tablets. After that, they launch the app and enter their profile information, such as their name, age, gender, hobbies, and interests. The entered information is sent from the device to a server, which then stores it in a database.

[0837] 2. Data Collection and Analysis

[0838] Within the app, users read articles, participate in events, and chat with friends. The device sequentially sends this behavioral history data to the server, which then stores it in a database. The generative AI model analyzes the behavioral history data to identify the user's interests and behavioral patterns.

[0839] 3. Emotion Recognition and Analysis

[0840] When a user uses the app, the device uses the front camera and microphone to collect facial and voice data, which is then sent from the device to a server where an emotion engine analyzes the data to identify the user's current emotional state.

[0841] 4. Providing opportunities for encounters

[0842] The server proposes optimal meeting opportunities to users based on the analysis results of the generative AI model and emotion engine. Specifically, it selects events and activities that match users' interests and sends them to the device as push notifications. Users can then participate in events and activities based on the suggestions they receive.

[0843] 5. Provide a memorable experience

[0844] The server extracts singles with common hobbies and interests from a database and uses a generative AI model to suggest joint activities. The server then creates a push notification, which the device sends to the user. The user then participates in the suggested activities and creates unforgettable memories.

[0845] 6. Proposal of a vision for the future

[0846] The generative AI model generates a future vision based on the user's interests, behavioral data, and emotional data. The server stores the generated future vision in a database, and the device presents it to the user in video or text format. The user can use the presented future vision as a reference to imagine and consider their own specific vision of the future.

[0847] Specific examples

[0848] For example, if a user's hobby is "music," the system will analyze the user's past behavioral history and suggest local music festivals. It will also make appropriate suggestions to the user based on the results of the emotion engine's analysis of their emotional data. It will also suggest music workshops that users can participate in together with other users who share the same hobby, and in the future, it will present a vision of moving to a region with a strong music scene.

[0849] Prompt Sentence Examples

[0850] The following prompt sentences are fed into the generative AI model for analysis:

[0851] "User A's hobby is music. Based on past behavioral history data, would it be appropriate to suggest a local music festival this weekend? Furthermore, how can we suggest joint activities with User B, who shares the same musical interest?"

[0852] As described above, the present invention analyzes a user's profile information, behavioral history data, and emotional data, and provides various types of support leading up to marriage.

[0853] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0854] Step 1: User Registration

[0855] 1. Input: The user downloads the app and installs it on their device.

[0856] 2. Input: The user enters their profile information (name, age, gender, hobbies, interests, etc.).

[0857] 3. Operation: The device sends the entered profile information to the server.

[0858] 4. Output: The server stores the received profile information in a database.

[0859] Example: If a user inputs that their hobby is "music," that hobby information is saved in a database.

[0860] Step 2: Data collection and analysis

[0861] 1. Input: A user reads an article, attends an event, or chats with a friend within the app.

[0862] 2. Operation: The device sequentially sends this behavioral history data to the server.

[0863] 3. Input: The server saves and updates the behavioral history data it receives in the database.

[0864] 4. Action: The generative AI model analyzes historical behavioral data and identifies user interests.

[0865] 5. Output: The analysis results from the generation AI are obtained from the server, and the user's interests and behavioral patterns are identified.

[0866] Example: If a user frequently reads articles about "music festivals," the generative AI will identify that the user is interested in music festivals.

[0867] Step 3: Emotion Recognition and Analysis

[0868] 1. Input: The device collects facial and voice data when the user uses the app.

[0869] 2. Operation: The device sends the collected facial and voice data to the server as emotion data.

[0870] 3. Input: The server passes the received emotion data to the emotion engine.

[0871] 4. Action: The emotion engine analyzes the emotion data and identifies the user's current emotional state.

[0872] 5. Output: The server obtains the analysis results from the emotion engine and identifies the user's emotional state.

[0873] Example: If a smiling expression is detected while a user is reading a music article, the emotion engine identifies the user as "happy."

[0874] Step 4: Providing opportunities for encounters

[0875] 1. Input: The analysis results of the generation AI and emotion engine are integrated on the server.

[0876] 2. Operation: Based on the analysis results, the server suggests the best meeting opportunities to the user.

[0877] 3. Input: Select events and activities that suit your interests as suggestions.

[0878] 4. Action: The server generates specific suggestions for dating opportunities and creates the body of the push notification.

[0879] 5. Output: The device sends a push notification to the user, and the user receives the notification.

[0880] Example: A user receives a push notification saying, "We encourage you to attend the music festival this weekend."

[0881] Step 5: Deliver a memorable experience

[0882] 1. Input: The server extracts from the database singles who share common hobbies and interests.

[0883] 2. Operation: The generative AI model generates suggestions for joint activities based on the extracted information and emotional data between users.

[0884] 3. Input: Suggestions for events and experiences based on common interests are generated.

[0885] 4. Operation: The server creates the push notification content, and the device sends the push notification to the user.

[0886] 5. Output: The user participates in the suggested activity and creates unforgettable memories through the experience.

[0887] Example: A user receives suggestions for cooking classes to join with other users who share the same interests.

[0888] Step 6: Propose a vision for the future

[0889] 1. Input: The generative AI model generates a future forecast based on the user's interests, behavioral data, and emotional data.

[0890] 2. Operation: The server saves the generated future projections in a database.

[0891] 3. Input: The saved future projection is ready to be provided to the user.

[0892] 4. Operation: The device presents the future vision to the user in the form of video and text.

[0893] 5. Output: The user uses the presented future vision as a reference to imagine and consider their own future in concrete terms.

[0894] Example: A user is presented with a plan to move to a music-loving area in the future.

[0895] This allows users to receive suggestions for more suitable encounters, memorable experiences, and future prospects based on their profile information, behavioral history data, and emotional data.

[0896] (Application example 2)

[0897] 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."

[0898] There is a lack of systems to promote marriage among today's unmarried people. In particular, there is a lack of methods to utilize users' emotional and behavioral data to provide them with optimal dating opportunities at the right time, and to use virtual spaces to help users visualize actual married life. This makes it difficult for users to imagine suitable dating opportunities and their future lives, leading to a decline in marriage rates.

[0899] The specification processing by the specification 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 inputting profile information of unmarried people, means for saving the profile information in a database, means for analyzing behavioral history data saved in the database and identifying the user's interests, means for suggesting meeting opportunities based on the analysis results, means for sending the suggested meeting opportunities via push notification, means for collecting and analyzing the user's emotional data, means for suggesting meeting opportunities at optimal times based on the analysis results of the emotional data, means for generating and presenting a future vision based on the user's profile information, behavioral history data, and emotional data, and means for constructing a virtual space and conducting meetings and activities within the virtual space. This makes it possible to appropriately utilize the user's emotional and behavioral data to provide optimal meeting opportunities and allow the user to imagine a concrete future life through the virtual space.

[0900] "Single" refers to someone who is not currently married.

[0901] "Profile Information" refers to basic information that identifies an individual, such as a user's name, age, gender, hobbies, and interests.

[0902] A "database" is a system for organizing and storing data in digital form.

[0903] "Behavioral history data" refers to various activity records generated when a user uses the system.

[0904] "Interests" refers to the interest or concern a user has in a particular activity or topic.

[0905] "Analyzing" refers to the detailed analysis of the data obtained using computational and statistical methods to derive specific information or patterns.

[0906] "Meeting opportunities" refers to events and activities that allow users to communicate with other users and build new relationships.

[0907] "Push notification" refers to a technology that sends specific information or messages directly to a user's device.

[0908] "Emotional data" refers to data that indicates the emotional state of a user analyzed from their facial expressions and voice.

[0909] "Virtual space" refers to a virtual three-dimensional space constructed using computer technology.

[0910] "Future projections" refer to diagrams and images that visually represent future lifestyles and situations, generated based on user data.

[0911] "Joint activities" refer to activities undertaken by multiple users who share a common hobby or interest.

[0912] "Building" refers to designing a system or program and putting it into a working form.

[0913] "Notify" refers to the act of informing a user of specific information.

[0914] The present invention is a system that provides various support services to unmarried people leading up to marriage. By combining a generative AI model and an emotion engine, the system analyzes users' interests, behavioral history, and emotional data to provide more appropriate "opportunities to meet people," "unforgettable memories," and "future projections." Specific embodiments of the present invention are described in detail below.

[0915] composition

[0916] This system consists of three main parts: the server, the terminal, and the user. Each part works together to provide optimal support for the user in their search for a partner.

[0917] Hardware and software used

[0918] Server: AWS (Amazon Web Services) is used, DynamoDB is used as the database, and AWS SNS is used as the notification service.

[0919] Device: The user's smartphone or head-mounted display (HMD) (e.g., Oculus Rift).

[0920] Analysis software:

[0921] We use Google Analytics to collect behavioral history data.

[0922] OpenCV (facial expression recognition) and Librosa (voice analysis) are used for emotion data processing.

[0923] TensorFlow and PyTorch are used for generative AI models.

[0924] User Registration

[0925] After installing the app on a smartphone or HMD, users enter their profile information, which is then sent from the device to the server and stored in DynamoDB.

[0926] Data collection and analysis

[0927] User behavioral history data is collected using Google Analytics. The server stores the collected data and analyzes it using generative AI models (TensorFlow or PyTorch) to identify user interests and behavioral patterns. The results of this analysis are stored in a database and used for future recommendations.

[0928] Emotion Recognition and Analysis

[0929] When a user uses a device (smartphone or HMD), facial expression data is collected using OpenCV and voice data is collected using Librosa. This emotion data is sent to the server and analyzed by the emotion engine. The analysis results are also stored in a database.

[0930] Providing opportunities to meet people

[0931] The server then uses the analysis results of the generative AI model and emotion engine to suggest optimal meeting opportunities for users. For example, it generates events and activities that share common interests and sends them to users as push notifications using AWS SNS.

[0932] Providing a memorable experience

[0933] The server extracts users with common hobbies and interests and uses a generative AI model to generate suggestions for joint activities (e.g., cooking classes or camping). The suggestions are sent to users as push notifications, allowing them to experience these activities in a virtual space. Unity is used to design the virtual space, and Photon is used for real-time communication.

[0934] Proposal for a vision of the future

[0935] A generative AI model generates a future vision based on the user's behavioral and emotional data. This future vision (e.g., a proposal for married life or a new home) is created as a 3D model using Blender and stored in AWS S3. It is then presented to the user's device in the form of a video or text.

[0936] Examples and prompts

[0937] As a specific example, if the user's hobby is "traveling," the following processing is performed.

[0938] 1. Analyze past travel events that users have participated in based on their behavioral history.

[0939] 2. Based on the analysis results and the emotion engine results, we suggest a virtual travel experience with someone who loves to travel.

[0940] 3. Present future travel plans and virtual tours of the city you will live in together as a vision of the future.

[0941] Example prompt for generative AI model:

[0942] The user's profile information states that their hobby is traveling. Based on their past behavior, they have previously been interested in traveling to Northern Europe. Based on their sentiment data, they are currently excited about traveling. Please suggest an event where they can virtually experience a Nordic trip with their travel-loving partner. Also, please create a vision of their future married life in a Nordic city.

[0943] In this way, the system aims to improve marriage rates by analyzing users' profile information, behavioral history data, and emotional data, and providing various types of support leading up to marriage.

[0944] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0945] Step 1:

[0946] Users install the app on their device (smartphone or HMD) and enter their profile information, which includes their name, age, gender, hobbies, and interests. The entered information is sent from the device to the server and stored in DynamoDB, which registers the user profile in the database.

[0947] Input: User profile information (name, age, gender, hobbies, etc.)

[0948] Output: User profile stored in database

[0949] Step 2:

[0950] When a user uses the app, behavioral history data is collected through Google Analytics. This data includes which events the user participated in, which content the user viewed, etc. The collected behavioral history data is sent to a server and stored in a database.

[0951] Input: User behavioral history data (event participation history, content viewing history, etc.)

[0952] Output: Behavioral history data stored in a database

[0953] Step 3:

[0954] The server uses generative AI models using TensorFlow and PyTorch to analyze the stored behavioral history data, identifying user interests and behavioral patterns and storing the results in a database.

[0955] Input: Behavioral history data stored in the database

[0956] Output: Analysis results of interests and behavioral patterns

[0957] Step 4:

[0958] When a user uses the device, emotion data is collected using facial recognition with OpenCV and voice analysis with Librosa. This emotion data is sent to the server, where it is analyzed by the emotion engine and the results are stored in a database.

[0959] Input: User's facial and voice data

[0960] Output: Analysis results of emotion data stored in the database

[0961] Step 5:

[0962] The server then proposes optimal meeting opportunities to users based on the analysis results of the generative AI model and emotion engine. The proposals are sent to the user's device as push notifications via AWS SNS. For example, it could suggest that users with common interests attend a music festival.

