system

Abstract

We provide the system. [Solution] A data storage means for storing attribute information collected from users, An analysis means for analyzing the user's characteristics using a generative model based on the attribute information, A compatibility estimation method that estimates compatibility between users and selects the most suitable interaction partner, A notification method for informing the user of the matching results, A means of facilitating communication that provides a means of communication for users to interact with each other, A topic suggestion method that proposes topics for interaction using a generative model, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern aging societies, the social isolation of the elderly and the difficulty of building new human relationships are serious problems. Especially among elderly couples, when their children have become independent and live far away, the sense of isolation often increases. If such a situation continues, the life satisfaction of the elderly may decline, and it may also have an adverse effect on their mental health. Therefore, there is a need to provide an environment in which the elderly can easily engage in social communication and build new human relationships.

Means for Solving the Problems

[0005] This invention provides a system that promotes smooth social interaction among the elderly by providing a compatibility estimation means that analyzes the characteristics of users using a generative model based on attribute information collected from users and selects the most suitable interaction partners. Furthermore, this system provides a communication means for interaction and utilizes a topic suggestion means based on the generative model to realize deeper interactions. In addition, by combining it with an event suggestion means based on local information and a health management means, it can provide a place for social interaction in which the elderly can participate with peace of mind. In this way, it presents a new solution that effectively alleviates social isolation among the elderly and enables them to lead fulfilling lives.

[0006] "Attribute information" refers to data about an individual's characteristics and background, such as their hobbies, interests, lifestyle, and past work history.

[0007] "Data storage means" refers to technical means for storing attribute information collected from users and making it accessible as needed.

[0008] A "generative model" is a type of artificial intelligence model that generates new data based on input data and performs predictions and analyses for specific purposes.

[0009] "Analysis methods" refer to techniques for understanding the characteristics of a user by processing collected attribute information and extracting its features.

[0010] A "compatibility estimation method" is a means of evaluating compatibility with other users based on the user's characteristics and selecting the most suitable person to interact with.

[0011] "Notification means" refers to communication technologies and interfaces for effectively conveying information to users.

[0012] "Means of facilitating communication" are system components that enable users to communicate smoothly with each other online.

[0013] A "topic suggestion tool" is a means of automatically selecting topics that will interest users and provide opportunities for conversation using a generative model.

[0014] An "event suggestion tool" is a technology that appropriately selects and suggests local events that users can participate in, based on their geographical location and interests.

[0015] "Health management methods" refer to techniques for providing individualized health advice by monitoring and analyzing the user's health status. [Brief explanation of the drawing]

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

Mode for Carrying Out the Invention

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

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

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

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

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

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

[0026] As shown in Figure 1, the 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 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

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

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0033] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the 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 processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

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

[0037] This invention is an innovative system designed to prevent social isolation among the elderly and foster new relationships. The system provides technology for selecting optimal interaction partners based on user attribute information. Specifically, it accumulates data from users and analyzes it using a generative model to match compatible users.

[0038] First, the terminal provides the user with an input interface, allowing them to enter attribute information such as name, age, hobbies, and lifestyle. Once the information is entered, the terminal sends it to the server.

[0039] The server stores the received attribute information in a database using a data storage mechanism. Subsequently, a generative model analyzes the patterns of each user's hobbies and interests. The generative model extracts features from the data and generates an index to estimate the compatibility between users with similar characteristics.

[0040] For matched users, the server uses a notification system to send the result to the device, preparing to notify the user. This allows the user to connect online with compatible partners. The device provides communication methods such as messaging and video calls to facilitate online interaction.

[0041] Furthermore, the generative model automatically suggests useful topics during conversations, supporting the development of mutual interest. This facilitates smooth communication between users.

[0042] Furthermore, the server selects and suggests appropriate events based on local information, increasing opportunities for users to interact offline. This feature makes it easier for seniors to participate in community activities.

[0043] Health-related functions are also incorporated into this system. The terminal provides an interface for users to input their health status, and the server collects and analyzes this information. Based on the analysis results, it generates and presents personalized health advice to the user.

[0044] This system is expected to enable elderly people to build new relationships, avoid isolation, and lead fulfilling lives.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The terminal displays an information input interface to the user. The user enters attribute information such as name, age, hobbies, past occupations, and lifestyle. Once the user has finished entering the information, the terminal sends the entered information to the server.

[0048] Step 2:

[0049] The server stores the received attribute information in a database. Using the stored data, it activates a generative model to analyze the user's hobbies and interests. This generates a feature vector for each user.

[0050] Step 3:

[0051] Based on the feature vectors calculated by the generative model, the server calculates a compatibility score between users. It selects the most compatible user pairs and generates this information as a matching result.

[0052] Step 4:

[0053] The server uses a notification mechanism to send information about the selected pair to the terminal in order to notify the user of the matching results. The receiving terminal displays this information to the user, allowing them to confirm the matching results.

[0054] Step 5:

[0055] Users can review the matching results and, if they wish to begin interacting, initiate video calls or messaging through their device. The device establishes the means of communication and supports interaction between users.

[0056] Step 6:

[0057] During interaction, the server uses a generative model to suggest topics based on shared hobbies and interests. This information is displayed to the user via their device and used to facilitate conversation.

[0058] Step 7:

[0059] The server verifies the user's location and collects information on events happening in the area. It analyzes the collected event information and generates data to select and suggest events that are suitable for the user to attend.

[0060] Step 8:

[0061] Regarding the health management function, the terminal provides a health information input screen, and the user enters their own health information. The server analyzes the collected health data and generates and provides personalized health advice to the user.

[0062] (Example 1)

[0063] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0064] In modern society, the problem of social isolation and difficulty in building new relationships exists among the elderly. These social problems increase the risk of negative mental and physical effects on the elderly. Traditional methods are ineffective in solving these problems, and a more efficient and individualized system for promoting social interaction is needed.

[0065] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0066] In this invention, the server includes an information recording means for storing attribute information collected from the user, a feature analysis means for analyzing the user's characteristics using a generative model based on the attribute information, and a compatibility evaluation means for predicting compatibility between users and selecting the optimal interaction partner. This enables the efficient search for appropriate interaction partners based on the user's attributes, making it possible for elderly people to build new relationships.

[0067] "Information recording means" refers to means for securely and efficiently storing attribute information collected from users.

[0068] A "feature analysis method" is a means of analyzing the characteristics of a user in detail using a generative model based on the user's attribute information that has been collected.

[0069] A "compatibility evaluation method" is a means of predicting compatibility between users and selecting the most suitable interaction partners.

[0070] A "notification function" is a means of quickly and accurately notifying the user of the matching results.

[0071] "Communication support means" refers to means that provide communication functions to enable users to interact smoothly with other users.

[0072] A "topic suggestion tool" is a method that uses generative models to suggest useful topics in order to facilitate interaction among users.

[0073] An "event recommendation method" is a means of suggesting activities or events suitable for users based on local information.

[0074] A "health promotion tool" is a means of analyzing a user's health status information and generating personalized health advice.

[0075] This invention is a system designed to prevent social isolation among the elderly and to help them build new relationships. This system provides technology for selecting the most suitable partners for interaction based on the user's attribute information.

[0076] The terminal provides the user with an input interface, allowing them to enter attribute information such as name, age, hobbies, and lifestyle. This interface is designed to allow for accurate information entry using a touchscreen or keyboard. The entered information is transmitted to the server via protocols such as SSL over the internet.

[0077] The server stores the received attribute information in a database system (e.g., MySQL®, PostgreSQL). This information is securely managed to protect user privacy and maintain data consistency. Subsequently, a generative AI model is used to analyze each user's hobbies and interests. The machine learning algorithms used (e.g., clustering, classification) are designed to efficiently process large amounts of data and perform feature extraction.

[0078] Users can receive matching results sent from their devices and interact online. Chat apps and video call tools are provided as means of interaction, enabling communication that transcends physical distance.

[0079] This system also features a generative AI model that automatically suggests topics to support the conversation as needed. A possible example of a prompt would be: "A 75-year-old man, whose hobbies are gardening and local history. Please recommend someone suitable to interact with." Upon entering this prompt, the AI ​​begins processing to recommend a suitable partner.

[0080] Furthermore, the system has a function that suggests events suitable for the user based on local information, thereby increasing opportunities for offline interaction. This event suggestion function uses a map service API to provide appropriate event information based on the user's location.

[0081] Finally, the terminal provides an interface for users to input information about their health status, and the server analyzes this information to generate personalized health advice. Through these processes, users can implement health management tailored to their individual needs.

[0082] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0083] Step 1:

[0084] The terminal provides the user with an input interface, allowing them to enter attribute information such as name, age, hobbies, and lifestyle. Input is performed by typing or selecting information into a form on the screen. The data is confirmed when the user presses the submit button. The entered information is then sent to the next processing step with the user's consent.

[0085] Step 2:

[0086] The terminal sends the entered attribute information to the server using the SSL protocol. The transmitted data is encrypted and securely transferred over the network. Specifically, after pressing the send button, the data packet arrives on the server via the internet.

[0087] Step 3:

[0088] The server verifies the received attribute information, confirms its security, and then stores it in the database. This process uses a database management system and performs database insertion operations to ensure the data is mapped to the correct fields. The input is user attribute information, and the output is the successfully stored information.

[0089] Step 4:

[0090] The server activates a generated AI model based on stored attribute information to analyze the user's characteristics. This analysis uses machine learning algorithms (clustering and classification) to analyze patterns and trends from the resulting dataset. The input is the user's attribute information, and the output is the analyzed characteristic data.

[0091] Step 5:

[0092] The server performs compatibility evaluations based on feature data analyzed by a generative AI model and selects the most suitable interaction partners. This evaluation includes similarity calculations, quantifying compatibility with other users who have similar characteristics. The input is feature data, and the output is a compatibility evaluation value and a list of optimal partners.