[0963] Input: Analysis results of interests and behavioral patterns and analysis results of emotional data

[0964] Output: Dating opportunities sent via push notification

[0965] Step 6:

[0966] The server extracts users with common hobbies and interests and uses a generative AI model to generate suggestions for joint activities (e.g., cooking classes or camping). These suggestions are sent to users as push notifications, allowing them to experience these activities in a virtual space. The virtual space is designed using Unity and Photon.

[0967] Input: Data of users with common hobbies and interests

[0968] Output: Collaborative activity suggestions sent via push notification

[0969] Step 7:

[0970] A generative AI model generates a future vision based on the user's behavioral and emotional data. This future vision is created as a 3D model using Blender and stored on AWS S3. By presenting it to the user in video and text format, it becomes easier for them to visualize specific future plans.

[0971] Input: User behavioral and emotional data

[0972] Output: A future vision presented to the user (3D model or video format)

[0973] 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.

[0974] 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.

[0975] 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.

[0976] [Third embodiment]

[0977] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0978] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0979] 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).

[0980] 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.

[0981] 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.

[0982] 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).

[0983] 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.

[0984] 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.

[0985] 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.

[0986] 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.

[0987] 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.

[0988] 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."

[0989] This invention is a system that provides various support to unmarried people until they get married. This system uses generative AI to analyze the user's interests and behavioral history, and provides "opportunities to meet people," "unforgettable memories," and "future visions" necessary for marriage. This system consists of three main parts: a server, a terminal, and a user.

[0990] Program processing

[0991] 1. User Registration

[0992] Describe the process by which a user enters profile information:

[0993] Users download the app and install it on their devices.

[0994] Users enter profile information such as their name, age, gender, hobbies, and interests into the device.

[0995] The terminal sends the input data to the server, which stores the information in a database.

[0996] 2. Data Collection and Analysis

[0997] Explain the process for collecting and analyzing user behavior data:

[0998] Within the app, users can read articles, attend events, and chat with friends.

[0999] The terminal transmits this behavior history data to the server.

[1000] The server successively stores and updates the collected behavioral history data in a database.

[1001] The generative AI analyzes behavioral history data and identifies the user's interests and behavioral patterns.

[1002] 3. Providing opportunities for encounters

[1003] Explain the process we use to find the right matchmaking opportunities for you:

[1004] Based on the analysis results of the generative AI, the server selects the most suitable meeting opportunities for the user (for example, events that share similar hobbies or activities that share common interests).

[1005] The server generates specific suggestions for dating opportunities and creates the body of the push notification.

[1006] The device will send a push notification to the user, who will then participate in the suggested event or activity based on the suggestions received.

[1007] 4. Providing a memorable experience

[1008] Describe the process for delivering experiences to users who share common hobbies and interests:

[1009] The server extracts unmarried people who share common hobbies and interests.

[1010] Based on the extracted information between users, the generation AI generates suggestions for joint activities (e.g., cooking classes, camping).

[1011] The server creates the push notification content, and the device sends the push notification to the user.

[1012] Users can participate in the suggested activities and create unforgettable memories through the experience.

[1013] 5. Proposal of a vision for the future

[1014] Describe the process to help users visualize their future life:

[1015] Generative AI generates a future vision (suggestions for newlywed life and relocation destinations) based on the user's interests and behavioral data.

[1016] The server stores the generated future projections in a database.

[1017] The device will present the user with the saved future vision in video and text format.

[1018] Users can use the presented future projections as a reference to imagine and consider their own specific vision of the future.

[1019] As a concrete example, consider a case where a user's hobby is "music." The system analyzes the user's past behavioral history and suggests local music festivals. It also suggests music workshops that users can participate in together with other users who share the same hobby, and suggests future plans for the user to move to a region with a strong music scene.

[1020] In this way, this system aims to improve marriage rates by analyzing users' profile information and behavioral history data and providing various types of support leading up to marriage.

[1021] The processing flow will be explained below.

[1022] Step 1:

[1023] User enters profile information:

[1024] Users download and install the app on their device, and then enter their profile information, such as their name, age, gender, hobbies, and interests, through the device.

[1025] Step 2:

[1026] The device sends the input data to the server:

[1027] The terminal transmits the input profile information to the server, and the server receives the input data.

[1028] Step 3:

[1029] The server stores the profile information in a database:

[1030] The server stores the received profile information in a database.

[1031] Step 4:

[1032] User takes action in the app:

[1033] Within the app, users can read articles, attend events, and chat with friends.

[1034] Step 5:

[1035] The device sends the activity history to the server:

[1036] User activity data (e.g., which articles you read, which events you attended, which users you chatted with) is sent from your device to a server.

[1037] Step 6:

[1038] The server collects and updates the behavioral history data:

[1039] The server sequentially stores and updates the collected behavioral history data in a database.

[1040] Step 7:

[1041] Generative AI analyzes historical behavioral data:

[1042] The generation AI on the server analyzes the stored behavioral history data and identifies the user's interests and behavioral patterns.

[1043] Step 8:

[1044] The server selects the opportunities and creates suggestions:

[1045] Based on the analysis results of the generation AI, the server selects meeting opportunities to suggest (for example, hobby-based events or activities) and generates the suggestions.

[1046] Step 9:

[1047] The server creates the push notification:

[1048] Create the body of the push notification to the user based on the suggestions generated by the server.

[1049] Step 10:

[1050] The device sends a push notification to the user:

[1051] The device sends the push notification created by the server to the user.

[1052] Step 11:

[1053] The user participates in a suggested dating opportunity:

[1054] Users receive push notifications and act on suggested events and activities.

[1055] Step 12:

[1056] The server extracts users with common hobbies and interests:

[1057] The server extracts users with common hobbies and interests from the database.

[1058] Step 13:

[1059] Generative AI suggests collaborative activities:

[1060] Based on the extracted information between users, the generative AI generates suggestions for joint activities (e.g., cooking classes or camping).

[1061] Step 14:

[1062] The server creates a push notification for the collaboration:

[1063] The server creates the text of the push notification for the collaborative activity based on the suggestions made by the generated AI.

[1064] Step 15:

[1065] The device sends a push notification to the user:

[1066] The device sends a push notification of the collaborative activity created by the server to the user.

[1067] Step 16:

[1068] The user participates in a proposed collaborative activity:

[1069] The user receives a push notification and acts on the suggested collaborative activity.

[1070] Step 17:

[1071] Generative AI creates a vision of the future:

[1072] The server's on-board AI generates a future vision (suggestions for newlywed life and relocation destinations) based on the user's interests and behavioral data.

[1073] Step 18:

[1074] The server saves the generated future view:

[1075] The server stores the generated future projections in a database.

[1076] Step 19:

[1077] The device presents the user with a vision of the future:

[1078] The device presents the future vision stored on the server to the user in the form of video and text.

[1079] Step 20:

[1080] Users consider the future:

[1081] Users use the future projections presented to them as a reference to imagine and consider their own specific future.

[1082] Example 1

[1083] 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."

[1084] In the process of getting married, unmarried people face challenges in finding suitable opportunities to meet people, engaging in joint activities, and having a concrete image of their future life. These challenges make it difficult for unmarried people to find a suitable partner based on their own interests and behavioral patterns, leading to a decline in the marriage rate. The present invention aims to solve these challenges and provide effective support to unmarried people.

[1085] 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.

[1086] In this invention, the server includes means for inputting personal information of unmarried people, means for saving the personal information in a storage device, means for analyzing the activity history data saved in the storage device and using a generative artificial intelligence model to identify the user's interests, means for using the generative artificial intelligence model to suggest meeting opportunities based on the analysis results, and means for sending the suggested meeting opportunities via a notification function. This enables unmarried people to receive suggestions for meeting opportunities and joint activities that match their interests and behavioral patterns, and is expected to improve the marriage rate.

[1087] "Single person" refers to an individual who is not married.

[1088] "Personal information" refers to information that identifies and distinguishes an individual, such as name, age, gender, hobbies, and interests.

[1089] "Storage" refers to a hardware device or electronic storage medium that can store data and retrieve it as needed.

[1090] "Activity history data" refers to data about behavior generated while a user uses the app, such as reading articles, attending events, and chatting.

[1091] A "generative artificial intelligence model" refers to an artificial intelligence technology model that performs analysis based on input data and generates output appropriate for the next action.

[1092] "Interests" refer to specific activities or information that a user is interested in or concerned about.

[1093] "Meeting opportunities" refers to events, activities, and other venues where unmarried people can interact with each other and build relationships.

[1094] "Notification Function" refers to a technical means for transmitting information to a recipient in real time, including push notifications.

[1095] This system uses a generative AI model to support unmarried people until they reach marriage. It consists of three main components: a server, a terminal, and a user.

[1096] First, the user downloads and installs the application onto their device. After installation, the user enters profile information such as name, age, gender, hobbies, and interests. This information is sent from the user device to the server, where it is stored in a database.

[1097] Next, behavioral history data is collected as users read articles, attend events, and chat with friends within the app. This data is also sent from the user's device to the server, which stores it in a database and keeps it up to date. Within the server, a generative AI model analyzes this data and processes it to identify the user's interests and behavioral patterns.

[1098] Based on the analysis results, the generative AI model generates information to suggest optimal meeting opportunities to the user. For example, if the user's hobby is music, the model will suggest information about local music festivals and music workshops. The generated suggestions are converted into push notifications on the server and sent to the user's device. Users who receive the notifications can participate in events and activities based on the suggestions.

[1099] Furthermore, the system will select unmarried people who share common hobbies and interests and suggest joint activities to those users. For example, if one of their hobbies is cooking, it will suggest that they join a cooking class. The details of the proposed joint activities will also be sent to the user via push notification.

[1100] Furthermore, to help users visualize their future lives in concrete terms, the generative AI model generates a future vision based on the user's interests and behavioral data. For example, for a user whose hobby is music, the model will create a vision of moving to a music-loving region or newlywed life. The generated future vision is saved on the server and presented in video or text format on the user's device. This allows users to realistically imagine their future and consider it in detail.

[1101] Examples of prompts include:

[1102] "Based on the user's profile information and behavioral data, suggest events that match their hobbies and interests."

[1103] "Please create opportunities for users with common interests to meet and express them as concrete proposals."

[1104] "Create a vision of the future that interests users and generate explanatory text to present it in video or text format."

[1105] As described above, this system utilizes generative AI models and various analytical technologies to provide various types of support to unmarried people, enabling them to obtain optimal dating opportunities and visions for the future based on their interests and behavioral patterns, and supporting them in the process of getting married.

[1106] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1107] Step 1:

[1108] A user downloads an app and installs it on their device. The input is the application download link and the output is the installed application. A user searches for an app in the App Store or Google Play and clicks the download button to install it.

[1109] Step 2:

[1110] The user opens the app and enters personal information such as name, age, gender, hobbies, and interests. The input is the personal information the user entered into the form, and the output is the personal information temporarily stored on the device. The user enters data into each field in the form displayed on the app's registration screen.

[1111] Step 3:

[1112] The device sends the entered personal information to the server. The input is the personal information entered by the user, and the output is the data sent to the server. When the device completes the input form and presses the send button, the data is encrypted and sent to the server.

[1113] Step 4:

[1114] The server stores the received data in a database. The input is the personal information sent from the terminal, and the output is the personal information stored in the database. The server analyzes the received data and stores it in the appropriate field.

[1115] Step 5:

[1116] When a user reads an article, attends an event, or chats with friends within an app, the input is the user's activity and the output is behavioral history data. As the user uses various functions within the app, that behavioral data is automatically collected.

[1117] Step 6:

[1118] The terminal sends the collected behavioral history data to the server. The input is the user's behavioral history data, and the output is the data sent to the server. At regular intervals, the terminal sends the data to the server using batch processing.

[1119] Step 7:

[1120] The server saves the collected behavioral history data in a database and updates it. The input is the behavioral history data sent from the device, and the output is the updated database. The server adds the new data to the database and updates the links and indexes.

[1121] Step 8:

[1122] The generative AI model analyzes behavioral history data and identifies the user's interests and behavioral patterns. The input is behavioral history data, and the output is the analysis results. The generative AI model uses a machine learning algorithm to cluster the data and extract features.

[1123] Step 9:

[1124] The server selects the best meeting opportunities for the user based on the analysis results of the generated AI model. The input is the analysis results, and the output is the selection results of meeting opportunities. The server filters matching events from the event database.

[1125] Step 10:

[1126] The server generates specific matchmaking suggestions and creates the push notification body. The input is the matchmaking selection results, and the output is the push notification body. Templates are used to generate and customize the notification message.

[1127] Step 11:

[1128] The device sends a push notification to the user. The input is the push notification body, and the output is the notification received by the user device. The backend notification server sends the real-time notification to the user device.

[1129] Step 12:

[1130] The server extracts singles who share common hobbies and interests. The input is interest data, and the output is a list of users who share common hobbies. A database query is used to list users who share common tags.

[1131] Step 13:

[1132] The generative AI model generates specific suggestions for joint activities based on the extracted information between users. The input is a list of users with common interests, and the output is suggestions for joint activities. Multiple options are generated based on the user's interests.