[0093] Step 6:

[0094] The server sends the compatibility evaluation results to the terminal and notifies the user of the results. Real-time push notifications and email notifications are used as notification methods, allowing the user to check the results immediately. The input is the compatibility evaluation result, and the output is the notification message.

[0095] Step 7:

[0096] The device provides users with online communication tools through messaging and video call functions. This allows them to communicate directly with selected individuals. Specific actions include launching related applications and starting sessions.

[0097] Step 8:

[0098] The generative AI model suggests useful topics during conversations as needed. The suggested topics are tailored to the user's interests based on pre-set prompt sentences. The input is a prompt sentence, and the output is a list of recommended topics.

[0099] Step 9:

[0100] The server suggests events based on local information, recommending activities that match the user's geographical location. This function accesses a map service API and filters and provides events based on the user's location. The input is the user's location information, and the output is a list of suggested events.

[0101] (Application Example 1)

[0102] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0103] To help older adults overcome social isolation and build new relationships, it is crucial to find appropriate partners and engage in meaningful conversations and activities. However, finding suitable partners and providing opportunities for interaction in the real world is difficult. Furthermore, opportunities for natural conversations with people who share similar hobbies and interests are also challenging. Therefore, there is a need for systems that support such interactions.

[0104] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0105] In this invention, the server includes data storage means for storing attribute information collected from users, analysis means for analyzing the characteristics of users using a generative model based on the attribute information, and compatibility estimation means for estimating compatibility between users and selecting the most suitable interaction partners. This enables users to engage in meaningful conversations and easily build new relationships in real-world interaction environments, with support from topic suggestion means.

[0106] A "data storage means" is a function that stores attribute information collected from users and makes it available for later analysis.

[0107] "Analysis tools" refer to functions that utilize generative models based on collected attribute information to analyze user characteristics in detail.

[0108] The "compatibility estimation method" is a function that analyzes commonalities and interests between users and selects the most suitable person to interact with.

[0109] A "notification method" is a function that quickly communicates matching results to the user and prompts them to take the next action.

[0110] "Means of facilitating interaction" refers to a function that provides the necessary communication means to enable users to interact effectively with each other.

[0111] A "topic suggestion tool" is a function that uses a generative model to automatically suggest topics useful for interaction, thereby facilitating smooth conversation.

[0112] A "display means" is a function that visually presents appropriate interaction targets or events to the user in a real-world interaction environment.

[0113] "Communication support means" refers to functions that support real-time interaction with other users and facilitate smooth communication.

[0114] To implement this invention, the system includes a program that collects and analyzes attribute information and performs appropriate matching between users. The server stores user attribute information obtained from devices such as smartphones and tablets in a data storage means. This information includes name, age, interests, lifestyle, and health status. This information is managed by a database management system (e.g., PostgreSQL). Furthermore, a wide-area network (e.g., the Internet) is used as a means of communication to enable bidirectional transmission and reception of information.

[0115] The server utilizes generative AI models based on TENSORFLOW® and PyTorch to analyze the received attribute information and understand the user's characteristics, such as interests and hobbies. Based on this analysis, it estimates compatibility between users with shared interests and uses AI to select appropriate interaction partners. Users are notified in real time of matching results and interaction events using notification methods such as Firebase Cloud Messaging.

[0116] To facilitate interaction, the display system visualizes relevant interaction targets and related event information on the terminal's screen in a real-world interaction environment, making them suitable for the user. Furthermore, to facilitate conversation, a topic suggestion system is used, where a generative model automatically suggests topics that are likely to pique the user's interest. For example, a prompt might look like this:

[0117] Example of a prompt:

[0118] User A's information: Age = 70, Hobbies = Gardening, Health status = Good

[0119] Candidate information list: [User B: Age=72, Hobby=Gardening, Health=Good, User C: Age=65, Hobby=Reading, Health=Good]

[0120] Please use an AI model to suggest the most compatible match for user A.

[0121] Furthermore, communication support means allow users to interact with each other through real-time chat and video calls. This function is implemented using technologies such as WebRTC. For example, in a cafe space, if another user who enjoys gardening is approached by the AI, the AI ​​might suggest a topic like, "What kind of techniques do you use when growing this flower?", facilitating a conversation based on shared interests. Through these processes, users can build new relationships and deepen their social connections.

[0122] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0123] Step 1:

[0124] The device receives attribute information from the user, such as name, age, hobbies, lifestyle, and health status, through an input interface. This information becomes input data sent to the server and is formatted as a user profile.

[0125] Step 2:

[0126] The server registers the received user attribute information in the database using a data storage mechanism. The input here is raw data sent from the terminal, which is then stored as structured data by the database management system.

[0127] Step 3:

[0128] The server processes user information retrieved from the database using analytical tools and performs user characteristic analysis using a generative AI model (using TensorFlow or PyTorch). The input is attribute information, and the output is a user characteristic vector. This process extracts commonalities and interest trends.

[0129] Step 4:

[0130] The server uses a compatibility estimation method based on the analyzed feature vectors to estimate the compatibility between users. The input is a list of feature vectors, and the output is a list including matching scores. The generative AI model identifies users with high similarity and selects matching candidates.

[0131] Step 5:

[0132] The server sends the matching results to the terminal via a notification system, informing the user of information about potential matches. The input is the matching score and a list of candidates, and the output is a notification signal to the user. Because notifications are sent in real time, Firebase Cloud Messaging is used.

[0133] Step 6:

[0134] On the device, interaction facilitators are activated based on the matching information received by the user, providing communication functions such as video calls and chat. Input consists of notified interaction candidates and topic suggestions, while output is the actual communication log. WebRTC is used to enable real-time conversations.

[0135] Step 7:

[0136] The server then uses a generative AI model to execute a topic suggestion mechanism, proposing conversation topics based on shared hobbies and interests between users. The input is the profiles of the matching users, and the output is a list of suggested topics. This facilitates smooth interaction between users.

[0137] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0138] This invention is a system for promoting social interaction among the elderly while taking into account the user's emotional state. Based on the user's attribute information and emotional state, this system selects the most suitable person to interact with and supports smooth interaction.

[0139] First, the terminal provides an interface for the user to input their personal information. The user enters information about their name, age, hobbies, and lifestyle, and the terminal sends that information to the server.

[0140] Next, the server stores the transmitted attribute information in a database. It also activates an emotion engine to recognize the user's emotional state in real time from the video and audio captured during video calls and messaging. The acquired emotion data, combined with a generative model, constitutes the user's feature vector.

[0141] The server uses feature vectors to calculate the user's compatibility score and selects the most suitable interaction partners. During this process, consideration is also given to the user's emotional state, prioritizing matches where positive compatibility is expected. Information about the selected interaction partners is sent to the user's device via a notification system.

[0142] Upon receiving the notification, the user can begin interacting with the person presented via their device. The device provides the means for the user to make video calls and send messages.

[0143] During the interaction, the server suggests the most appropriate topics based on the user's emotions, as recognized by the emotion engine. These suggestions are displayed on the terminal and play a role in stimulating the interaction.

[0144] In addition, the server collects information on local events based on the user's location. If the emotional state recognized by the emotion engine is deemed suitable for going out or participating in social activities, the server suggests that the user participate in the event.

[0145] Regarding health management, the emotional engine considers the user's emotional state and generates specific health advice tailored to stress levels and mood swings. This allows users to benefit from more personalized health management.

[0146] Thus, by utilizing an emotion engine, the present invention can provide appropriate support tailored to the user's state, enabling more fulfilling social interaction and health management.

[0147] The following describes the processing flow.

[0148] Step 1:

[0149] The terminal displays a screen for the user to input attribute information. The user enters information such as name, age, hobbies, and lifestyle into the terminal. After input, the terminal sends the data to the server.

[0150] Step 2:

[0151] The server stores the received attribute information in a database. Based on the stored information, a generative model is used to generate a feature vector for the user. This feature vector indicates the user's preferences and interests.

[0152] Step 3:

[0153] When a user starts a conversation, the device monitors the video or voice call and passes the acquired audio and video data to the emotion engine. The emotion engine analyzes the user's tone of voice and facial expressions to generate emotion data.

[0154] Step 4:

[0155] The server combines the generated feature vectors with sentiment data to calculate a compatibility score between users. Based on the compatibility score, the matching system selects the most suitable interaction partners for each user.

[0156] Step 5:

[0157] The server sends the matching results to the device using a notification system. The device displays the notification to the user, encouraging interaction with the matched person. The notification also includes hints on the appropriate timing for interaction based on emotions.

[0158] Step 6:

[0159] During interaction, the server monitors the latest emotional data from the emotion engine. Based on this data, the server selects the most appropriate topics and sends suggestions to the terminal to enhance the interaction.

[0160] Step 7:

[0161] The server obtains the user's current location information and collects local event information. Considering the user's emotional state, it selects events appropriate to that situation and suggests participation.

[0162] Step 8:

[0163] The device collects health-related information entered by the user and sends it to a server. The server generates health advice, taking into account the user's emotional state, and provides it to the user. The tailored advice includes suggestions for stress management and activity levels.

[0164] (Example 2)

[0165] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0166] Social isolation and health management challenges among the elderly are becoming increasingly important. There is a need for support that allows seniors to connect with appropriate people and live healthy lives based on their emotional state, without feeling isolated. However, current systems do not adequately address the emotional states and individual health needs of users. Against this backdrop, there is a demand for a comprehensive and flexible system that enables seniors to lead richer social lives.

[0167] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0168] In this invention, the server includes data storage means for storing demographic data collected from users, analysis means for analyzing the individual characteristics of users using a generative model based on the demographic data and the users' emotional data, and compatibility selection means for estimating compatibility considering the emotional states between users and selecting the most suitable interaction partners. This enables users to prevent isolation and lead healthy and vibrant lives through appropriate interactions based on their emotional states.