[1133] Step 14:

[1134] The server generates collaborative activity suggestions and creates a push notification. The input is the collaborative activity suggestions and the output is the push notification body. A personalized notification is created based on the suggestions.

[1135] Step 15:

[1136] The device sends a push notification to the user. The input is the push notification body, and the output is the notification received by the user device. The notification server sends the notification to the user device in real time.

[1137] Step 16:

[1138] The generative AI model generates a future forecast based on user interest and behavioral data. The input is interest data and behavioral history data, and the output is a future forecast. Scenarios are depicted using simulation models and past data.

[1139] Step 17:

[1140] The server saves the generated future projections in a database. The input is the future projections, and the output is the future projections saved in the database. A future projection customized for each user is saved.

[1141] Step 18:

[1142] The device presents the saved future vision to the user in the form of video or text. The input is the future vision stored in the database, and the output is the content presented to the user. Create a section within the app to display the content of the future vision.

[1143] (Application example 1)

[1144] 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."

[1145] While there are existing systems that provide various support to unmarried people leading up to marriage, there are no systems that promote opportunities for meeting people while traveling in self-driving vehicles. Furthermore, there is a lack of appropriate matching and suggestions for joint activities that utilize users' travel routes and ride-sharing history, as well as a means to concretely visualize their future lives. This makes it difficult for unmarried people to efficiently find opportunities to meet people while traveling.

[1146] 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.

[1147] In this invention, the server includes means for inputting profile information of unmarried people, means for saving the profile information in a database, means for analyzing behavioral history data saved in the database and identifying user interests, means for suggesting meeting opportunities based on the analysis results, means for sending the suggested meeting opportunities by push notification, means for collecting travel routes and ride-sharing histories of autonomous vehicles, means for saving and analyzing the travel routes and ride-sharing histories in a database, and means for matching users heading in the same direction based on the analysis results and sending the results by push notification. This enables unmarried people to efficiently find meeting opportunities while traveling in autonomous vehicles.

[1148] "Profile Information" is personal information about a user, such as their name, age, gender, hobbies, and interests.

[1149] A "database" is a system for organizing, storing, and managing collected information.

[1150] "Behavioral history data" is a record of a user's past activities and behaviors.

[1151] "Analysis" is the process of examining collected data in detail and finding meaning.

[1152] "Interests" refers to the range of interests or concerns a user has about a particular subject.

[1153] "Meeting Opportunities" are situations or events where users can meet new people.

[1154] "Push Notification" means a notification sent to a User's Device in real time.

[1155] An "autonomous vehicle" is a vehicle that operates automatically without a human driver.

[1156] A "travel route" is the route a vehicle takes.

[1157] "Ride-sharing history" is a record of ride-sharing services a user has used in the past.

[1158] "Matching" is the process of connecting users with common interests and goals.

[1159] A "collaborative activity" is an event or activity in which multiple users participate together.

[1160] A "future vision" is a visual or written suggestion that helps users visualize their future life and activities.

[1161] This invention is a matching system for singles that operates inside an autonomous vehicle. The system is designed to enable singles to efficiently enjoy opportunities to meet people while traveling. The system consists of three main parts: a server, a terminal (display or smartphone of the autonomous vehicle), and a user.

[1162] User Registration

[1163] The server provides a means for users to install the application and enter profile information (such as name, age, gender, hobbies, interests, etc.). The profile information entered by the user is sent to the server via the device and stored in a database. This allows the server to centrally manage individual user information.

[1164] Data collection and analysis

[1165] The server collects the autonomous vehicle's route and ride-sharing history data and stores it in a database. Based on this, the generative AI model analyzes the data and identifies the user's behavioral patterns and interests. Specifically, it analyzes the user's past route and ride-sharing history to understand their behavioral trends. For example, if a user frequently participates in a particular event, that tendency can be analyzed and used to suggest encounters.

[1166] Providing opportunities to meet people

[1167] The server then proposes optimal meeting opportunities to users based on the analysis results of the generation AI. In particular, it matches users heading in the same direction to provide meeting opportunities while traveling in an autonomous vehicle. At this time, the server generates a push notification and sends it to the device. The user can view and participate in the proposed meeting opportunities through their device.

[1168] Specific examples

[1169] When users A and B are traveling long distances to the same area, they discover that they have a common hobby (e.g., music festivals) and suggest an opportunity for them to attend the event together while traveling.

[1170] Providing a memorable experience

[1171] The server extracts singles with common hobbies and interests and generates suggestions for joint activities (e.g., cooking classes, camping) that can be participated in while traveling. These suggestions are automatically generated using AI and sent to users via push notifications on their devices. By participating in the suggested joint activities, users can easily share unforgettable experiences.

[1172] Proposal for a vision of the future

[1173] The server generates a future vision based on the user's interests and behavioral data. For example, generative AI is used to generate specific future images, such as suggestions for newlywed life or where to move. This future vision is stored in a database and presented to the user in video or text format via their device. This allows the user to concretely imagine their future life and make easier plans.

[1174] Prompt Sentence Examples

[1175] “The user is looking to meet someone while traveling long distances. Please suggest attractions and events for the near future. The prompt given to the AI ​​generator is, ‘Please suggest events that the user can enjoy during their trip that share their interests.’”

[1176] This system will enable singles to efficiently find opportunities to meet people while traveling in an autonomous vehicle, and will also provide them with memorable experiences and support in concretely imagining their future lives.

[1177] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1178] Step 1:

[1179] The user enters profile information (such as name, age, gender, hobbies, and interests) into a device (such as a smartphone or the display of an autonomous vehicle). The entered profile information is sent from the device to a server, which receives it and stores it in a database.

[1180] Step 2:

[1181] The user starts traveling in the autonomous vehicle using the application. The terminal collects the vehicle's route and ride-sharing history data in real time and transmits it to the server, which receives it and stores it in a database.

[1182] Step 3:

[1183] The server inputs the behavioral history data stored in the database into the generative AI model to analyze the user's interests. The generative AI model identifies behavioral patterns and hobbies and preferences and outputs the results to the server.

[1184] Step 4:

[1185] The server uses the results of the generative AI model's analysis to suggest optimal meeting opportunities for the user, using an algorithm to determine whether a match with another user heading in the same direction is possible. As a result, an appropriate match is made (e.g., joint attendance at a music festival).

[1186] Step 5:

[1187] The server generates a proposed matchmaking opportunity and sends it as a push notification to the device, which receives the notification and displays it to the user, who then reviews the notification and decides whether to participate in the proposed matchmaking opportunity.

[1188] Step 6:

[1189] The server extracts users with common hobbies and interests and suggests activities they can participate in together (e.g., cooking classes or camping). These suggestions are also automatically generated using a generative AI model and sent to the device as a push notification from the server. The device displays the notification to the user, who then decides whether or not to participate in the activity.

[1190] Step 7:

[1191] The server generates a future vision based on the user's interests and behavioral data and stores it in a database. The generated future vision is presented to the user via their device in the form of video or text. The device displays content that allows the user to concretely imagine what life will be like in the future.

[1192] Step 8:

[1193] To help users visualize their future lives, the generative AI model receives specific prompts, such as "Please suggest events that users can enjoy during their trip that involve common hobbies," and the model receives appropriate output.

[1194] Through these steps, the system will enable singles to efficiently find opportunities to meet people while traveling in an autonomous vehicle, and will also provide them with memorable experiences and support in concretely imagining their future lives.

[1195] 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.

[1196] This invention is a system that provides various support to unmarried people leading up to marriage, and in particular, it is a system that combines an emotion engine that recognizes the user's emotions. This system uses generative AI to analyze the user's interests and behavioral history, and further analyzes the user's emotional data using an emotion engine, to provide more appropriate "opportunities to meet," "unforgettable memories," and "future visions." This system consists of three main parts: a server, a terminal, and the user.

[1197] Program processing

[1198] 1. User Registration

[1199] Describe the process by which a user enters profile information:

[1200] Users download and install the app on their devices, then enter their profile information, such as their name, age, gender, hobbies, and interests, into the device. The device then sends the information to the server, which then stores it in a database.

[1201] 2. Data Collection and Analysis

[1202] Explain the process for collecting and analyzing user behavior data:

[1203] Within the app, users read articles, participate in events, and chat with friends. The device sends this behavioral history data to the server, which then stores and updates the collected behavioral history data in a database. The generation AI analyzes the behavioral history data and identifies the user's interests and behavioral patterns.

[1204] 3. Emotion Recognition and Analysis

[1205] Explain the process of recognizing and analyzing user emotions:

[1206] The device collects facial and voice data when the user uses the app. The device sends this data to the server as emotional data. The server's emotional engine analyzes the emotional data and identifies the user's current emotional state.

[1207] 4. Providing opportunities for encounters

[1208] Explain the process we use to find the right matchmaking opportunities for you:

[1209] The server selects the most suitable meeting opportunities for the user (for example, events that match hobbies or activities that share common interests) based on the analysis results of the generation AI and the emotion engine. The server generates specific suggestions for meeting opportunities and creates the body of the push notification. The device sends the push notification to the user, and the user participates in the suggested events or activities based on the received suggestions.

[1210] 5. Provide a memorable experience

[1211] Describe the process for delivering experiences to users who share common hobbies and interests:

[1212] The server extracts unmarried people who share common hobbies and interests. The generation AI generates suggestions for joint activities (e.g., cooking classes, camping) based on the extracted information about users and their emotions. The server creates the push notification content, and the device sends the push notification to the user. The user participates in the suggested activity and creates unforgettable memories through the experience.

[1213] 6. Proposal of a vision for the future

[1214] Describe the process to help users visualize their future life:

[1215] The AI ​​generates a future vision (suggestions for newlywed life or relocation destinations) based on the user's interests, behavioral data, and emotional data. The server stores the generated future vision in a database. The device presents the saved future vision to the user in video or text format. The user can use the presented future vision as a reference to imagine and consider their own specific vision of the future.

[1216] As a concrete example, consider a case where a user's hobby is "music." The system analyzes the user's past behavioral history and suggests local music festivals. Furthermore, based on the results of the emotion engine's analysis of the user's emotional data, the system makes suggestions to the user at appropriate times. It also suggests music workshops that users can participate in together with other users who share the same hobby, and presents a vision of the future of relocating to a region with a strong music scene.

[1217] In this way, this system aims to improve marriage rates by analyzing users' profile information, behavioral history data, and emotional data, and providing various types of support leading up to marriage.

[1218] The processing flow will be explained below.

[1219] Step 1:

[1220] User enters profile information:

[1221] Users download and install the app on their device, then enter their profile information, such as their name, age, gender, hobbies, and interests.

[1222] Step 2:

[1223] The device sends the input data to the server:

[1224] The terminal transmits the input profile information to the server, and the server receives the input data.

[1225] Step 3:

[1226] The server stores the profile information in a database:

[1227] The server stores the received profile information in a database.

[1228] Step 4:

[1229] User takes action in the app:

[1230] Within the app, users can read articles, attend events, and chat with friends.

[1231] Step 5:

[1232] The device sends the activity history data to the server:

[1233] Data about each user's activity (e.g., articles viewed, events attended, chat history) is sent from the device to the server.

[1234] Step 6:

[1235] The server collects the behavioral history data and stores it in a database:

[1236] The server stores the collected behavioral history data in a database and updates it accordingly.

[1237] Step 7:

[1238] The emotion engine collects emotion data:

[1239] The device collects facial expressions and voice data when the user uses the app and sends it to the server as emotional data.

[1240] Step 8:

[1241] The server analyzes the emotion data:

[1242] An emotion engine in the server analyzes the emotion data and identifies the user's current emotional state.

[1243] Step 9:

[1244] Generative AI analyzes behavioral and emotional data:

[1245] The generation AI on the server analyzes behavioral history data and emotional data to identify the user's interests and behavioral patterns.

[1246] Step 10:

[1247] The server selects the opportunities and creates suggestions:

[1248] Based on the analysis results of the generation AI and emotion engine, the server selects meeting opportunities (e.g., hobby-based events and content) to suggest and generates the proposed content.

[1249] Step 11:

[1250] The server creates the push notification content:

[1251] Create the push notification body based on the suggestions generated by the server.

[1252] Step 12:

[1253] The device sends a push notification to the user:

[1254] The device forwards the contents of the push notification sent from the server to the user.

[1255] Step 13:

[1256] The user participates in a suggested dating opportunity:

[1257] Users receive push notifications and act on suggested events and activities.

[1258] Step 14:

[1259] The server extracts users with common hobbies and interests:

[1260] The server extracts users with common hobbies and interests from the database.

[1261] Step 15:

[1262] Generative AI suggests collaborative activities:

[1263] Based on the extracted information between users, a generation AI on the server generates suggestions for joint activities (e.g., cooking classes, camping).

[1264] Step 16:

[1265] The server creates a push notification for the collaboration:

[1266] The server creates the text of the push notification for the collaborative activity based on the suggestions made by the generation AI.

[1267] Step 17:

[1268] The device sends a push notification to the user about the collaborative activity:

[1269] The terminal forwards the push notification of the collaborative activity sent from the server to the user.