[0169] A "data storage method" is a function that can stably store demographic data and sentiment data collected from users and retrieve them quickly as needed.

[0170] "Analysis tools" refer to functions that utilize collected data and generative models to comprehensively analyze the individual characteristics of users.

[0171] The "compatibility selection method" is a function that evaluates the user's emotional state, estimates their compatibility with other users based on that evaluation, and selects the most suitable person to interact with.

[0172] "Information provision means" refers to a function for transmitting information about selected interaction targets to users in an appropriate format.

[0173] A "communication support system" is a system that provides functions to enable users to communicate smoothly over long distances.

[0174] The "agenda proposal tool" is a function that uses a generative model to present agenda items suitable for the user, with the aim of stimulating interaction.

[0175] A "health guidance tool" is a function that develops and guides individual health plans based on the user's emotional state and health-related data.

[0176] The "activity suggestion tool" is a function that suggests social activities and events suitable for the user based on local information.

[0177] A "health management tool" is a function that evaluates the user's psychological state and generates and provides an individualized health strategy based on that evaluation.

[0178] This invention is a social interaction promotion system specifically designed for the elderly. This system utilizes user demographic and emotional data to select the most suitable interaction partners and support a healthy lifestyle.

[0179] First, the device provides an interface for users to input their demographic data, such as age, hobbies, and lifestyle. This typically involves a touchscreen or keyboard. It also includes a camera and microphone to collect emotional data.

[0180] The input data is transmitted to the server in real time. The server uses a high-performance database system to manage the data and general emotion engine software to analyze emotional data. A specific example of such software would be emotion recognition software. The server analyzes this data using a generative AI model (for example, a large-scale language model) to understand the user's individual characteristics.

[0181] Based on this analysis, the server selects the most suitable contact and notifies the user of that information. The notification is sent to the device via email or app push notification. The user then decides whether to interact based on the information presented.

[0182] Furthermore, the server collects information on local social activities and events based on the user's location and makes suggestions tailored to the user. Location-based services are used for this purpose. It can suggest events that will help the user refresh themselves, such as local concerts or craft classes.

[0183] In health management, the server uses collected information to suggest healthy lifestyle habits tailored to each individual user. For example, when a specific emotional state is detected, it can provide guidance on appropriate relaxation methods.

[0184] As a concrete example, the system operates based on the following prompt:

[0185] "Please suggest how to address the emotional state of users in order to promote social interaction among the elderly."

[0186] This system aims to support users in leading fulfilling lives while maintaining their health and avoiding social isolation.

[0187] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0188] Step 1:

[0189] The device collects demographic data from users. Specifically, users input information such as age, hobbies, and lifestyle through a touch panel or keyboard interface. This information is output as structured data, such as in JSON format, and sent to the server.

[0190] Step 2:

[0191] The server stores demographic data received from the terminal in a database. The received JSON data is stored as a database record, allowing for fast retrieval when needed. This is the data storage method, and the output is the data stored in the database.

[0192] Step 3:

[0193] The device collects user emotional data in real time. Specifically, it uses a camera to capture facial expressions and a microphone to record voice. This raw data is immediately transmitted to the server.

[0194] Step 4:

[0195] The server uses an emotion engine to analyze the received emotion data. It analyzes emotional states from video footage using facial recognition technology and measures tone from audio using speech analysis technology. This process outputs numerical data representing the emotional state.

[0196] Step 5:

[0197] The server uses demographic and sentiment data to analyze individual user characteristics using a generative AI model. Specifically, it uses a sentiment engine and machine learning libraries to represent user characteristics as feature vectors. These feature vectors are the output of the analysis.

[0198] Step 6:

[0199] The server uses a machine learning algorithm to calculate compatibility scores and select the most suitable interaction partners. Here, it analyzes the user's feature vectors and compares their compatibility with other users to select the most appropriate interaction partners. The selected candidates are then generated as output.

[0200] Step 7:

[0201] The server sends a notification to the user's device based on the information of the selected interaction partners. Using email or push notifications, it presents the user with the profiles and contact information of the selected partners. This is the output of the information provision.

[0202] Step 8:

[0203] The user initiates interaction via their device based on a notification from the server. Specifically, they use a video call application as a means of remote communication to communicate with the selected interaction partner. In this step, the output is successful communication.

[0204] (Application Example 2)

[0205] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0206] There is a need to promote social interaction among the elderly and provide appropriate communication tailored to their emotional state. However, existing systems have had problems in promoting interaction while adequately considering the user's feelings. Furthermore, the provision of information to support individual interactions and participation in social activities has been limited, and there has been a lack of mechanisms that allow the elderly to actively participate in particular.

[0207] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0208] In this invention, the server includes a storage means for storing attribute information collected from the user, an analysis means for analyzing the user's characteristics, and an emotion recognition suggestion means for analyzing the user's emotional state and suggesting appropriate topics. This makes it possible to select the optimal interaction partners, suggest topics for interaction, and provide information on local activities while taking the user's emotional state into consideration.

[0209] A "memory device" is a device that has the function of storing the user's attribute information.

[0210] An "analysis tool" is a device that has the function of analyzing attribute information and emotional states obtained from the user and extracting characteristics.

[0211] A "prediction means" is a device that has the function of predicting compatibility between users and selecting the optimal interaction partner.

[0212] An "information notification device" is a device that has the function of informing the user of the results obtained from analysis or estimation.

[0213] A "communication support device" is a device that provides the infrastructure for users to make calls and communicate, and has functions to promote communication.

[0214] A "content suggestion device" is a device that has the function of providing users with topics and information for interaction using a generative model.

[0215] An "emotion recognition suggestion device" is a device that has the function of detecting the user's emotional state and suggesting an appropriate topic according to that state.

[0216] A "community activity suggestion device" is a device that has the function of suggesting events and activities within a community based on the user's emotional state and local information.

[0217] An "automated interaction support device" is a device that uses robots or other means to provide real-time interaction support tailored to the user's emotional state.

[0218] A "health analysis device" is a device that analyzes the user's emotional state and generates personalized health management advice.

[0219] To implement this invention, first, the terminal receives attribute information from the user and transmits it to the server. The server stores this attribute information in a storage means and extracts the user's characteristics using an analysis means. Next, an estimation means calculates the compatibility between users based on these characteristics and selects the optimal interaction partner. This result is communicated to the user via an information notification means.

[0220] When a user begins interacting, the emotion recognition suggestion system uses hardware such as cameras and microphones to recognize the user's emotional state in real time and provides appropriate topics based on that situation using a generative AI model. For example, if the generative AI model detects that the user is excited, it will generate a prompt such as, "How about talking about the recent weather or seasons?"

[0221] Furthermore, the server uses a local activity suggestion system to combine the user's emotional state with local event information and suggests participation in events if it determines that going out is appropriate. In addition, robots equipped with automated interaction support systems provide real-time support for interactions with the user in stores and other locations. This allows users to maintain social connections with peace of mind.

[0222] Simultaneously, the health analysis system generates personalized health advice based on the user's emotional data. This allows users to receive specific advice that helps maintain their health. Thus, the present invention is a system that provides comprehensive support for the social interaction and health management of the elderly.

[0223] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0224] Step 1:

[0225] The terminal receives attribute information (name, age, hobbies, lifestyle, etc.) from the user and sends that data to the server. Its operation involves acquiring the user's attribute information as input and sending it to the server using a communication method. The output is the user's attribute information sent to the server.

[0226] Step 2:

[0227] The server stores the attribute information it receives in its memory. Its operation involves receiving attribute information sent from a terminal as input and saving it to a database as preparation for analysis. The output is the data saved for analysis.

[0228] Step 3:

[0229] The server uses analytical means to analyze the user's characteristics using a generative AI model and generates a feature vector for the user. The input is attribute information stored in a memory device, and the operation involves vectorizing the data using the generative model and extracting features. The output is the feature-vectorized user information.

[0230] Step 4:

[0231] The server uses estimation methods to calculate compatibility scores between users based on feature vectors and selects the most suitable interaction partners. The input is the user's feature vector, and the operation involves applying a compatibility calculation algorithm to select the optimal partner. The output is the interaction partners determined to be compatible.

[0232] Step 5:

[0233] The server notifies the terminal of the selected communication target via an information notification mechanism. The input is data of the optimal communication target, which is sent to the terminal using the communication mechanism to inform the user. The output is the notification information sent to the user.

[0234] Step 6:

[0235] When a user begins interacting, the terminal's emotion recognition system uses a camera and microphone to detect the user's emotional state in real time. The input consists of camera video and microphone audio data, and the system uses analysis software to analyze the emotional state. The output is information about the detected emotions.

[0236] Step 7:

[0237] The server, through an emotion recognition suggestion mechanism, utilizes a generative AI model to generate topics corresponding to the user's emotions and displays them on the terminal. The input is detected emotion information, and the generative AI model generates prompt sentences based on this data. The output is the suggested topic that is displayed.

[0238] Step 8:

[0239] The server combines the user's emotional state with local event information using a local activity suggestion system, and suggests events as needed. The input consists of emotional state information and local information, and the system's operation involves selecting and presenting appropriate events using an algorithm. The output is the event information suggested to the user.

[0240] Step 9:

[0241] The robot uses automated interaction support mechanisms to provide real-time communication tailored to the user's emotional state within the store. The input is the user's real-time emotional information, and the robot's operation involves adaptive interaction and support. The output is real-time interaction support.

[0242] Step 10:

[0243] The server uses health analysis tools to generate personalized health advice based on the user's emotional data and sends it to the terminal. The input is emotional data, and the system operates by generating health advice using a health management algorithm. The output is health advice information for the user.

[0244] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0245] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0246] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0247] [Second Embodiment]

[0248] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0249] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0250] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0251] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0252] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0253] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0254] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0255] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0256] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0257] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0258] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0259] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0260] This invention is an innovative system designed to prevent social isolation among the elderly and foster new relationships. The system provides technology for selecting optimal interaction partners based on user attribute information. Specifically, it accumulates data from users and analyzes it using a generative model to match compatible users.