[1270] Step 18:

[1271] The user participates in a proposed collaborative activity:

[1272] Users receive push notifications and act on suggested collaborative activities.

[1273] Step 19:

[1274] Generative AI creates a vision of the future:

[1275] The generation AI on the server generates a future vision (suggestions for newlywed life and relocation destinations) based on the user's interests, behavioral data, and emotional data.

[1276] Step 20:

[1277] The server saves the generated future view:

[1278] The server stores the generated future projections in a database.

[1279] Step 21:

[1280] The device presents the user with a vision of the future:

[1281] The device presents the future vision stored on the server to the user in video or text format.

[1282] Step 22:

[1283] Users consider the future:

[1284] Users can use the presented future projections to concretely imagine and consider their own future.

[1285] Example 2

[1286] 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."

[1287] Unmarried people face difficulties in finding a partner and building relationships in the process leading up to marriage. In particular, there is no system that can properly grasp a user's interests and emotional state and suggest opportunities to meet or joint activities based on that information, making it difficult for unmarried people to build deep relationships with each other.

[1288] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1289] In this invention, the server includes means for inputting profile information of unmarried people, means for saving the profile information in a database, means for collecting behavioral history data, means for analyzing the behavioral history data saved in the database and identifying the user's interests, means for collecting user emotional data, means for analyzing the emotional data and identifying the user's emotional state, means for suggesting meeting opportunities based on the analysis results, and means for sending the suggested meeting opportunities by push notification. This makes it possible to suggest appropriate meeting opportunities and joint activities based on the user's interests and emotional state.

[1290] "Single" means a person who is not legally married.

[1291] "Profile information" refers to personal information such as name, age, gender, hobbies, and interests.

[1292] A "database" is a digital recording system that stores information in an organized manner and makes it easy to search and manage.

[1293] "Behavioral history data" is a record of various activities and operations performed by users within the app.

[1294] "Interests" are the things or areas that a user is particularly interested in and finds appealing.

[1295] "User" means an individual who uses this system.

[1296] "Emotional data" refers to information about emotions obtained from the user's facial expressions, voice, etc.

[1297] An "emotional state" is the psychological state or feeling a user is experiencing at a given moment.

[1298] "Analysis results" are conclusions or information obtained through data analysis.

[1299] "Dating opportunities" are events and activities that allow singles to meet other singles.

[1300] "Push notification" means a notification that the system sends to a user's device in real time.

[1301] "Joint activities" are events or activities that single people with common hobbies or interests participate in together.

[1302] "Future Visions" are simulations or scenarios that concretely illustrate the user's future possibilities.

[1303] The present invention is a system that provides various support services to unmarried people leading up to marriage, and in particular, it is a system that combines an emotion engine that recognizes the user's emotions. This system is implemented using the following hardware and software.

[1304] Hardware and software used

[1305] Terminal: A device that is directly operated by the user, such as a smartphone, tablet, or PC.

[1306] Server: The server that stores, processes, and notifies data.

[1307] Database: A relational database management system (RDBMS) such as MySQL or PostgreSQL.

[1308] Generative AI model: A machine learning model for analyzing user behavioral history and interests.

[1309] Emotion engine: A software module that analyzes a user's facial expressions and voice data to identify emotions.

[1310] Processing Overview

[1311] 1. User Registration

[1312] Users download and install the app on their devices such as smartphones or tablets. After that, they launch the app and enter their profile information, such as their name, age, gender, hobbies, and interests. The entered information is sent from the device to a server, which then stores it in a database.

[1313] 2. Data Collection and Analysis

[1314] Within the app, users read articles, participate in events, and chat with friends. The device sequentially sends this behavioral history data to the server, which then stores it in a database. The generative AI model analyzes the behavioral history data to identify the user's interests and behavioral patterns.

[1315] 3. Emotion Recognition and Analysis

[1316] When a user uses the app, the device uses the front camera and microphone to collect facial and voice data, which is then sent from the device to a server where an emotion engine analyzes the data to identify the user's current emotional state.

[1317] 4. Providing opportunities for encounters

[1318] The server proposes optimal meeting opportunities to users based on the analysis results of the generative AI model and emotion engine. Specifically, it selects events and activities that match users' interests and sends them to the device as push notifications. Users can then participate in events and activities based on the suggestions they receive.

[1319] 5. Provide a memorable experience

[1320] The server extracts singles with common hobbies and interests from a database and uses a generative AI model to suggest joint activities. The server then creates a push notification, which the device sends to the user. The user then participates in the suggested activities and creates unforgettable memories.

[1321] 6. Proposal of a vision for the future

[1322] The generative AI model generates a future vision based on the user's interests, behavioral data, and emotional data. The server stores the generated future vision in a database, and the device presents it to the user in video or text format. The user can use the presented future vision as a reference to imagine and consider their own specific vision of the future.

[1323] Specific examples

[1324] For example, if a user's hobby is "music," the system will analyze the user's past behavioral history and suggest local music festivals. It will also make appropriate suggestions to the user based on the results of the emotion engine's analysis of their emotional data. It will also suggest music workshops that users can participate in together with other users who share the same hobby, and in the future, it will present a vision of moving to a region with a strong music scene.

[1325] Prompt Sentence Examples

[1326] The following prompt sentences are fed into the generative AI model for analysis:

[1327] "User A's hobby is music. Based on past behavioral history data, would it be appropriate to suggest a local music festival this weekend? Furthermore, how can we suggest joint activities with User B, who shares the same musical interest?"

[1328] As described above, the present invention analyzes a user's profile information, behavioral history data, and emotional data, and provides various types of support leading up to marriage.

[1329] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1330] Step 1: User Registration

[1331] 1. Input: The user downloads the app and installs it on their device.

[1332] 2. Input: The user enters their profile information (name, age, gender, hobbies, interests, etc.).

[1333] 3. Operation: The device sends the entered profile information to the server.

[1334] 4. Output: The server stores the received profile information in a database.

[1335] Example: If a user inputs that their hobby is "music," that hobby information is saved in a database.

[1336] Step 2: Data collection and analysis

[1337] 1. Input: A user reads an article, attends an event, or chats with a friend within the app.

[1338] 2. Operation: The device sequentially sends this behavioral history data to the server.

[1339] 3. Input: The server saves and updates the behavioral history data it receives in the database.

[1340] 4. Action: The generative AI model analyzes historical behavioral data and identifies user interests.

[1341] 5. Output: The analysis results from the generation AI are obtained from the server, and the user's interests and behavioral patterns are identified.

[1342] Example: If a user frequently reads articles about "music festivals," the generative AI will identify that the user is interested in music festivals.

[1343] Step 3: Emotion Recognition and Analysis

[1344] 1. Input: The device collects facial and voice data when the user uses the app.

[1345] 2. Operation: The device sends the collected facial and voice data to the server as emotion data.

[1346] 3. Input: The server passes the received emotion data to the emotion engine.

[1347] 4. Action: The emotion engine analyzes the emotion data and identifies the user's current emotional state.

[1348] 5. Output: The server obtains the analysis results from the emotion engine and identifies the user's emotional state.

[1349] Example: If a smiling expression is detected while a user is reading a music article, the emotion engine identifies the user as "happy."

[1350] Step 4: Providing opportunities for encounters

[1351] 1. Input: The analysis results of the generation AI and emotion engine are integrated on the server.

[1352] 2. Operation: Based on the analysis results, the server suggests the best meeting opportunities to the user.

[1353] 3. Input: Select events and activities that suit your interests as suggestions.

[1354] 4. Action: The server generates specific suggestions for dating opportunities and creates the body of the push notification.

[1355] 5. Output: The device sends a push notification to the user, and the user receives the notification.

[1356] Example: A user receives a push notification saying, "We encourage you to attend the music festival this weekend."

[1357] Step 5: Deliver a memorable experience

[1358] 1. Input: The server extracts from the database singles who share common hobbies and interests.

[1359] 2. Operation: The generative AI model generates suggestions for joint activities based on the extracted information and emotional data between users.

[1360] 3. Input: Suggestions for events and experiences based on common interests are generated.

[1361] 4. Operation: The server creates the push notification content, and the device sends the push notification to the user.

[1362] 5. Output: The user participates in the suggested activity and creates unforgettable memories through the experience.

[1363] Example: A user receives suggestions for cooking classes to join with other users who share the same interests.

[1364] Step 6: Propose a vision for the future

[1365] 1. Input: The generative AI model generates a future forecast based on the user's interests, behavioral data, and emotional data.

[1366] 2. Operation: The server saves the generated future projections in a database.

[1367] 3. Input: The saved future projection is ready to be provided to the user.

[1368] 4. Operation: The device presents the future vision to the user in the form of video and text.

[1369] 5. Output: The user uses the presented future vision as a reference to imagine and consider their own future in concrete terms.

[1370] Example: A user is presented with a plan to move to a music-loving area in the future.

[1371] This allows users to receive suggestions for more suitable encounters, memorable experiences, and future prospects based on their profile information, behavioral history data, and emotional data.

[1372] (Application example 2)

[1373] 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."

[1374] There is a lack of systems to promote marriage among today's unmarried people. In particular, there is a lack of methods to utilize users' emotional and behavioral data to provide them with optimal dating opportunities at the right time, and to use virtual spaces to help users visualize actual married life. This makes it difficult for users to imagine suitable dating opportunities and their future lives, leading to a decline in marriage rates.

[1375] The specification processing by the specification 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 inputting profile information of unmarried people, means for saving the profile information in a database, means for analyzing behavioral history data saved in the database and identifying the user's interests, means for suggesting meeting opportunities based on the analysis results, means for sending the suggested meeting opportunities via push notification, means for collecting and analyzing the user's emotional data, means for suggesting meeting opportunities at optimal times based on the analysis results of the emotional data, means for generating and presenting a future vision based on the user's profile information, behavioral history data, and emotional data, and means for constructing a virtual space and conducting meetings and activities within the virtual space. This makes it possible to appropriately utilize the user's emotional and behavioral data to provide optimal meeting opportunities and allow the user to imagine a concrete future life through the virtual space.

[1376] "Single" refers to someone who is not currently married.

[1377] "Profile Information" refers to basic information that identifies an individual, such as a user's name, age, gender, hobbies, and interests.

[1378] A "database" is a system for organizing and storing data in digital form.

[1379] "Behavioral history data" refers to various activity records generated when a user uses the system.

[1380] "Interests" refers to the interest or concern a user has in a particular activity or topic.

[1381] "Analyzing" refers to the detailed analysis of the data obtained using computational and statistical methods to derive specific information or patterns.

[1382] "Meeting opportunities" refers to events and activities that allow users to communicate with other users and build new relationships.

[1383] "Push notification" refers to a technology that sends specific information or messages directly to a user's device.

[1384] "Emotional data" refers to data that indicates the emotional state of a user analyzed from their facial expressions and voice.

[1385] "Virtual space" refers to a virtual three-dimensional space constructed using computer technology.

[1386] "Future projections" refer to diagrams and images that visually represent future lifestyles and situations, generated based on user data.

[1387] "Joint activities" refer to activities undertaken by multiple users who share a common hobby or interest.

[1388] "Building" refers to designing a system or program and putting it into a working form.

[1389] "Notify" refers to the act of informing a user of specific information.

[1390] The present invention is a system that provides various support services to unmarried people leading up to marriage. By combining a generative AI model and an emotion engine, the system analyzes users' interests, behavioral history, and emotional data to provide more appropriate "opportunities to meet people," "unforgettable memories," and "future projections." Specific embodiments of the present invention are described in detail below.

[1391] composition

[1392] This system consists of three main parts: the server, the terminal, and the user. Each part works together to provide optimal support for the user in their search for a partner.

[1393] Hardware and software used

[1394] Server: AWS (Amazon Web Services) is used, DynamoDB is used as the database, and AWS SNS is used as the notification service.

[1395] Device: The user's smartphone or head-mounted display (HMD) (e.g., Oculus Rift).

[1396] Analysis software:

[1397] We use Google Analytics to collect behavioral history data.

[1398] OpenCV (facial expression recognition) and Librosa (voice analysis) are used for emotion data processing.

[1399] TensorFlow and PyTorch are used for generative AI models.

[1400] User Registration

[1401] After installing the app on a smartphone or HMD, users enter their profile information, which is then sent from the device to the server and stored in DynamoDB.

[1402] Data collection and analysis

[1403] User behavioral history data is collected using Google Analytics. The server stores the collected data and analyzes it using generative AI models (TensorFlow or PyTorch) to identify user interests and behavioral patterns. The results of this analysis are stored in a database and used for future recommendations.

[1404] Emotion Recognition and Analysis

[1405] When a user uses a device (smartphone or HMD), facial expression data is collected using OpenCV and voice data is collected using Librosa. This emotion data is sent to the server and analyzed by the emotion engine. The analysis results are also stored in a database.

[1406] Providing opportunities to meet people

[1407] The server then uses the analysis results of the generative AI model and emotion engine to suggest optimal meeting opportunities for users. For example, it generates events and activities that share common interests and sends them to users as push notifications using AWS SNS.