[0261] First, the terminal provides the user with an input interface, allowing them to enter attribute information such as name, age, hobbies, and lifestyle. Once the information is entered, the terminal sends it to the server.

[0262] The server stores the received attribute information in a database using a data storage mechanism. Subsequently, a generative model analyzes the patterns of each user's hobbies and interests. The generative model extracts features from the data and generates an index to estimate the compatibility between users with similar characteristics.

[0263] For matched users, the server uses a notification system to send the result to the device, preparing to notify the user. This allows the user to connect online with compatible partners. The device provides communication methods such as messaging and video calls to facilitate online interaction.

[0264] Furthermore, the generative model automatically suggests useful topics during conversations, supporting the development of mutual interest. This facilitates smooth communication between users.

[0265] Furthermore, the server selects and suggests appropriate events based on local information, increasing opportunities for users to interact offline. This feature makes it easier for seniors to participate in community activities.

[0266] Health-related functions are also incorporated into this system. The terminal provides an interface for users to input their health status, and the server collects and analyzes this information. Based on the analysis results, it generates and presents personalized health advice to the user.

[0267] This system is expected to enable elderly people to build new relationships, avoid isolation, and lead fulfilling lives.

[0268] The following describes the processing flow.

[0269] Step 1:

[0270] The terminal displays an information input interface to the user. The user enters attribute information such as name, age, hobbies, past occupations, and lifestyle. Once the user has finished entering the information, the terminal sends the entered information to the server.

[0271] Step 2:

[0272] The server stores the received attribute information in a database. Using the stored data, it activates a generative model to analyze the user's hobbies and interests. This generates a feature vector for each user.

[0273] Step 3:

[0274] Based on the feature vectors calculated by the generative model, the server calculates a compatibility score between users. It selects the most compatible user pairs and generates this information as a matching result.

[0275] Step 4:

[0276] The server uses a notification mechanism to send information about the selected pair to the terminal in order to notify the user of the matching results. The receiving terminal displays this information to the user, allowing them to confirm the matching results.

[0277] Step 5:

[0278] Users can review the matching results and, if they wish to begin interacting, initiate video calls or messaging through their device. The device establishes the means of communication and supports interaction between users.

[0279] Step 6:

[0280] During interaction, the server uses a generative model to suggest topics based on shared hobbies and interests. This information is displayed to the user via their device and used to facilitate conversation.

[0281] Step 7:

[0282] The server checks the location information of the user and collects event information held in the area. It analyzes the collected event information and generates information for selecting and proposing events suitable for the user to participate in.

[0283] Step 8:

[0284] Regarding the health management function, the terminal provides a health information input screen, and the user inputs their own health information. The server analyzes the collected health data and generates and provides personalized health advice to the user.

[0285] (Example 1)

[0286] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0287] In modern society, there is a problem that it is difficult for the elderly to socially isolate and build new human relationships. Due to such social problems, the risk of the elderly suffering from mental and physical adverse effects is increasing. With conventional methods, it is difficult to effectively solve such problems, and a more efficient and individualized communication promotion system is required.

[0288] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following respective means.

[0289] In this invention, the server includes information recording means for storing attribute information collected from the user, feature analysis means for analyzing the user's characteristics using a generation model based on the attribute information, and compatibility evaluation means for predicting the compatibility between users and selecting an optimal communication partner. Thereby, it becomes possible to efficiently find an appropriate communication partner based on the attributes of the user, and for the elderly to build new human relationships.

[0290] "Information recording means" refers to means for securely and efficiently storing attribute information collected from users.

[0291] A "feature analysis method" is a means of analyzing the characteristics of a user in detail using a generative model based on the user's attribute information that has been collected.

[0292] A "compatibility evaluation method" is a means of predicting compatibility between users and selecting the most suitable interaction partners.

[0293] A "notification function" is a means of quickly and accurately notifying the user of the matching results.

[0294] "Communication support means" refers to means that provide communication functions to enable users to interact smoothly with other users.

[0295] A "topic suggestion tool" is a method that uses generative models to suggest useful topics in order to facilitate interaction among users.

[0296] An "event recommendation method" is a means of suggesting activities or events suitable for users based on local information.

[0297] A "health promotion tool" is a means of analyzing a user's health status information and generating personalized health advice.

[0298] This invention is a system designed to prevent social isolation among the elderly and to help them build new relationships. This system provides technology for selecting the most suitable partners for interaction based on the user's attribute information.

[0299] The terminal provides the user with an input interface, allowing them to enter attribute information such as name, age, hobbies, and lifestyle. This interface is designed to allow for accurate information entry using a touchscreen or keyboard. The entered information is transmitted to the server via protocols such as SSL over the internet.

[0300] The server stores the received attribute information in a database system (e.g., MySQL, PostgreSQL). This information is securely managed to protect user privacy and maintain data consistency. Subsequently, a generative AI model is used to analyze each user's hobbies and interests. The machine learning algorithms used (e.g., clustering, classification) are designed to efficiently process large amounts of data and perform feature extraction.

[0301] Users can receive matching results sent from their devices and interact online. Chat apps and video call tools are provided as means of interaction, enabling communication that transcends physical distance.

[0302] This system also features a generative AI model that automatically suggests topics to support the conversation as needed. A possible example of a prompt would be: "A 75-year-old man, whose hobbies are gardening and local history. Please recommend someone suitable to interact with." Upon entering this prompt, the AI ​​begins processing to recommend a suitable partner.

[0303] Furthermore, the system has a function that suggests events suitable for the user based on local information, thereby increasing opportunities for offline interaction. This event suggestion function uses a map service API to provide appropriate event information based on the user's location.

[0304] Finally, the terminal provides an interface for users to input information about their health status, and the server analyzes this information to generate personalized health advice. Through these processes, users can implement health management tailored to their individual needs.

[0305] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0306] Step 1:

[0307] The terminal provides an input interface to the user and allows the user to input attribute information such as name, age, hobbies, lifestyle, etc. The input is performed by typing or selecting information in a form on the screen. When the send button is pressed to confirm this input data, the data is confirmed. The input information is sent to the next process with the user's consent.

[0308] Step 2:

[0309] The terminal sends the input attribute information to the server using the SSL protocol. The data to be sent is encrypted and securely transferred through the network. As a specific operation, after pressing the send button, it is designed to reach the server via the Internet as data packets.

[0310] Step 3:

[0311] The server verifies the received attribute information, confirms its security, and then saves it in the database. In this process, a database management system is used, and a database insertion operation is performed to map the data to the correct fields. The input is user attribute information, and the output is the information that has been successfully stored.

[0312] Step 4:

[0313] The server activates an AI model generated based on the stored attribute information and analyzes the user's characteristics. In this analysis, machine learning algorithms (such as clustering and classification) are used to analyze patterns and trends from the obtained dataset. The input is the user's attribute information, and the output is the analyzed characteristic data.

[0314] Step 5:

[0315] The server performs compatibility evaluations based on feature data analyzed by a generative AI model and selects the most suitable interaction partners. This evaluation includes similarity calculations, quantifying compatibility with other users who have similar characteristics. The input is feature data, and the output is a compatibility evaluation value and a list of optimal partners.

[0316] Step 6:

[0317] The server sends the compatibility evaluation results to the terminal and notifies the user of the results. Real-time push notifications and email notifications are used as notification methods, allowing the user to check the results immediately. The input is the compatibility evaluation result, and the output is the notification message.

[0318] Step 7:

[0319] The device provides users with online communication tools through messaging and video call functions. This allows them to communicate directly with selected individuals. Specific actions include launching related applications and starting sessions.

[0320] Step 8:

[0321] The generative AI model suggests useful topics during conversations as needed. The suggested topics are tailored to the user's interests based on pre-set prompt sentences. The input is a prompt sentence, and the output is a list of recommended topics.

[0322] Step 9:

[0323] The server suggests events based on local information, recommending activities that match the user's geographical location. This function accesses a map service API and filters and provides events based on the user's location. The input is the user's location information, and the output is a list of suggested events.

[0324] (Application Example 1)

[0325] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0326] To help older adults overcome social isolation and build new relationships, it is crucial to find appropriate partners and engage in meaningful conversations and activities. However, finding suitable partners and providing opportunities for interaction in the real world is difficult. Furthermore, opportunities for natural conversations with people who share similar hobbies and interests are also challenging. Therefore, there is a need for systems that support such interactions.

[0327] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0328] In this invention, the server includes data storage means for storing attribute information collected from users, analysis means for analyzing the characteristics of users using a generative model based on the attribute information, and compatibility estimation means for estimating compatibility between users and selecting the most suitable interaction partners. This enables users to engage in meaningful conversations and easily build new relationships in real-world interaction environments, with support from topic suggestion means.

[0329] A "data storage means" is a function that stores attribute information collected from users and makes it available for later analysis.

[0330] "Analysis tools" refer to functions that utilize generative models based on collected attribute information to analyze user characteristics in detail.

[0331] The "compatibility estimation method" is a function that analyzes commonalities and interests between users and selects the most suitable person to interact with.

[0332] A "notification method" is a function that quickly communicates matching results to the user and prompts them to take the next action.

[0333] "Means of facilitating interaction" refers to a function that provides the necessary communication means to enable users to interact effectively with each other.

[0334] A "topic suggestion tool" is a function that uses a generative model to automatically suggest topics useful for interaction, thereby facilitating smooth conversation.

[0335] A "display means" is a function that visually presents appropriate interaction targets or events to the user in a real-world interaction environment.

[0336] "Communication support means" refers to functions that support real-time interaction with other users and facilitate smooth communication.