[1408] Providing a memorable experience

[1409] The server extracts users with common hobbies and interests and uses a generative AI model to generate suggestions for joint activities (e.g., cooking classes or camping). The suggestions are sent to users as push notifications, allowing them to experience these activities in a virtual space. Unity is used to design the virtual space, and Photon is used for real-time communication.

[1410] Proposal for a vision of the future

[1411] A generative AI model generates a future vision based on the user's behavioral and emotional data. This future vision (e.g., a proposal for married life or a new home) is created as a 3D model using Blender and stored in AWS S3. It is then presented to the user's device in the form of a video or text.

[1412] Examples and prompts

[1413] As a specific example, if the user's hobby is "traveling," the following processing is performed.

[1414] 1. Analyze past travel events that users have participated in based on their behavioral history.

[1415] 2. Based on the analysis results and the emotion engine results, we suggest a virtual travel experience with someone who loves to travel.

[1416] 3. Present future travel plans and virtual tours of the city you will live in together as a vision of the future.

[1417] Example prompt for generative AI model:

[1418] The user's profile information states that their hobby is traveling. Based on their past behavior, they have previously been interested in traveling to Northern Europe. Based on their sentiment data, they are currently excited about traveling. Please suggest an event where they can virtually experience a Nordic trip with their travel-loving partner. Also, please create a vision of their future married life in a Nordic city.

[1419] In this way, the system aims to improve marriage rates by analyzing users' profile information, behavioral history data, and emotional data, and providing various types of support leading up to marriage.

[1420] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1421] Step 1:

[1422] Users install the app on their device (smartphone or HMD) and enter their profile information, which includes their name, age, gender, hobbies, and interests. The entered information is sent from the device to the server and stored in DynamoDB, which registers the user profile in the database.

[1423] Input: User profile information (name, age, gender, hobbies, etc.)

[1424] Output: User profile stored in database

[1425] Step 2:

[1426] When a user uses the app, behavioral history data is collected through Google Analytics. This data includes which events the user participated in, which content the user viewed, etc. The collected behavioral history data is sent to a server and stored in a database.

[1427] Input: User behavioral history data (event participation history, content viewing history, etc.)

[1428] Output: Behavioral history data stored in a database

[1429] Step 3:

[1430] The server uses generative AI models using TensorFlow and PyTorch to analyze the stored behavioral history data, identifying user interests and behavioral patterns and storing the results in a database.

[1431] Input: Behavioral history data stored in the database

[1432] Output: Analysis results of interests and behavioral patterns

[1433] Step 4:

[1434] When a user uses the device, emotion data is collected using facial recognition with OpenCV and voice analysis with Librosa. This emotion data is sent to the server, where it is analyzed by the emotion engine and the results are stored in a database.

[1435] Input: User's facial and voice data

[1436] Output: Analysis results of emotion data stored in the database

[1437] Step 5:

[1438] The server then proposes optimal meeting opportunities to users based on the analysis results of the generative AI model and emotion engine. The proposals are sent to the user's device as push notifications via AWS SNS. For example, it could suggest that users with common interests attend a music festival.

[1439] Input: Analysis results of interests and behavioral patterns and analysis results of emotional data

[1440] Output: Dating opportunities sent via push notification

[1441] Step 6:

[1442] The server extracts users with common hobbies and interests and uses a generative AI model to generate suggestions for joint activities (e.g., cooking classes or camping). These suggestions are sent to users as push notifications, allowing them to experience these activities in a virtual space. The virtual space is designed using Unity and Photon.

[1443] Input: Data of users with common hobbies and interests

[1444] Output: Collaborative activity suggestions sent via push notification

[1445] Step 7:

[1446] A generative AI model generates a future vision based on the user's behavioral and emotional data. This future vision is created as a 3D model using Blender and stored on AWS S3. By presenting it to the user in video and text format, it becomes easier for them to visualize specific future plans.

[1447] Input: User behavioral and emotional data

[1448] Output: A future vision presented to the user (3D model or video format)

[1449] 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.

[1450] 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.

[1451] 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.

[1452] [Fourth embodiment]

[1453] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1454] 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.

[1455] 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).

[1456] 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.

[1457] 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.

[1458] 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).

[1459] 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.

[1460] 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.

[1461] 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.

[1462] 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.

[1463] 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.

[1464] 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.

[1465] 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."

[1466] This invention is a system that provides various support to unmarried people until they get married. This system uses generative AI to analyze the user's interests and behavioral history, and provides "opportunities to meet people," "unforgettable memories," and "future visions" necessary for marriage. This system consists of three main parts: a server, a terminal, and a user.

[1467] Program processing

[1468] 1. User Registration

[1469] Describe the process by which a user enters profile information:

[1470] Users download the app and install it on their devices.

[1471] Users enter profile information such as their name, age, gender, hobbies, and interests into the device.

[1472] The terminal sends the input data to the server, which stores the information in a database.

[1473] 2. Data Collection and Analysis

[1474] Explain the process for collecting and analyzing user behavior data:

[1475] Within the app, users can read articles, attend events, and chat with friends.

[1476] The terminal transmits this behavior history data to the server.

[1477] The server successively stores and updates the collected behavioral history data in a database.

[1478] The generative AI analyzes behavioral history data and identifies the user's interests and behavioral patterns.

[1479] 3. Providing opportunities for encounters

[1480] Explain the process we use to find the right matchmaking opportunities for you:

[1481] Based on the analysis results of the generative AI, the server selects the most suitable meeting opportunities for the user (for example, events that share similar hobbies or activities that share common interests).

[1482] The server generates specific suggestions for dating opportunities and creates the body of the push notification.

[1483] The device will send a push notification to the user, who will then participate in the suggested event or activity based on the suggestions received.

[1484] 4. Providing a memorable experience

[1485] Describe the process for delivering experiences to users who share common hobbies and interests:

[1486] The server extracts unmarried people who share common hobbies and interests.

[1487] Based on the extracted information between users, the generation AI generates suggestions for joint activities (e.g., cooking classes, camping).

[1488] The server creates the push notification content, and the device sends the push notification to the user.

[1489] Users can participate in the suggested activities and create unforgettable memories through the experience.

[1490] 5. Proposal of a vision for the future

[1491] Describe the process to help users visualize their future life:

[1492] Generative AI generates a future vision (suggestions for newlywed life and relocation destinations) based on the user's interests and behavioral data.

[1493] The server stores the generated future projections in a database.

[1494] The device will present the user with the saved future vision in video and text format.

[1495] Users can use the presented future projections as a reference to imagine and consider their own specific vision of the future.

[1496] As a concrete example, consider a case where a user's hobby is "music." The system analyzes the user's past behavioral history and suggests local music festivals. It also suggests music workshops that users can participate in together with other users who share the same hobby, and suggests future plans for the user to move to a region with a strong music scene.

[1497] In this way, this system aims to improve marriage rates by analyzing users' profile information and behavioral history data and providing various types of support leading up to marriage.

[1498] The processing flow will be explained below.

[1499] Step 1:

[1500] User enters profile information:

[1501] Users download and install the app on their device, and then enter their profile information, such as their name, age, gender, hobbies, and interests, through the device.

[1502] Step 2:

[1503] The device sends the input data to the server:

[1504] The terminal transmits the input profile information to the server, and the server receives the input data.

[1505] Step 3:

[1506] The server stores the profile information in a database:

[1507] The server stores the received profile information in a database.

[1508] Step 4:

[1509] User takes action in the app:

[1510] Within the app, users can read articles, attend events, and chat with friends.

[1511] Step 5:

[1512] The device sends the activity history to the server:

[1513] User activity data (e.g., which articles you read, which events you attended, which users you chatted with) is sent from your device to a server.

[1514] Step 6:

[1515] The server collects and updates the behavioral history data:

[1516] The server sequentially stores and updates the collected behavioral history data in a database.

[1517] Step 7:

[1518] Generative AI analyzes historical behavioral data:

[1519] The generation AI on the server analyzes the stored behavioral history data and identifies the user's interests and behavioral patterns.

[1520] Step 8:

[1521] The server selects the opportunities and creates suggestions:

[1522] Based on the analysis results of the generation AI, the server selects meeting opportunities to suggest (for example, hobby-based events or activities) and generates the suggestions.

[1523] Step 9:

[1524] The server creates the push notification:

[1525] Create the body of the push notification to the user based on the suggestions generated by the server.

[1526] Step 10:

[1527] The device sends a push notification to the user:

[1528] The device sends the push notification created by the server to the user.

[1529] Step 11:

[1530] The user participates in a suggested dating opportunity:

[1531] Users receive push notifications and act on suggested events and activities.

[1532] Step 12:

[1533] The server extracts users with common hobbies and interests:

[1534] The server extracts users with common hobbies and interests from the database.

[1535] Step 13:

[1536] Generative AI suggests collaborative activities:

[1537] Based on the extracted information between users, the generative AI generates suggestions for joint activities (e.g., cooking classes or camping).

[1538] Step 14:

[1539] The server creates a push notification for the collaboration:

[1540] The server creates the text of the push notification for the collaborative activity based on the suggestions made by the generated AI.

[1541] Step 15:

[1542] The device sends a push notification to the user:

[1543] The device sends a push notification of the collaborative activity created by the server to the user.

[1544] Step 16:

[1545] The user participates in a proposed collaborative activity:

[1546] The user receives a push notification and acts on the suggested collaborative activity.

[1547] Step 17:

[1548] Generative AI creates a vision of the future:

[1549] The server's on-board AI generates a future vision (suggestions for newlywed life and relocation destinations) based on the user's interests and behavioral data.

[1550] Step 18:

[1551] The server saves the generated future view:

[1552] The server stores the generated future projections in a database.

[1553] Step 19:

[1554] The device presents the user with a vision of the future:

[1555] The device presents the future vision stored on the server to the user in the form of video and text.

[1556] Step 20:

[1557] Users consider the future:

[1558] Users use the future projections presented to them as a reference to imagine and consider their own specific future.

[1559] Example 1

[1560] 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."

[1561] In the process of getting married, unmarried people face challenges in finding suitable opportunities to meet people, engaging in joint activities, and having a concrete image of their future life. These challenges make it difficult for unmarried people to find a suitable partner based on their own interests and behavioral patterns, leading to a decline in the marriage rate. The present invention aims to solve these challenges and provide effective support to unmarried people.

[1562] 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.

[1563] In this invention, the server includes means for inputting personal information of unmarried people, means for saving the personal information in a storage device, means for analyzing the activity history data saved in the storage device and using a generative artificial intelligence model to identify the user's interests, means for using the generative artificial intelligence model to suggest meeting opportunities based on the analysis results, and means for sending the suggested meeting opportunities via a notification function. This enables unmarried people to receive suggestions for meeting opportunities and joint activities that match their interests and behavioral patterns, and is expected to improve the marriage rate.

[1564] "Single person" refers to an individual who is not married.

[1565] "Personal information" refers to information that identifies and distinguishes an individual, such as name, age, gender, hobbies, and interests.

[1566] "Storage" refers to a hardware device or electronic storage medium that can store data and retrieve it as needed.

[1567] "Activity history data" refers to data about behavior generated while a user uses the app, such as reading articles, attending events, and chatting.

[1568] A "generative artificial intelligence model" refers to an artificial intelligence technology model that performs analysis based on input data and generates output appropriate for the next action.

[1569] "Interests" refer to specific activities or information that a user is interested in or concerned about.

[1570] "Meeting opportunities" refers to events, activities, and other venues where unmarried people can interact with each other and build relationships.

[1571] "Notification Function" refers to a technical means for transmitting information to a recipient in real time, including push notifications.

[1572] This system uses a generative AI model to support unmarried people until they reach marriage. It consists of three main components: a server, a terminal, and a user.

[1573] First, the user downloads and installs the application onto their device. After installation, the user enters profile information such as name, age, gender, hobbies, and interests. This information is sent from the user device to the server, where it is stored in a database.

[1574] Next, behavioral history data is collected as users read articles, attend events, and chat with friends within the app. This data is also sent from the user's device to the server, which stores it in a database and keeps it up to date. Within the server, a generative AI model analyzes this data and processes it to identify the user's interests and behavioral patterns.

[1575] Based on the analysis results, the generative AI model generates information to suggest optimal meeting opportunities to the user. For example, if the user's hobby is music, the model will suggest information about local music festivals and music workshops. The generated suggestions are converted into push notifications on the server and sent to the user's device. Users who receive the notifications can participate in events and activities based on the suggestions.

[1576] Furthermore, the system will select unmarried people who share common hobbies and interests and suggest joint activities to those users. For example, if one of their hobbies is cooking, it will suggest that they join a cooking class. The details of the proposed joint activities will also be sent to the user via push notification.

[1577] Furthermore, to help users visualize their future lives in concrete terms, the generative AI model generates a future vision based on the user's interests and behavioral data. For example, for a user whose hobby is music, the model will create a vision of moving to a music-loving region or newlywed life. The generated future vision is saved on the server and presented in video or text format on the user's device. This allows users to realistically imagine their future and consider it in detail.

[1578] Examples of prompts include:

[1579] "Based on the user's profile information and behavioral data, suggest events that match their hobbies and interests."

[1580] "Please create opportunities for users with common interests to meet and express them as concrete proposals."

[1581] "Create a vision of the future that interests users and generate explanatory text to present it in video or text format."

[1582] As described above, this system utilizes generative AI models and various analytical technologies to provide various types of support to unmarried people, enabling them to obtain optimal dating opportunities and visions for the future based on their interests and behavioral patterns, and supporting them in the process of getting married.

[1583] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1584] Step 1:

[1585] A user downloads an app and installs it on their device. The input is the application download link and the output is the installed application. A user searches for an app in the App Store or Google Play and clicks the download button to install it.

[1586] Step 2:

[1587] The user opens the app and enters personal information such as name, age, gender, hobbies, and interests. The input is the personal information the user entered into the form, and the output is the personal information temporarily stored on the device. The user enters data into each field in the form displayed on the app's registration screen.

[1588] Step 3:

[1589] The device sends the entered personal information to the server. The input is the personal information entered by the user, and the output is the data sent to the server. When the device completes the input form and presses the send button, the data is encrypted and sent to the server.

[1590] Step 4:

[1591] The server stores the received data in a database. The input is the personal information sent from the terminal, and the output is the personal information stored in the database. The server analyzes the received data and stores it in the appropriate field.

[1592] Step 5:

[1593] When a user reads an article, attends an event, or chats with friends within an app, the input is the user's activity and the output is behavioral history data. As the user uses various functions within the app, that behavioral data is automatically collected.

[1594] Step 6:

[1595] The terminal sends the collected behavioral history data to the server. The input is the user's behavioral history data, and the output is the data sent to the server. At regular intervals, the terminal sends the data to the server using batch processing.

[1596] Step 7:

[1597] The server saves the collected behavioral history data in a database and updates it. The input is the behavioral history data sent from the device, and the output is the updated database. The server adds the new data to the database and updates the links and indexes.

[1598] Step 8:

[1599] The generative AI model analyzes behavioral history data and identifies the user's interests and behavioral patterns. The input is behavioral history data, and the output is the analysis results. The generative AI model uses a machine learning algorithm to cluster the data and extract features.

[1600] Step 9:

[1601] The server selects the best meeting opportunities for the user based on the analysis results of the generated AI model. The input is the analysis results, and the output is the selection results of meeting opportunities. The server filters matching events from the event database.

[1602] Step 10:

[1603] The server generates specific matchmaking suggestions and creates the push notification body. The input is the matchmaking selection results, and the output is the push notification body. Templates are used to generate and customize the notification message.

[1604] Step 11:

[1605] The device sends a push notification to the user. The input is the push notification body, and the output is the notification received by the user device. The backend notification server sends the real-time notification to the user device.

[1606] Step 12:

[1607] The server extracts singles who share common hobbies and interests. The input is interest data, and the output is a list of users who share common hobbies. A database query is used to list users who share common tags.

[1608] Step 13:

[1609] The generative AI model generates specific suggestions for joint activities based on the extracted information between users. The input is a list of users with common interests, and the output is suggestions for joint activities. Multiple options are generated based on the user's interests.

[1610] Step 14:

[1611] The server generates collaborative activity suggestions and creates a push notification. The input is the collaborative activity suggestions and the output is the push notification body. A personalized notification is created based on the suggestions.

[1612] Step 15:

[1613] The device sends a push notification to the user. The input is the push notification body, and the output is the notification received by the user device. The notification server sends the notification to the user device in real time.

[1614] Step 16:

[1615] The generative AI model generates a future forecast based on user interest and behavioral data. The input is interest data and behavioral history data, and the output is a future forecast. Scenarios are depicted using simulation models and past data.

[1616] Step 17:

[1617] The server saves the generated future projections in a database. The input is the future projections, and the output is the future projections saved in the database. A future projection customized for each user is saved.

[1618] Step 18:

[1619] The device presents the saved future vision to the user in the form of video or text. The input is the future vision stored in the database, and the output is the content presented to the user. Create a section within the app to display the content of the future vision.

[1620] (Application example 1)

[1621] 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."

[1622] While there are existing systems that provide various support to unmarried people leading up to marriage, there are no systems that promote opportunities for meeting people while traveling in self-driving vehicles. Furthermore, there is a lack of appropriate matching and suggestions for joint activities that utilize users' travel routes and ride-sharing history, as well as a means to concretely visualize their future lives. This makes it difficult for unmarried people to efficiently find opportunities to meet people while traveling.

[1623] 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.

[1624] In this invention, the server includes means for inputting profile information of unmarried people, means for saving the profile information in a database, means for analyzing behavioral history data saved in the database and identifying user interests, means for suggesting meeting opportunities based on the analysis results, means for sending the suggested meeting opportunities by push notification, means for collecting travel routes and ride-sharing histories of autonomous vehicles, means for saving and analyzing the travel routes and ride-sharing histories in a database, and means for matching users heading in the same direction based on the analysis results and sending the results by push notification. This enables unmarried people to efficiently find meeting opportunities while traveling in autonomous vehicles.

[1625] "Profile Information" is personal information about a user, such as their name, age, gender, hobbies, and interests.

[1626] A "database" is a system for organizing, storing, and managing collected information.

[1627] "Behavioral history data" is a record of a user's past activities and behaviors.

[1628] "Analysis" is the process of examining collected data in detail and finding meaning.

[1629] "Interests" refers to the range of interests or concerns a user has about a particular subject.

[1630] "Meeting Opportunities" are situations or events where users can meet new people.

[1631] "Push Notification" means a notification sent to a User's Device in real time.

[1632] An "autonomous vehicle" is a vehicle that operates automatically without a human driver.

[1633] A "travel route" is the route a vehicle takes.

[1634] "Ride-sharing history" is a record of ride-sharing services a user has used in the past.

[1635] "Matching" is the process of connecting users with common interests and goals.

[1636] A "collaborative activity" is an event or activity in which multiple users participate together.

[1637] A "future vision" is a visual or written suggestion that helps users visualize their future life and activities.

[1638] This invention is a matching system for singles that operates inside an autonomous vehicle. The system is designed to enable singles to efficiently enjoy opportunities to meet people while traveling. The system consists of three main parts: a server, a terminal (display or smartphone of the autonomous vehicle), and a user.

[1639] User Registration

[1640] The server provides a means for users to install the application and enter profile information (such as name, age, gender, hobbies, interests, etc.). The profile information entered by the user is sent to the server via the device and stored in a database. This allows the server to centrally manage individual user information.

[1641] Data collection and analysis

[1642] The server collects the autonomous vehicle's route and ride-sharing history data and stores it in a database. Based on this, the generative AI model analyzes the data and identifies the user's behavioral patterns and interests. Specifically, it analyzes the user's past route and ride-sharing history to understand their behavioral trends. For example, if a user frequently participates in a particular event, that tendency can be analyzed and used to suggest encounters.

[1643] Providing opportunities to meet people

[1644] The server then proposes optimal meeting opportunities to users based on the analysis results of the generation AI. In particular, it matches users heading in the same direction to provide meeting opportunities while traveling in an autonomous vehicle. At this time, the server generates a push notification and sends it to the device. The user can view and participate in the proposed meeting opportunities through their device.

[1645] Specific examples

[1646] When users A and B are traveling long distances to the same area, they discover that they have a common hobby (e.g., music festivals) and suggest an opportunity for them to attend the event together while traveling.

[1647] Providing a memorable experience

[1648] The server extracts singles with common hobbies and interests and generates suggestions for joint activities (e.g., cooking classes, camping) that can be participated in while traveling. These suggestions are automatically generated using AI and sent to users via push notifications on their devices. By participating in the suggested joint activities, users can easily share unforgettable experiences.

[1649] Proposal for a vision of the future

[1650] The server generates a future vision based on the user's interests and behavioral data. For example, generative AI is used to generate specific future images, such as suggestions for newlywed life or where to move. This future vision is stored in a database and presented to the user in video or text format via their device. This allows the user to concretely imagine their future life and make easier plans.

[1651] Prompt Sentence Examples

[1652] “The user is looking to meet someone while traveling long distances. Please suggest attractions and events for the near future. The prompt given to the AI ​​generator is, ‘Please suggest events that the user can enjoy during their trip that share their interests.’”

[1653] This system will enable singles to efficiently find opportunities to meet people while traveling in an autonomous vehicle, and will also provide them with memorable experiences and support in concretely imagining their future lives.

[1654] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1655] Step 1:

[1656] The user enters profile information (such as name, age, gender, hobbies, and interests) into a device (such as a smartphone or the display of an autonomous vehicle). The entered profile information is sent from the device to a server, which receives it and stores it in a database.

[1657] Step 2:

[1658] The user starts traveling in the autonomous vehicle using the application. The terminal collects the vehicle's route and ride-sharing history data in real time and transmits it to the server, which receives it and stores it in a database.

[1659] Step 3:

[1660] The server inputs the behavioral history data stored in the database into the generative AI model to analyze the user's interests. The generative AI model identifies behavioral patterns and hobbies and preferences and outputs the results to the server.

[1661] Step 4:

[1662] The server uses the results of the generative AI model's analysis to suggest optimal meeting opportunities for the user, using an algorithm to determine whether a match with another user heading in the same direction is possible. As a result, an appropriate match is made (e.g., joint attendance at a music festival).

[1663] Step 5:

[1664] The server generates a proposed matchmaking opportunity and sends it as a push notification to the device, which receives the notification and displays it to the user, who then reviews the notification and decides whether to participate in the proposed matchmaking opportunity.

[1665] Step 6:

[1666] The server extracts users with common hobbies and interests and suggests activities they can participate in together (e.g., cooking classes or camping). These suggestions are also automatically generated using a generative AI model and sent to the device as a push notification from the server. The device displays the notification to the user, who then decides whether or not to participate in the activity.

[1667] Step 7:

[1668] The server generates a future vision based on the user's interests and behavioral data and stores it in a database. The generated future vision is presented to the user via their device in the form of video or text. The device displays content that allows the user to concretely imagine what life will be like in the future.

[1669] Step 8:

[1670] To help users visualize their future lives, the generative AI model receives specific prompts, such as "Please suggest events that users can enjoy during their trip that involve common hobbies," and the model receives appropriate output.

[1671] Through these steps, the system will enable singles to efficiently find opportunities to meet people while traveling in an autonomous vehicle, and will also provide them with memorable experiences and support in concretely imagining their future lives.

[1672] 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.

[1673] This invention is a system that provides various support to unmarried people leading up to marriage, and in particular, it is a system that combines an emotion engine that recognizes the user's emotions. This system uses generative AI to analyze the user's interests and behavioral history, and further analyzes the user's emotional data using an emotion engine, to provide more appropriate "opportunities to meet," "unforgettable memories," and "future visions." This system consists of three main parts: a server, a terminal, and the user.

[1674] Program processing

[1675] 1. User Registration

[1676] Describe the process by which a user enters profile information:

[1677] Users download and install the app on their devices, then enter their profile information, such as their name, age, gender, hobbies, and interests, into the device. The device then sends the information to the server, which then stores it in a database.

[1678] 2. Data Collection and Analysis

[1679] Explain the process for collecting and analyzing user behavior data:

[1680] Within the app, users read articles, participate in events, and chat with friends. The device sends this behavioral history data to the server, which then stores and updates the collected behavioral history data in a database. The generation AI analyzes the behavioral history data and identifies the user's interests and behavioral patterns.

[1681] 3. Emotion Recognition and Analysis

[1682] Explain the process of recognizing and analyzing user emotions:

[1683] The device collects facial and voice data when the user uses the app. The device sends this data to the server as emotional data. The server's emotional engine analyzes the emotional data and identifies the user's current emotional state.

[1684] 4. Providing opportunities for encounters

[1685] Explain the process we use to find the right matchmaking opportunities for you:

[1686] The server selects the most suitable meeting opportunities for the user (for example, events that match hobbies or activities that share common interests) based on the analysis results of the generation AI and the emotion engine. The server generates specific suggestions for meeting opportunities and creates the body of the push notification. The device sends the push notification to the user, and the user participates in the suggested events or activities based on the received suggestions.

[1687] 5. Provide a memorable experience

[1688] Describe the process for delivering experiences to users who share common hobbies and interests:

[1689] The server extracts unmarried people who share common hobbies and interests. The generation AI generates suggestions for joint activities (e.g., cooking classes, camping) based on the extracted information about users and their emotions. The server creates the push notification content, and the device sends the push notification to the user. The user participates in the suggested activity and creates unforgettable memories through the experience.

[1690] 6. Proposal of a vision for the future

[1691] Describe the process to help users visualize their future life:

[1692] The AI ​​generates a future vision (suggestions for newlywed life or relocation destinations) based on the user's interests, behavioral data, and emotional data. The server stores the generated future vision in a database. The device presents the saved future vision to the user in video or text format. The user can use the presented future vision as a reference to imagine and consider their own specific vision of the future.