[0337] To implement this invention, the system includes a program that collects and analyzes attribute information and performs appropriate matching between users. The server stores user attribute information obtained from devices such as smartphones and tablets in a data storage means. This information includes name, age, interests, lifestyle, and health status. This information is managed by a database management system (e.g., PostgreSQL). Furthermore, a wide-area network (e.g., the Internet) is used as a means of communication to enable bidirectional transmission and reception of information.

[0338] The server utilizes generative AI models based on TensorFlow and PyTorch to analyze the received attribute information and understand the user's characteristics, such as interests and hobbies. Based on this analysis, it estimates compatibility between users with shared interests and uses AI to select appropriate interaction partners. Users are notified in real time of matching results and interaction events using notification methods such as Firebase Cloud Messaging.

[0339] To facilitate interaction, the display system visualizes relevant interaction targets and related event information on the terminal's screen in a real-world interaction environment, making them suitable for the user. Furthermore, to facilitate conversation, a topic suggestion system is used, where a generative model automatically suggests topics that are likely to pique the user's interest. For example, a prompt might look like this:

[0340] Example of a prompt:

[0341] User A's information: Age = 70, Hobbies = Gardening, Health status = Good

[0342] Candidate information list: [User B: Age=72, Hobby=Gardening, Health=Good, User C: Age=65, Hobby=Reading, Health=Good]

[0343] Please use an AI model to suggest the most compatible match for user A.

[0344] Furthermore, communication support means allow users to interact with each other through real-time chat and video calls. This function is implemented using technologies such as WebRTC. For example, in a cafe space, if another user who enjoys gardening is approached by the AI, the AI ​​might suggest a topic like, "What kind of techniques do you use when growing this flower?", facilitating a conversation based on shared interests. Through these processes, users can build new relationships and deepen their social connections.

[0345] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0346] Step 1:

[0347] The device receives attribute information from the user, such as name, age, hobbies, lifestyle, and health status, through an input interface. This information becomes input data sent to the server and is formatted as a user profile.

[0348] Step 2:

[0349] The server registers the received user attribute information in the database using a data storage mechanism. The input here is raw data sent from the terminal, which is then stored as structured data by the database management system.

[0350] Step 3:

[0351] The server processes user information retrieved from the database using analytical tools and performs user characteristic analysis using a generative AI model (using TensorFlow or PyTorch). The input is attribute information, and the output is a user characteristic vector. This process extracts commonalities and interest trends.

[0352] Step 4:

[0353] The server uses a compatibility estimation method based on the analyzed feature vectors to estimate the compatibility between users. The input is a list of feature vectors, and the output is a list including matching scores. The generative AI model identifies users with high similarity and selects matching candidates.

[0354] Step 5:

[0355] The server sends the matching results to the terminal via a notification system, informing the user of information about potential matches. The input is the matching score and a list of candidates, and the output is a notification signal to the user. Because notifications are sent in real time, Firebase Cloud Messaging is used.

[0356] Step 6:

[0357] On the device, interaction facilitators are activated based on the matching information received by the user, providing communication functions such as video calls and chat. Input consists of notified interaction candidates and topic suggestions, while output is the actual communication log. WebRTC is used to enable real-time conversations.

[0358] Step 7:

[0359] The server then uses a generative AI model to execute a topic suggestion mechanism, proposing conversation topics based on shared hobbies and interests between users. The input is the profiles of the matching users, and the output is a list of suggested topics. This facilitates smooth interaction between users.

[0360] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0361] This invention is a system for promoting social interaction among the elderly while taking into account the user's emotional state. Based on the user's attribute information and emotional state, this system selects the most suitable person to interact with and supports smooth interaction.

[0362] First, the terminal provides an interface for the user to input their personal information. The user enters information about their name, age, hobbies, and lifestyle, and the terminal sends that information to the server.

[0363] Next, the server stores the transmitted attribute information in a database. It also activates an emotion engine to recognize the user's emotional state in real time from the video and audio captured during video calls and messaging. The acquired emotion data, combined with a generative model, constitutes the user's feature vector.

[0364] The server uses feature vectors to calculate the user's compatibility score and selects the most suitable interaction partners. During this process, consideration is also given to the user's emotional state, prioritizing matches where positive compatibility is expected. Information about the selected interaction partners is sent to the user's device via a notification system.

[0365] Upon receiving the notification, the user can begin interacting with the person presented via their device. The device provides the means for the user to make video calls and send messages.

[0366] During the interaction, the server suggests the most appropriate topics based on the user's emotions, as recognized by the emotion engine. These suggestions are displayed on the terminal and play a role in stimulating the interaction.

[0367] In addition, the server collects information on local events based on the user's location. If the emotional state recognized by the emotion engine is deemed suitable for going out or participating in social activities, the server suggests that the user participate in the event.

[0368] Regarding health management, the emotional engine considers the user's emotional state and generates specific health advice tailored to stress levels and mood swings. This allows users to benefit from more personalized health management.

[0369] Thus, by utilizing an emotion engine, the present invention can provide appropriate support tailored to the user's state, enabling more fulfilling social interaction and health management.

[0370] The following describes the processing flow.

[0371] Step 1:

[0372] The terminal displays a screen for the user to input attribute information. The user enters information such as name, age, hobbies, and lifestyle into the terminal. After input, the terminal sends the data to the server.

[0373] Step 2:

[0374] The server stores the received attribute information in a database. Based on the stored information, a generative model is used to generate a feature vector for the user. This feature vector indicates the user's preferences and interests.

[0375] Step 3:

[0376] When a user starts a conversation, the device monitors the video or voice call and passes the acquired audio and video data to the emotion engine. The emotion engine analyzes the user's tone of voice and facial expressions to generate emotion data.

[0377] Step 4:

[0378] The server combines the generated feature vectors with sentiment data to calculate a compatibility score between users. Based on the compatibility score, the matching system selects the most suitable interaction partners for each user.

[0379] Step 5:

[0380] The server sends the matching results to the device using a notification system. The device displays the notification to the user, encouraging interaction with the matched person. The notification also includes hints on the appropriate timing for interaction based on emotions.

[0381] Step 6:

[0382] During interaction, the server monitors the latest emotional data from the emotion engine. Based on this data, the server selects the most appropriate topics and sends suggestions to the terminal to enhance the interaction.

[0383] Step 7:

[0384] The server obtains the user's current location information and collects local event information. Considering the user's emotional state, it selects events appropriate to that situation and suggests participation.

[0385] Step 8:

[0386] The device collects health-related information entered by the user and sends it to a server. The server generates health advice, taking into account the user's emotional state, and provides it to the user. The tailored advice includes suggestions for stress management and activity levels.

[0387] (Example 2)

[0388] Next, we will describe Example 2. 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".

[0389] Social isolation and health management challenges among the elderly are becoming increasingly important. There is a need for support that allows seniors to connect with appropriate people and live healthy lives based on their emotional state, without feeling isolated. However, current systems do not adequately address the emotional states and individual health needs of users. Against this backdrop, there is a demand for a comprehensive and flexible system that enables seniors to lead richer social lives.

[0390] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0391] In this invention, the server includes data storage means for storing demographic data collected from users, analysis means for analyzing the individual characteristics of users using a generative model based on the demographic data and the users' emotional data, and compatibility selection means for estimating compatibility considering the emotional states between users and selecting the most suitable interaction partners. This enables users to prevent isolation and lead healthy and vibrant lives through appropriate interactions based on their emotional states.

[0392] A "data storage method" is a function that can stably store demographic data and sentiment data collected from users and retrieve them quickly as needed.

[0393] "Analysis tools" refer to functions that utilize collected data and generative models to comprehensively analyze the individual characteristics of users.

[0394] The "compatibility selection method" is a function that evaluates the user's emotional state, estimates their compatibility with other users based on that evaluation, and selects the most suitable person to interact with.

[0395] "Information provision means" refers to a function for transmitting information about selected interaction targets to users in an appropriate format.

[0396] A "communication support system" is a system that provides functions to enable users to communicate smoothly over long distances.

[0397] The "agenda proposal tool" is a function that uses a generative model to present agenda items suitable for the user, with the aim of stimulating interaction.

[0398] A "health guidance tool" is a function that develops and guides individual health plans based on the user's emotional state and health-related data.

[0399] The "activity suggestion tool" is a function that suggests social activities and events suitable for the user based on local information.

[0400] A "health management tool" is a function that evaluates the user's psychological state and generates and provides an individualized health strategy based on that evaluation.

[0401] This invention is a social interaction promotion system specifically designed for the elderly. This system utilizes user demographic and emotional data to select the most suitable interaction partners and support a healthy lifestyle.

[0402] First, the device provides an interface for users to input their demographic data, such as age, hobbies, and lifestyle. This typically involves a touchscreen or keyboard. It also includes a camera and microphone to collect emotional data.

[0403] The input data is transmitted to the server in real time. The server uses a high-performance database system to manage the data and general emotion engine software to analyze emotional data. A specific example of such software would be emotion recognition software. The server analyzes this data using a generative AI model (for example, a large-scale language model) to understand the user's individual characteristics.

[0404] Based on this analysis, the server selects the most suitable contact and notifies the user of that information. The notification is sent to the device via email or app push notification. The user then decides whether to interact based on the information presented.

[0405] Furthermore, the server collects information on local social activities and events based on the user's location and makes suggestions tailored to the user. Location-based services are used for this purpose. It can suggest events that will help the user refresh themselves, such as local concerts or craft classes.

[0406] In health management, the server uses collected information to suggest healthy lifestyle habits tailored to each individual user. For example, when a specific emotional state is detected, it can provide guidance on appropriate relaxation methods.

[0407] As a concrete example, the system operates based on the following prompt:

[0408] "Please suggest how to address the emotional state of users in order to promote social interaction among the elderly."

[0409] This system aims to support users in leading fulfilling lives while maintaining their health and avoiding social isolation.