[1693] As a concrete example, consider a case where a user's hobby is "music." The system analyzes the user's past behavioral history and suggests local music festivals. Furthermore, based on the results of the emotion engine's analysis of the user's emotional data, the system makes suggestions to the user at appropriate times. It also suggests music workshops that users can participate in together with other users who share the same hobby, and presents a vision of the future of relocating to a region with a strong music scene.

[1694] In this way, this system aims to improve marriage rates by analyzing users' profile information, behavioral history data, and emotional data, and providing various types of support leading up to marriage.

[1695] The processing flow will be explained below.

[1696] Step 1:

[1697] User enters profile information:

[1698] Users download and install the app on their device, then enter their profile information, such as their name, age, gender, hobbies, and interests.

[1699] Step 2:

[1700] The device sends the input data to the server:

[1701] The terminal transmits the input profile information to the server, and the server receives the input data.

[1702] Step 3:

[1703] The server stores the profile information in a database:

[1704] The server stores the received profile information in a database.

[1705] Step 4:

[1706] User takes action in the app:

[1707] Within the app, users can read articles, attend events, and chat with friends.

[1708] Step 5:

[1709] The device sends the activity history data to the server:

[1710] Data about each user's activity (e.g., articles viewed, events attended, chat history) is sent from the device to the server.

[1711] Step 6:

[1712] The server collects the behavioral history data and stores it in a database:

[1713] The server stores the collected behavioral history data in a database and updates it accordingly.

[1714] Step 7:

[1715] The emotion engine collects emotion data:

[1716] The device collects facial expressions and voice data when the user uses the app and sends it to the server as emotional data.

[1717] Step 8:

[1718] The server analyzes the emotion data:

[1719] An emotion engine in the server analyzes the emotion data and identifies the user's current emotional state.

[1720] Step 9:

[1721] Generative AI analyzes behavioral and emotional data:

[1722] The generation AI on the server analyzes behavioral history data and emotional data to identify the user's interests and behavioral patterns.

[1723] Step 10:

[1724] The server selects the opportunities and creates suggestions:

[1725] Based on the analysis results of the generation AI and emotion engine, the server selects meeting opportunities (e.g., hobby-based events and content) to suggest and generates the proposed content.

[1726] Step 11:

[1727] The server creates the push notification content:

[1728] Create the push notification body based on the suggestions generated by the server.

[1729] Step 12:

[1730] The device sends a push notification to the user:

[1731] The device forwards the contents of the push notification sent from the server to the user.

[1732] Step 13:

[1733] The user participates in a suggested dating opportunity:

[1734] Users receive push notifications and act on suggested events and activities.

[1735] Step 14:

[1736] The server extracts users with common hobbies and interests:

[1737] The server extracts users with common hobbies and interests from the database.

[1738] Step 15:

[1739] Generative AI suggests collaborative activities:

[1740] Based on the extracted information between users, a generation AI on the server generates suggestions for joint activities (e.g., cooking classes, camping).

[1741] Step 16:

[1742] The server creates a push notification for the collaboration:

[1743] The server creates the text of the push notification for the collaborative activity based on the suggestions made by the generation AI.

[1744] Step 17:

[1745] The device sends a push notification to the user about the collaborative activity:

[1746] The terminal forwards the push notification of the collaborative activity sent from the server to the user.

[1747] Step 18:

[1748] The user participates in a proposed collaborative activity:

[1749] Users receive push notifications and act on suggested collaborative activities.

[1750] Step 19:

[1751] Generative AI creates a vision of the future:

[1752] The generation AI on the server generates a future vision (suggestions for newlywed life and relocation destinations) based on the user's interests, behavioral data, and emotional data.

[1753] Step 20:

[1754] The server saves the generated future view:

[1755] The server stores the generated future projections in a database.

[1756] Step 21:

[1757] The device presents the user with a vision of the future:

[1758] The device presents the future vision stored on the server to the user in video or text format.

[1759] Step 22:

[1760] Users consider the future:

[1761] Users can use the presented future projections to concretely imagine and consider their own future.

[1762] Example 2

[1763] 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."

[1764] Unmarried people face difficulties in finding a partner and building relationships in the process leading up to marriage. In particular, there is no system that can properly grasp a user's interests and emotional state and suggest opportunities to meet or joint activities based on that information, making it difficult for unmarried people to build deep relationships with each other.

[1765] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1766] In this invention, the server includes means for inputting profile information of unmarried people, means for saving the profile information in a database, means for collecting behavioral history data, means for analyzing the behavioral history data saved in the database and identifying the user's interests, means for collecting user emotional data, means for analyzing the emotional data and identifying the user's emotional state, means for suggesting meeting opportunities based on the analysis results, and means for sending the suggested meeting opportunities by push notification. This makes it possible to suggest appropriate meeting opportunities and joint activities based on the user's interests and emotional state.

[1767] "Single" means a person who is not legally married.

[1768] "Profile information" refers to personal information such as name, age, gender, hobbies, and interests.

[1769] A "database" is a digital recording system that stores information in an organized manner and makes it easy to search and manage.

[1770] "Behavioral history data" is a record of various activities and operations performed by users within the app.

[1771] "Interests" are the things or areas that a user is particularly interested in and finds appealing.

[1772] "User" means an individual who uses this system.

[1773] "Emotional data" refers to information about emotions obtained from the user's facial expressions, voice, etc.

[1774] An "emotional state" is the psychological state or feeling a user is experiencing at a given moment.

[1775] "Analysis results" are conclusions or information obtained through data analysis.

[1776] "Dating opportunities" are events and activities that allow singles to meet other singles.

[1777] "Push notification" means a notification that the system sends to a user's device in real time.

[1778] "Joint activities" are events or activities that single people with common hobbies or interests participate in together.

[1779] "Future Visions" are simulations or scenarios that concretely illustrate the user's future possibilities.

[1780] The present invention is a system that provides various support services to unmarried people leading up to marriage, and in particular, it is a system that combines an emotion engine that recognizes the user's emotions. This system is implemented using the following hardware and software.

[1781] Hardware and software used

[1782] Terminal: A device that is directly operated by the user, such as a smartphone, tablet, or PC.

[1783] Server: The server that stores, processes, and notifies data.

[1784] Database: A relational database management system (RDBMS) such as MySQL or PostgreSQL.

[1785] Generative AI model: A machine learning model for analyzing user behavioral history and interests.

[1786] Emotion engine: A software module that analyzes a user's facial expressions and voice data to identify emotions.

[1787] Processing Overview

[1788] 1. User Registration

[1789] Users download and install the app on their devices such as smartphones or tablets. After that, they launch the app and enter their profile information, such as their name, age, gender, hobbies, and interests. The entered information is sent from the device to a server, which then stores it in a database.

[1790] 2. Data Collection and Analysis

[1791] Within the app, users read articles, participate in events, and chat with friends. The device sequentially sends this behavioral history data to the server, which then stores it in a database. The generative AI model analyzes the behavioral history data to identify the user's interests and behavioral patterns.

[1792] 3. Emotion Recognition and Analysis

[1793] When a user uses the app, the device uses the front camera and microphone to collect facial and voice data, which is then sent from the device to a server where an emotion engine analyzes the data to identify the user's current emotional state.

[1794] 4. Providing opportunities for encounters

[1795] The server proposes optimal meeting opportunities to users based on the analysis results of the generative AI model and emotion engine. Specifically, it selects events and activities that match users' interests and sends them to the device as push notifications. Users can then participate in events and activities based on the suggestions they receive.

[1796] 5. Provide a memorable experience

[1797] The server extracts singles with common hobbies and interests from a database and uses a generative AI model to suggest joint activities. The server then creates a push notification, which the device sends to the user. The user then participates in the suggested activities and creates unforgettable memories.

[1798] 6. Proposal of a vision for the future

[1799] The generative AI model generates a future vision based on the user's interests, behavioral data, and emotional data. The server stores the generated future vision in a database, and the device presents it to the user in video or text format. The user can use the presented future vision as a reference to imagine and consider their own specific vision of the future.

[1800] Specific examples

[1801] For example, if a user's hobby is "music," the system will analyze the user's past behavioral history and suggest local music festivals. It will also make appropriate suggestions to the user based on the results of the emotion engine's analysis of their emotional data. It will also suggest music workshops that users can participate in together with other users who share the same hobby, and in the future, it will present a vision of moving to a region with a strong music scene.

[1802] Prompt Sentence Examples

[1803] The following prompt sentences are fed into the generative AI model for analysis:

[1804] "User A's hobby is music. Based on past behavioral history data, would it be appropriate to suggest a local music festival this weekend? Furthermore, how can we suggest joint activities with User B, who shares the same musical interest?"

[1805] As described above, the present invention analyzes a user's profile information, behavioral history data, and emotional data, and provides various types of support leading up to marriage.

[1806] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1807] Step 1: User Registration

[1808] 1. Input: The user downloads the app and installs it on their device.

[1809] 2. Input: The user enters their profile information (name, age, gender, hobbies, interests, etc.).

[1810] 3. Operation: The device sends the entered profile information to the server.

[1811] 4. Output: The server stores the received profile information in a database.

[1812] Example: If a user inputs that their hobby is "music," that hobby information is saved in a database.

[1813] Step 2: Data collection and analysis

[1814] 1. Input: A user reads an article, attends an event, or chats with a friend within the app.

[1815] 2. Operation: The device sequentially sends this behavioral history data to the server.

[1816] 3. Input: The server saves and updates the behavioral history data it receives in the database.

[1817] 4. Action: The generative AI model analyzes historical behavioral data and identifies user interests.

[1818] 5. Output: The analysis results from the generation AI are obtained from the server, and the user's interests and behavioral patterns are identified.

[1819] Example: If a user frequently reads articles about "music festivals," the generative AI will identify that the user is interested in music festivals.

[1820] Step 3: Emotion Recognition and Analysis

[1821] 1. Input: The device collects facial and voice data when the user uses the app.

[1822] 2. Operation: The device sends the collected facial and voice data to the server as emotion data.

[1823] 3. Input: The server passes the received emotion data to the emotion engine.

[1824] 4. Action: The emotion engine analyzes the emotion data and identifies the user's current emotional state.

[1825] 5. Output: The server obtains the analysis results from the emotion engine and identifies the user's emotional state.

[1826] Example: If a smiling expression is detected while a user is reading a music article, the emotion engine identifies the user as "happy."

[1827] Step 4: Providing opportunities for encounters

[1828] 1. Input: The analysis results of the generation AI and emotion engine are integrated on the server.

[1829] 2. Operation: Based on the analysis results, the server suggests the best meeting opportunities to the user.

[1830] 3. Input: Select events and activities that suit your interests as suggestions.

[1831] 4. Action: The server generates specific suggestions for dating opportunities and creates the body of the push notification.

[1832] 5. Output: The device sends a push notification to the user, and the user receives the notification.

[1833] Example: A user receives a push notification saying, "We encourage you to attend the music festival this weekend."

[1834] Step 5: Deliver a memorable experience

[1835] 1. Input: The server extracts from the database singles who share common hobbies and interests.

[1836] 2. Operation: The generative AI model generates suggestions for joint activities based on the extracted information and emotional data between users.

[1837] 3. Input: Suggestions for events and experiences based on common interests are generated.

[1838] 4. Operation: The server creates the push notification content, and the device sends the push notification to the user.

[1839] 5. Output: The user participates in the suggested activity and creates unforgettable memories through the experience.

[1840] Example: A user receives suggestions for cooking classes to join with other users who share the same interests.

[1841] Step 6: Propose a vision for the future

[1842] 1. Input: The generative AI model generates a future forecast based on the user's interests, behavioral data, and emotional data.

[1843] 2. Operation: The server saves the generated future projections in a database.

[1844] 3. Input: The saved future projection is ready to be provided to the user.

[1845] 4. Operation: The device presents the future vision to the user in the form of video and text.

[1846] 5. Output: The user uses the presented future vision as a reference to imagine and consider their own future in concrete terms.

[1847] Example: A user is presented with a plan to move to a music-loving area in the future.

[1848] This allows users to receive suggestions for more suitable encounters, memorable experiences, and future prospects based on their profile information, behavioral history data, and emotional data.

[1849] (Application example 2)

[1850] 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."

[1851] There is a lack of systems to promote marriage among today's unmarried people. In particular, there is a lack of methods to utilize users' emotional and behavioral data to provide them with optimal dating opportunities at the right time, and to use virtual spaces to help users visualize actual married life. This makes it difficult for users to imagine suitable dating opportunities and their future lives, leading to a decline in marriage rates.

[1852] The specification processing by the specification 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 inputting profile information of unmarried people, means for saving the profile information in a database, means for analyzing behavioral history data saved in the database and identifying the user's interests, means for suggesting meeting opportunities based on the analysis results, means for sending the suggested meeting opportunities via push notification, means for collecting and analyzing the user's emotional data, means for suggesting meeting opportunities at optimal times based on the analysis results of the emotional data, means for generating and presenting a future vision based on the user's profile information, behavioral history data, and emotional data, and means for constructing a virtual space and conducting meetings and activities within the virtual space. This makes it possible to appropriately utilize the user's emotional and behavioral data to provide optimal meeting opportunities and allow the user to imagine a concrete future life through the virtual space.