[0410] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0411] Step 1:

[0412] The device collects demographic data from users. Specifically, users input information such as age, hobbies, and lifestyle through a touch panel or keyboard interface. This information is output as structured data, such as in JSON format, and sent to the server.

[0413] Step 2:

[0414] The server stores demographic data received from the terminal in a database. The received JSON data is stored as a database record, allowing for fast retrieval when needed. This is the data storage method, and the output is the data stored in the database.

[0415] Step 3:

[0416] The device collects user emotional data in real time. Specifically, it uses a camera to capture facial expressions and a microphone to record voice. This raw data is immediately transmitted to the server.

[0417] Step 4:

[0418] The server uses an emotion engine to analyze the received emotion data. It analyzes emotional states from video footage using facial recognition technology and measures tone from audio using speech analysis technology. This process outputs numerical data representing the emotional state.

[0419] Step 5:

[0420] The server uses demographic and sentiment data to analyze individual user characteristics using a generative AI model. Specifically, it uses a sentiment engine and machine learning libraries to represent user characteristics as feature vectors. These feature vectors are the output of the analysis.

[0421] Step 6:

[0422] The server uses a machine learning algorithm to calculate compatibility scores and select the most suitable interaction partners. Here, it analyzes the user's feature vectors and compares their compatibility with other users to select the most appropriate interaction partners. The selected candidates are then generated as output.

[0423] Step 7:

[0424] The server sends a notification to the user's device based on the information of the selected interaction partners. Using email or push notifications, it presents the user with the profiles and contact information of the selected partners. This is the output of the information provision.

[0425] Step 8:

[0426] The user initiates interaction via their device based on a notification from the server. Specifically, they use a video call application as a means of remote communication to communicate with the selected interaction partner. In this step, the output is successful communication.

[0427] (Application Example 2)

[0428] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0429] There is a need to promote social interaction among the elderly and provide appropriate communication tailored to their emotional state. However, existing systems have had problems in promoting interaction while adequately considering the user's feelings. Furthermore, the provision of information to support individual interactions and participation in social activities has been limited, and there has been a lack of mechanisms that allow the elderly to actively participate in particular.

[0430] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0431] In this invention, the server includes a storage means for storing attribute information collected from the user, an analysis means for analyzing the user's characteristics, and an emotion recognition suggestion means for analyzing the user's emotional state and suggesting appropriate topics. This makes it possible to select the optimal interaction partners, suggest topics for interaction, and provide information on local activities while taking the user's emotional state into consideration.

[0432] A "memory device" is a device that has the function of storing the user's attribute information.

[0433] An "analysis tool" is a device that has the function of analyzing attribute information and emotional states obtained from the user and extracting characteristics.

[0434] A "prediction means" is a device that has the function of predicting compatibility between users and selecting the optimal interaction partner.

[0435] An "information notification device" is a device that has the function of informing the user of the results obtained from analysis or estimation.

[0436] A "communication support device" is a device that provides the infrastructure for users to make calls and communicate, and has functions to promote communication.

[0437] A "content suggestion device" is a device that has the function of providing users with topics and information for interaction using a generative model.

[0438] An "emotion recognition suggestion device" is a device that has the function of detecting the user's emotional state and suggesting an appropriate topic according to that state.

[0439] A "community activity suggestion device" is a device that has the function of suggesting events and activities within a community based on the user's emotional state and local information.

[0440] An "automated interaction support device" is a device that uses robots or other means to provide real-time interaction support tailored to the user's emotional state.

[0441] A "health analysis device" is a device that analyzes the user's emotional state and generates personalized health management advice.

[0442] To implement this invention, first, the terminal receives attribute information from the user and transmits it to the server. The server stores this attribute information in a storage means and extracts the user's characteristics using an analysis means. Next, an estimation means calculates the compatibility between users based on these characteristics and selects the optimal interaction partner. This result is communicated to the user via an information notification means.

[0443] When a user begins interacting, the emotion recognition suggestion system uses hardware such as cameras and microphones to recognize the user's emotional state in real time and provides appropriate topics based on that situation using a generative AI model. For example, if the generative AI model detects that the user is excited, it will generate a prompt such as, "How about talking about the recent weather or seasons?"

[0444] Furthermore, the server uses a local activity suggestion system to combine the user's emotional state with local event information and suggests participation in events if it determines that going out is appropriate. In addition, robots equipped with automated interaction support systems provide real-time support for interactions with the user in stores and other locations. This allows users to maintain social connections with peace of mind.

[0445] Simultaneously, the health analysis system generates personalized health advice based on the user's emotional data. This allows users to receive specific advice that helps maintain their health. Thus, the present invention is a system that provides comprehensive support for the social interaction and health management of the elderly.

[0446] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0447] Step 1:

[0448] The terminal receives attribute information (name, age, hobbies, lifestyle, etc.) from the user and sends that data to the server. Its operation involves acquiring the user's attribute information as input and sending it to the server using a communication method. The output is the user's attribute information sent to the server.

[0449] Step 2:

[0450] The server stores the attribute information it receives in its memory. Its operation involves receiving attribute information sent from a terminal as input and saving it to a database as preparation for analysis. The output is the data saved for analysis.

[0451] Step 3:

[0452] The server uses analytical means to analyze the user's characteristics using a generative AI model and generates a feature vector for the user. The input is attribute information stored in a memory device, and the operation involves vectorizing the data using the generative model and extracting features. The output is the feature-vectorized user information.

[0453] Step 4:

[0454] The server uses estimation methods to calculate compatibility scores between users based on feature vectors and selects the most suitable interaction partners. The input is the user's feature vector, and the operation involves applying a compatibility calculation algorithm to select the optimal partner. The output is the interaction partners determined to be compatible.

[0455] Step 5:

[0456] The server notifies the terminal of the selected communication target via an information notification mechanism. The input is data of the optimal communication target, which is sent to the terminal using the communication mechanism to inform the user. The output is the notification information sent to the user.

[0457] Step 6:

[0458] When a user begins interacting, the terminal's emotion recognition system uses a camera and microphone to detect the user's emotional state in real time. The input consists of camera video and microphone audio data, and the system uses analysis software to analyze the emotional state. The output is information about the detected emotions.

[0459] Step 7:

[0460] The server, through an emotion recognition suggestion mechanism, utilizes a generative AI model to generate topics corresponding to the user's emotions and displays them on the terminal. The input is detected emotion information, and the generative AI model generates prompt sentences based on this data. The output is the suggested topic that is displayed.

[0461] Step 8:

[0462] The server combines the user's emotional state with local event information using a local activity suggestion system, and suggests events as needed. The input consists of emotional state information and local information, and the system's operation involves selecting and presenting appropriate events using an algorithm. The output is the event information suggested to the user.

[0463] Step 9:

[0464] The robot uses automated interaction support mechanisms to provide real-time communication tailored to the user's emotional state within the store. The input is the user's real-time emotional information, and the robot's operation involves adaptive interaction and support. The output is real-time interaction support.

[0465] Step 10:

[0466] The server uses health analysis tools to generate personalized health advice based on the user's emotional data and sends it to the terminal. The input is emotional data, and the system operates by generating health advice using a health management algorithm. The output is health advice information for the user.

[0467] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0468] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0469] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0470] [Third Embodiment]

[0471] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0472] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0473] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0474] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0475] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0476] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0477] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0478] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0479] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0480] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0481] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0482] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0483] This invention is an innovative system designed to prevent social isolation among the elderly and foster new relationships. The system provides technology for selecting optimal interaction partners based on user attribute information. Specifically, it accumulates data from users and analyzes it using a generative model to match compatible users.

[0484] First, the terminal provides the user with an input interface, allowing them to enter attribute information such as name, age, hobbies, and lifestyle. Once the information is entered, the terminal sends it to the server.

[0485] The server stores the received attribute information in a database using a data storage mechanism. Subsequently, a generative model analyzes the patterns of each user's hobbies and interests. The generative model extracts features from the data and generates an index to estimate the compatibility between users with similar characteristics.

[0486] For matched users, the server uses a notification system to send the result to the device, preparing to notify the user. This allows the user to connect online with compatible partners. The device provides communication methods such as messaging and video calls to facilitate online interaction.

[0487] Furthermore, the generative model automatically suggests useful topics during conversations, supporting the development of mutual interest. This facilitates smooth communication between users.

[0488] Furthermore, the server selects and suggests appropriate events based on local information, increasing opportunities for users to interact offline. This feature makes it easier for seniors to participate in community activities.

[0489] Health-related functions are also incorporated into this system. The terminal provides an interface for the user to input their health status, and the server collects and analyzes that information. Based on the analysis results, it generates and presents personalized health advice to the user.

[0490] This system is expected to enable elderly people to build new relationships, avoid isolation, and lead fulfilling lives.

[0491] The following describes the processing flow.

[0492] Step 1:

[0493] The terminal displays an information input interface to the user. The user enters attribute information such as name, age, hobbies, past occupations, and lifestyle. Once the user has finished entering the information, the terminal sends the entered information to the server.

[0494] Step 2:

[0495] The server stores the received attribute information in a database. Using the stored data, it activates a generative model to analyze the user's hobbies and interests. This generates a feature vector for each user.

[0496] Step 3:

[0497] Based on the feature vectors calculated by the generative model, the server calculates a compatibility score between users. It selects the most compatible user pairs and generates this information as a matching result.

[0498] Step 4:

[0499] The server uses a notification mechanism to send information about the selected pair to the terminal in order to notify the user of the matching results. The receiving terminal displays this information to the user, allowing them to confirm the matching results.

[0500] Step 5:

[0501] Users can review the matching results and, if they wish to begin interacting, initiate video calls or messaging through their device. The device establishes the means of communication and supports interaction between users.

[0502] Step 6:

[0503] During interaction, the server uses a generative model to suggest topics based on shared hobbies and interests. This information is displayed to the user via their device and used to facilitate conversation.