[1853] "Single" refers to someone who is not currently married.

[1854] "Profile Information" refers to basic information that identifies an individual, such as a user's name, age, gender, hobbies, and interests.

[1855] A "database" is a system for organizing and storing data in digital form.

[1856] "Behavioral history data" refers to various activity records generated when a user uses the system.

[1857] "Interests" refers to the interest or concern a user has in a particular activity or topic.

[1858] "Analyzing" refers to the detailed analysis of the data obtained using computational and statistical methods to derive specific information or patterns.

[1859] "Meeting opportunities" refers to events and activities that allow users to communicate with other users and build new relationships.

[1860] "Push notification" refers to a technology that sends specific information or messages directly to a user's device.

[1861] "Emotional data" refers to data that indicates the emotional state of a user analyzed from their facial expressions and voice.

[1862] "Virtual space" refers to a virtual three-dimensional space constructed using computer technology.

[1863] "Future projections" refer to diagrams and images that visually represent future lifestyles and situations, generated based on user data.

[1864] "Joint activities" refer to activities undertaken by multiple users who share a common hobby or interest.

[1865] "Building" refers to designing a system or program and putting it into a working form.

[1866] "Notify" refers to the act of informing a user of specific information.

[1867] The present invention is a system that provides various support services to unmarried people leading up to marriage. By combining a generative AI model and an emotion engine, the system analyzes users' interests, behavioral history, and emotional data to provide more appropriate "opportunities to meet people," "unforgettable memories," and "future projections." Specific embodiments of the present invention are described in detail below.

[1868] composition

[1869] This system consists of three main parts: the server, the terminal, and the user. Each part works together to provide optimal support for the user in their search for a partner.

[1870] Hardware and software used

[1871] Server: AWS (Amazon Web Services) is used, DynamoDB is used as the database, and AWS SNS is used as the notification service.

[1872] Device: The user's smartphone or head-mounted display (HMD) (e.g., Oculus Rift).

[1873] Analysis software:

[1874] We use Google Analytics to collect behavioral history data.

[1875] OpenCV (facial expression recognition) and Librosa (voice analysis) are used for emotion data processing.

[1876] TensorFlow and PyTorch are used for generative AI models.

[1877] User Registration

[1878] After installing the app on a smartphone or HMD, users enter their profile information, which is then sent from the device to the server and stored in DynamoDB.

[1879] Data collection and analysis

[1880] User behavioral history data is collected using Google Analytics. The server stores the collected data and analyzes it using generative AI models (TensorFlow or PyTorch) to identify user interests and behavioral patterns. The results of this analysis are stored in a database and used for future recommendations.

[1881] Emotion Recognition and Analysis

[1882] When a user uses a device (smartphone or HMD), facial expression data is collected using OpenCV and voice data is collected using Librosa. This emotion data is sent to the server and analyzed by the emotion engine. The analysis results are also stored in a database.

[1883] Providing opportunities to meet people

[1884] The server then uses the analysis results of the generative AI model and emotion engine to suggest optimal meeting opportunities for users. For example, it generates events and activities that share common interests and sends them to users as push notifications using AWS SNS.

[1885] Providing a memorable experience

[1886] The server extracts users with common hobbies and interests and uses a generative AI model to generate suggestions for joint activities (e.g., cooking classes or camping). The suggestions are sent to users as push notifications, allowing them to experience these activities in a virtual space. Unity is used to design the virtual space, and Photon is used for real-time communication.

[1887] Proposal for a vision of the future

[1888] A generative AI model generates a future vision based on the user's behavioral and emotional data. This future vision (e.g., a proposal for married life or a new home) is created as a 3D model using Blender and stored in AWS S3. It is then presented to the user's device in the form of a video or text.

[1889] Examples and prompts

[1890] As a specific example, if the user's hobby is "traveling," the following processing is performed.

[1891] 1. Analyze past travel events that users have participated in based on their behavioral history.

[1892] 2. Based on the analysis results and the emotion engine results, we suggest a virtual travel experience with someone who loves to travel.

[1893] 3. Present future travel plans and virtual tours of the city you will live in together as a vision of the future.

[1894] Example prompt for generative AI model:

[1895] The user's profile information states that their hobby is traveling. Based on their past behavior, they have previously been interested in traveling to Northern Europe. Based on their sentiment data, they are currently excited about traveling. Please suggest an event where they can virtually experience a Nordic trip with their travel-loving partner. Also, please create a vision of their future married life in a Nordic city.

[1896] In this way, the system aims to improve marriage rates by analyzing users' profile information, behavioral history data, and emotional data, and providing various types of support leading up to marriage.

[1897] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1898] Step 1:

[1899] Users install the app on their device (smartphone or HMD) and enter their profile information, which includes their name, age, gender, hobbies, and interests. The entered information is sent from the device to the server and stored in DynamoDB, which registers the user profile in the database.

[1900] Input: User profile information (name, age, gender, hobbies, etc.)

[1901] Output: User profile stored in database

[1902] Step 2:

[1903] When a user uses the app, behavioral history data is collected through Google Analytics. This data includes which events the user participated in, which content the user viewed, etc. The collected behavioral history data is sent to a server and stored in a database.

[1904] Input: User behavioral history data (event participation history, content viewing history, etc.)

[1905] Output: Behavioral history data stored in a database

[1906] Step 3:

[1907] The server uses generative AI models using TensorFlow and PyTorch to analyze the stored behavioral history data, identifying user interests and behavioral patterns and storing the results in a database.

[1908] Input: Behavioral history data stored in the database

[1909] Output: Analysis results of interests and behavioral patterns

[1910] Step 4:

[1911] When a user uses the device, emotion data is collected using facial recognition with OpenCV and voice analysis with Librosa. This emotion data is sent to the server, where it is analyzed by the emotion engine and the results are stored in a database.

[1912] Input: User's facial and voice data

[1913] Output: Analysis results of emotion data stored in the database

[1914] Step 5:

[1915] The server then proposes optimal meeting opportunities to users based on the analysis results of the generative AI model and emotion engine. The proposals are sent to the user's device as push notifications via AWS SNS. For example, it could suggest that users with common interests attend a music festival.

[1916] Input: Analysis results of interests and behavioral patterns and analysis results of emotional data

[1917] Output: Dating opportunities sent via push notification

[1918] Step 6:

[1919] The server extracts users with common hobbies and interests and uses a generative AI model to generate suggestions for joint activities (e.g., cooking classes or camping). These suggestions are sent to users as push notifications, allowing them to experience these activities in a virtual space. The virtual space is designed using Unity and Photon.

[1920] Input: Data of users with common hobbies and interests

[1921] Output: Collaborative activity suggestions sent via push notification

[1922] Step 7:

[1923] A generative AI model generates a future vision based on the user's behavioral and emotional data. This future vision is created as a 3D model using Blender and stored on AWS S3. By presenting it to the user in video and text format, it becomes easier for them to visualize specific future plans.

[1924] Input: User behavioral and emotional data

[1925] Output: A future vision presented to the user (3D model or video format)

[1926] 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.

[1927] 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.

[1928] 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.

[1929] 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.

[1930] 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.

[1931] 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.

[1932] 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).

[1933] 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.

[1934] 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."

[1935] 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.

[1936] 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).

[1937] 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.

[1938] 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.

[1939] 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.

[1940] 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.

[1941] 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.

[1942] 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.

[1943] 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.

[1944] 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.

[1945] 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.

[1946] 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.

[1947] The following is further disclosed regarding the above embodiment.

[1948] (Claim 1)

[1949] a means for inputting profile information for singles;

[1950] means for storing said profile information in a database;

[1951] A means for analyzing the behavior history data stored in the database and identifying the user's interests;

[1952] A means for suggesting opportunities to meet based on the analysis results;

[1953] means for sending the suggested meeting opportunities via push notification;

[1954] A system including:

[1955] (Claim 2)

[1956] A means to extract unmarried people who share common hobbies and interests,

[1957] A means for proposing joint activities to the extracted unmarried persons;

[1958] means for sending the joint activity by push notification;

[1959] The system of claim 1 further comprising:

[1960] (Claim 3)

[1961] A means of generating future predictions from user interests and behavioral data,

[1962] means for storing the generated future forecast in a database;

[1963] means for presenting the stored future projection to a user;

[1964] The system of claim 1 further comprising:

[1965] "Example 1"

[1966] (Claim 1)

[1967] a means for inputting personal information of unmarried persons;

[1968] means for storing the personal information in a storage device;

[1969] means for analyzing the activity history data stored in the storage device and using a generative artificial intelligence model to identify user interests;

[1970] A means using a generative artificial intelligence model to suggest meeting opportunities based on the analysis results;

[1971] means for transmitting the suggested meeting opportunities via a notification function;

[1972] A system including:

[1973] (Claim 2)

[1974] A way to find singles who share common hobbies and interests,

[1975] means for proposing joint activities to the selected unmarried persons;

[1976] means for transmitting the joint activity by a notification function;

[1977] The system of claim 1 further comprising:

[1978] (Claim 3)

[1979] a means for generating future simulations from user interest and activity data;

[1980] means for storing the generated future simulation in a storage device;

[1981] means for presenting the saved future simulation to a user;

[1982] The system of claim 1 further comprising:

[1983] "Application Example 1"

[1984] (Claim 1)

[1985] a means for inputting profile information for singles;

[1986] means for storing said profile information in a database;

[1987] A means for analyzing the behavior history data stored in the database and identifying the user's interests;

[1988] A means for suggesting opportunities to meet based on the analysis results;

[1989] means for sending the suggested meeting opportunities via push notification;

[1990] a means for collecting route and ride-sharing history of the autonomous vehicle;

[1991] A means for storing and analyzing the travel route and ride-sharing history in a database;

[1992] A means for matching users heading in the same direction based on the analysis results and sending the matching results by push notification;

[1993] A system including:

[1994] (Claim 2)

[1995] A means to extract unmarried people who share common hobbies and interests,

[1996] A means for proposing joint activities to the extracted unmarried persons;

[1997] means for sending the joint activity by push notification;

[1998] The system of claim 1 further comprising:

[1999] (Claim 3)

[2000] A means of generating future predictions from user interests and behavioral data,

[2001] means for storing the generated future forecast in a database;

[2002] means for presenting the stored future projection to a user;

[2003] The system of claim 1 further comprising:

[2004] "Example 2: Combining Emotion Engines"

[2005] (Claim 1)

[2006] a means for inputting profile information for singles;

[2007] means for storing said profile information in a database;

[2008] A means for collecting behavioral history data;

[2009] A means for analyzing the behavior history data stored in the database and identifying the user's interests;

[2010] a means for collecting user emotional data;

[2011] means for analyzing the emotion data and identifying an emotional state of a user;

[2012] A means for suggesting opportunities to meet based on the analysis results;

[2013] means for sending the suggested meeting opportunities via push notification;

[2014] A system including:

[2015] (Claim 2)

[2016] A means to extract unmarried people who share common hobbies and interests,

[2017] A means for proposing joint activities to the extracted unmarried persons;

[2018] means for sending the joint activity by push notification;

[2019] The system of claim 1 further comprising:

[2020] (Claim 3)

[2021] A means for generating a future forecast from user interests, behavioral data, and emotional data;

[2022] means for storing the generated future forecast in a database;

[2023] means for presenting the stored future projection to a user;

[2024] The system of claim 1 further comprising:

[2025] "Application example 2 when combining emotion engines"

[2026] (Claim 1)

[2027] a means for inputting profile information for singles;

[2028] means for storing said profile information in a database;

[2029] A means for analyzing the behavior history data stored in the database and identifying the user's interests;

[2030] A means for suggesting opportunities to meet based on the analysis results;

[2031] means for sending the suggested meeting opportunities via push notification;

[2032] A means for collecting and analyzing user emotional data;

[2033] A means for suggesting an opportunity to meet someone at an optimal timing based on the analysis result of the emotion data;

[2034] A means for generating and presenting a future forecast based on the user's profile information, behavioral history data, and emotional data;

[2035] A means for constructing a virtual space and conducting encounters and activities within the virtual space;

[2036] A syste...

Claims

1. a means for inputting profile information for singles; means for storing said profile information in a database; A means for analyzing the behavior history data stored in the database and identifying the user's interests; A means for suggesting opportunities to meet based on the analysis results; means for sending the suggested meeting opportunities via push notification; A system including:

2. A means to extract unmarried people who share common hobbies and interests, A means for proposing joint activities to the extracted unmarried persons; means for sending the joint activity by push notification; The system of claim 1 further comprising:

3. A means of generating future predictions from user interests and behavioral data, means for storing the generated future forecast in a database; means for presenting the stored future projection to a user; The system of claim 1 further comprising:

Images