[0504] Step 7:

[0505] The server verifies the user's location and collects information on events happening in the area. It analyzes the collected event information and generates data to select and suggest events that are suitable for the user to attend.

[0506] Step 8:

[0507] Regarding the health management function, the terminal provides a health information input screen, and the user enters their own health information. The server analyzes the collected health data and generates and provides personalized health advice to the user.

[0508] (Example 1)

[0509] Next, we will describe Example 1. 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."

[0510] In modern society, the problem of social isolation and difficulty in building new relationships exists among the elderly. These social problems increase the risk of negative mental and physical effects on the elderly. Traditional methods are ineffective in solving these problems, and a more efficient and individualized system for promoting social interaction is needed.

[0511] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0512] In this invention, the server includes an information recording means for storing attribute information collected from the user, a feature analysis means for analyzing the user's characteristics using a generative model based on the attribute information, and a compatibility evaluation means for predicting compatibility between users and selecting the optimal interaction partner. This enables the efficient search for appropriate interaction partners based on the user's attributes, making it possible for elderly people to build new relationships.

[0513] "Information recording means" refers to means for securely and efficiently storing attribute information collected from users.

[0514] A "feature analysis method" is a means of analyzing the characteristics of a user in detail using a generative model based on the user's attribute information that has been collected.

[0515] A "compatibility evaluation method" is a means of predicting compatibility between users and selecting the most suitable interaction partners.

[0516] A "notification function" is a means of quickly and accurately notifying the user of the matching results.

[0517] "Communication support means" refers to means that provide communication functions to enable users to interact smoothly with other users.

[0518] A "topic suggestion tool" is a method that uses generative models to suggest useful topics in order to facilitate interaction among users.

[0519] An "event recommendation method" is a means of suggesting activities or events suitable for users based on local information.

[0520] A "health promotion tool" is a means of analyzing a user's health status information and generating personalized health advice.

[0521] This invention is a system designed to prevent social isolation among the elderly and to help them build new relationships. This system provides technology for selecting the most suitable partners for interaction based on the user's attribute information.

[0522] The terminal provides the user with an input interface, allowing them to enter attribute information such as name, age, hobbies, and lifestyle. This interface is designed to allow for accurate information entry using a touchscreen or keyboard. The entered information is transmitted to the server via protocols such as SSL over the internet.

[0523] The server stores the received attribute information in a database system (e.g., MySQL, PostgreSQL). This information is securely managed to protect user privacy and maintain data consistency. Subsequently, a generative AI model is used to analyze each user's hobbies and interests. The machine learning algorithms used (e.g., clustering, classification) are designed to efficiently process large amounts of data and perform feature extraction.

[0524] Users can receive matching results sent from their devices and interact online. Chat apps and video call tools are provided as means of interaction, enabling communication that transcends physical distance.

[0525] This system also features a generative AI model that automatically suggests topics to support the conversation as needed. A possible example of a prompt would be: "A 75-year-old man, whose hobbies are gardening and local history. Please recommend someone suitable to interact with." Upon entering this prompt, the AI ​​begins processing to recommend a suitable partner.

[0526] Furthermore, the system has a function that suggests events suitable for the user based on local information, thereby increasing opportunities for offline interaction. This event suggestion function uses a map service API to provide appropriate event information based on the user's location.

[0527] Finally, the terminal provides an interface for users to input information about their health status, and the server analyzes this information to generate personalized health advice. Through these processes, users can implement health management tailored to their individual needs.

[0528] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0529] Step 1:

[0530] The terminal provides the user with an input interface, allowing them to enter attribute information such as name, age, hobbies, and lifestyle. Input is performed by typing or selecting information into a form on the screen. The data is confirmed when the user presses the submit button. The entered information is then sent to the next processing step with the user's consent.

[0531] Step 2:

[0532] The terminal sends the entered attribute information to the server using the SSL protocol. The transmitted data is encrypted and securely transferred over the network. Specifically, after pressing the send button, the data packet arrives on the server via the internet.

[0533] Step 3:

[0534] The server verifies the received attribute information, confirms its security, and then stores it in the database. This process uses a database management system and performs database insertion operations to ensure the data is mapped to the correct fields. The input is user attribute information, and the output is the successfully stored information.

[0535] Step 4:

[0536] The server activates a generated AI model based on stored attribute information to analyze the user's characteristics. This analysis uses machine learning algorithms (clustering and classification) to analyze patterns and trends from the resulting dataset. The input is the user's attribute information, and the output is the analyzed characteristic data.

[0537] Step 5:

[0538] The server performs compatibility evaluations based on feature data analyzed by a generative AI model and selects the most suitable interaction partners. This evaluation includes similarity calculations, quantifying compatibility with other users who have similar characteristics. The input is feature data, and the output is a compatibility evaluation value and a list of optimal partners.

[0539] Step 6:

[0540] The server sends the compatibility evaluation results to the terminal and notifies the user of the results. Real-time push notifications and email notifications are used as notification methods, allowing the user to check the results immediately. The input is the compatibility evaluation result, and the output is the notification message.

[0541] Step 7:

[0542] The device provides users with online communication tools through messaging and video call functions. This allows them to communicate directly with selected individuals. Specific actions include launching related applications and starting sessions.

[0543] Step 8:

[0544] The generative AI model suggests useful topics during conversations as needed. The suggested topics are tailored to the user's interests based on pre-set prompt sentences. The input is a prompt sentence, and the output is a list of recommended topics.

[0545] Step 9:

[0546] The server suggests events based on local information, recommending activities that match the user's geographical location. This function accesses a map service API and filters and provides events based on the user's location. The input is the user's location information, and the output is a list of suggested events.

[0547] (Application Example 1)

[0548] Next, we will explain Application Example 1. In the following explanation, 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."

[0549] To help older adults overcome social isolation and build new relationships, it is crucial to find appropriate partners and engage in meaningful conversations and activities. However, finding suitable partners and providing opportunities for interaction in the real world is difficult. Furthermore, opportunities for natural conversations with people who share similar hobbies and interests are also challenging. Therefore, there is a need for systems that support such interactions.

[0550] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0551] In this invention, the server includes data storage means for storing attribute information collected from users, analysis means for analyzing the characteristics of users using a generative model based on the attribute information, and compatibility estimation means for estimating compatibility between users and selecting the most suitable interaction partners. This enables users to engage in meaningful conversations and easily build new relationships in real-world interaction environments, with support from topic suggestion means.

[0552] A "data storage means" is a function that stores attribute information collected from users and makes it available for later analysis.

[0553] "Analysis tools" refer to functions that utilize generative models based on collected attribute information to analyze user characteristics in detail.

[0554] The "compatibility estimation method" is a function that analyzes commonalities and interests between users and selects the most suitable person to interact with.

[0555] A "notification method" is a function that quickly communicates matching results to the user and prompts them to take the next action.

[0556] "Means of facilitating interaction" refers to a function that provides the necessary communication means to enable users to interact effectively with each other.

[0557] A "topic suggestion tool" is a function that uses a generative model to automatically suggest topics useful for interaction, thereby facilitating smooth conversation.

[0558] A "display means" is a function that visually presents appropriate interaction targets or events to the user in a real-world interaction environment.

[0559] "Communication support means" refers to functions that support real-time interaction with other users and facilitate smooth communication.

[0560] To implement this invention, the system includes a program that collects and analyzes attribute information and performs appropriate matching between users. The server stores user attribute information obtained from devices such as smartphones and tablets in a data storage means. This information includes name, age, interests, lifestyle, and health status. This information is managed by a database management system (e.g., PostgreSQL). Furthermore, a wide-area network (e.g., the Internet) is used as a means of communication to enable bidirectional transmission and reception of information.

[0561] The server utilizes generative AI models based on TensorFlow and PyTorch to analyze the received attribute information and understand the user's characteristics, such as interests and hobbies. Based on this analysis, it estimates compatibility between users with shared interests and uses AI to select appropriate interaction partners. Users are notified in real time of matching results and interaction events using notification methods such as Firebase Cloud Messaging.

[0562] To facilitate interaction, the display system visualizes relevant interaction targets and related event information on the terminal's screen in a real-world interaction environment, making them suitable for the user. Furthermore, to facilitate conversation, a topic suggestion system is used, where a generative model automatically suggests topics that are likely to pique the user's interest. For example, a prompt might look like this:

[0563] Example of a prompt:

[0564] User A's information: Age = 70, Hobbies = Gardening, Health status = Good

[0565] Candidate information list: [User B: Age=72, Hobby=Gardening, Health=Good, User C: Age=65, Hobby=Reading, Health=Good]

[0566] Please use an AI model to suggest the most compatible match for user A.

[0567] Furthermore, communication support means allow users to interact with each other through real-time chat and video calls. This function is implemented using technologies such as WebRTC. For example, in a cafe space, if another user who enjoys gardening is approached by the AI, the AI ​​might suggest a topic like, "What kind of techniques do you use when growing this flower?", facilitating a conversation based on shared interests. Through these processes, users can build new relationships and deepen their social connections.

[0568] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0569] Step 1:

[0570] The device receives attribute information from the user, such as name, age, hobbies, lifestyle, and health status, through an input interface. This information becomes input data sent to the server and is formatted as a user profile.

[0571] Step 2:

[0572] The server registers the received user attribute information in the database using a data storage mechanism. The input here is raw data sent from the terminal, which is then stored as structured data by the database management system.

[0573] Step 3:

[0574] The server processes user information retrieved from the database using analytical tools and performs user characteristic analysis using a generative AI model (using TensorFlow or PyTorch). The input is attribute information, and the output is a user characteristic vector. This process extracts commonalities and interest trends.

[0575] Step 4:

[0576] The server uses a compatibility estimation method based on the analyzed feature vectors to estimate the compatibility between users. The input is a list of feature vectors, and the output is a list including matching scores. The generative AI model identifies users with high similarity and selects matching candidates.

[0577] Step 5:

[0578] The server sends the matching results to the terminal via a notification system, informing the user of information about potential matches. The input is the matching score and a list of candidates, and the output is a notification signal to the user. Because notifications are sent in real time, Firebase Cloud Messaging is used.

[0579] Step 6:

[0580] On the device, interaction facilitators are activated based on the matching information received by the user, providing communication functions such as video calls and chat. Input consists of notified interaction candidates and topic suggestions, while output is the actual communication log. WebRTC is used to enable real-time conversations.

[0581] Step 7:

[0582] The server then uses a generative AI model to execute a topic suggestion mechanism, proposing conversation topics based on shared hobbies and interests between users. The input is the profiles of the matching users, and the output is a list of suggested topics. This facilitates smooth interaction between users.

[0583] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0584] This invention is a system for promoting social interaction among the elderly while taking into account the user's emotional state. Based on the user's attribute information and emotional state, this system selects the most suitable person to interact with and supports smooth interaction.

[0585] First, the terminal provides an interface for the user to input their personal information. The user enters information about their name, age, hobbies, and lifestyle, and the terminal sends that information to the server.

[0586] Next, the server stores the transmitted attribute information in a database. It also activates an emotion engine to recognize the user's emotional state in real time from the video and audio captured during video calls and messaging. The acquired emotion data, combined with a generative model, constitutes the user's feature vector.

[0587] The server uses feature vectors to calculate the user's compatibility score and selects the most suitable interaction partners. During this process, consideration is also given to the user's emotional state, prioritizing matches where positive compatibility is expected. Information about the selected interaction partners is sent to the user's device via a notification system.

[0588] Upon receiving the notification, the user can begin interacting with the person presented via their device. The device provides the means for the user to make video calls and send messages.

[0589] During the interaction, the server suggests the most appropriate topics based on the user's emotions, as recognized by the emotion engine. These suggestions are displayed on the terminal and play a role in stimulating the interaction.

[0590] In addition, the server collects information on local events based on the user's location. If the emotional state recognized by the emotion engine is deemed suitable for going out or participating in social activities, the server suggests that the user participate in the event.

[0591] Regarding health management, the emotional engine considers the user's emotional state and generates specific health advice tailored to stress levels and mood swings. This allows users to benefit from more personalized health management.

[0592] Thus, by utilizing an emotion engine, the present invention can provide appropriate support tailored to the user's state, enabling more fulfilling social interaction and health management.

[0593] The following describes the processing flow.

[0594] Step 1:

[0595] The terminal displays a screen for the user to input attribute information. The user enters information such as name, age, hobbies, and lifestyle into the terminal. After input, the terminal sends the data to the server.

[0596] Step 2:

[0597] The server stores the received attribute information in a database. Based on the stored information, a generative model is used to generate a feature vector for the user. This feature vector indicates the user's preferences and interests.

[0598] Step 3:

[0599] When a user starts a conversation, the device monitors the video or voice call and passes the acquired audio and video data to the emotion engine. The emotion engine analyzes the user's tone of voice and facial expressions to generate emotion data.

[0600] Step 4:

[0601] The server combines the generated feature vectors with sentiment data to calculate a compatibility score between users. Based on the compatibility score, the matching system selects the most suitable interaction partners for each user.

[0602] Step 5:

[0603] The server sends the matching results to the device using a notification system. The device displays the notification to the user, encouraging interaction with the matched person. The notification also includes hints on the appropriate timing for interaction based on emotions.

[0604] Step 6:

[0605] During interaction, the server monitors the latest emotional data from the emotion engine. Based on this data, the server selects the most appropriate topics and sends suggestions to the terminal to enhance the interaction.

[0606] Step 7:

[0607] The server obtains the user's current location information and collects local event information. Considering the user's emotional state, it selects events appropriate to that situation and suggests participation.

[0608] Step 8:

[0609] The device collects health-related information entered by the user and sends it to a server. The server generates health advice, taking into account the user's emotional state, and provides it to the user. The tailored advice includes suggestions for stress management and activity levels.

[0610] (Example 2)

[0611] Next, we will describe Example 2. 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."

[0612] Social isolation and health management challenges among the elderly are becoming increasingly important. There is a need for support that allows seniors to connect with appropriate people and live healthy lives based on their emotional state, without feeling isolated. However, current systems do not adequately address the emotional states and individual health needs of users. Against this backdrop, there is a demand for a comprehensive and flexible system that enables seniors to lead richer social lives.

[0613] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0614] In this invention, the server includes data storage means for storing demographic data collected from users, analysis means for analyzing the individual characteristics of users using a generative model based on the demographic data and the users' emotional data, and compatibility selection means for estimating compatibility considering the emotional states between users and selecting the most suitable interaction partners. This enables users to prevent isolation and lead healthy and vibrant lives through appropriate interactions based on their emotional states.

[0615] A "data storage method" is a function that can stably store demographic data and sentiment data collected from users and retrieve them quickly as needed.

[0616] "Analysis tools" refer to functions that utilize collected data and generative models to comprehensively analyze the individual characteristics of users.

[0617] The "compatibility selection method" is a function that evaluates the user's emotional state, estimates their compatibility with other users based on that evaluation, and selects the most suitable person to interact with.

[0618] "Information provision means" refers to a function for transmitting information about selected interaction targets to users in an appropriate format.

[0619] A "communication support system" is a system that provides functions to enable users to communicate smoothly over long distances.

[0620] The "agenda proposal tool" is a function that uses a generative model to present agenda items suitable for the user, with the aim of stimulating interaction.

[0621] A "health guidance tool" is a function that develops and guides individual health plans based on the user's emotional state and health-related data.

[0622] The "activity suggestion tool" is a function that suggests social activities and events suitable for the user based on local information.

[0623] A "health management tool" is a function that evaluates the user's psychological state and generates and provides an individualized health strategy based on that evaluation.

[0624] This invention is a social interaction promotion system specifically designed for the elderly. This system utilizes user demographic and emotional data to select the most suitable interaction partners and support a healthy lifestyle.

[0625] First, the device provides an interface for users to input their demographic data, such as age, hobbies, and lifestyle. This typically involves a touchscreen or keyboard. It also includes a camera and microphone to collect emotional data.

[0626] The input data is transmitted to the server in real time. The server uses a high-performance database system to manage the data and general emotion engine software to analyze emotional data. A specific example of such software would be emotion recognition software. The server analyzes this data using a generative AI model (for example, a large-scale language model) to understand the user's individual characteristics.

[0627] Based on this analysis, the server selects the most suitable contact and notifies the user of that information. The notification is sent to the device via email or app push notification. The user then decides whether to interact based on the information presented.

[0628] Furthermore, the server collects information on local social activities and events based on the user's location and makes suggestions tailored to the user. Location-based services are used for this purpose. It can suggest events that will help the user refresh themselves, such as local concerts or craft classes.

[0629] In health management, the server uses collected information to suggest healthy lifestyle habits tailored to each individual user. For example, when a specific emotional state is detected, it can provide guidance on appropriate relaxation methods.

[0630] As a concrete example, the system operates based on the following prompt:

[0631] "Please suggest how to address the emotional state of users in order to promote social interaction among the elderly."

[0632] This system aims to support users in leading fulfilling lives while maintaining their health and avoiding social isolation.

[0633] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0634] Step 1:

[0635] The device collects demographic data from users. Specifically, users input information such as age, hobbies, and lifestyle through a touch panel or keyboard interface. This information is output as structured data, such as in JSON format, and sent to the server.

[0636] Step 2:

[0637] The server stores demographic data received from the terminal in a database. The received JSON data is stored as a database record, allowing for fast retrieval when needed. This is the data storage method, and the output is the data stored in the database.

[0638] Step 3:

[0639] The device collects user emotional data in real time. Specifically, it uses a camera to capture facial expressions and a microphone to record voice. This raw data is immediately transmitted to the server.

[0640] Step 4:

[0641] The server uses an emotion engine to analyze the received emotion data. It analyzes emotional states from video footage using facial recognition technology and measures tone from audio using speech analysis technology. This process outputs numerical data representing the emotional state.

[0642] Step 5:

[0643] The server uses demographic and sentiment data to analyze individual user characteristics using a generative AI model. Specifically, it uses a sentiment engine and machine learning libraries to represent user characteristics as feature vectors. These feature vectors are the output of the analysis.

[0644] Step 6:

[0645] The server uses a machine learning algorithm to calculate compatibility scores and select the most suitable interaction partners. Here, it analyzes the user's feature vectors and compares their compatibility with other users to select the most appropriate interaction partners. The selected candidates are then generated as output.

[0646] Step 7:

[0647] The server sends a notification to the user's device based on the information of the selected interaction partners. Using email or push notifications, it presents the user with the profiles and contact information of the selected partners. This is the output of the information provision.

[0648] Step 8:

[0649] The user initiates interaction via their device based on a notification from the server. Specifically, they use a video call application as a means of remote communication to communicate with the selected interaction partner. In this step, the output is successful communication.

[0650] (Application Example 2)

[0651] Next, we will explain application example 2. In the following explanation, 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."

[0652] There is a need to promote social interaction among the elderly and provide appropriate communication tailored to their emotional state. However, existing systems have had problems in promoting interaction while adequately considering the user's feelings. Furthermore, the provision of information to support individual interactions and participation in social activities has been limited, and there has been a lack of mechanisms that allow the elderly to actively participate in particular.

[0653] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0654] In this invention, the server includes a storage means for storing attribute information collected from the user, an analysis means for analyzing the user's characteristics, and an emotion recognition suggestion means for analyzing the user's emotional state and suggesting appropriate topics. This makes it possible to select the optimal interaction partners, suggest topics for interaction, and provide information on local activities while taking the user's emotional state into consideration.

[0655] A "memory device" is a device that has the function of storing the user's attribute information.

[0656] An "analysis tool" is a device that has the function of analyzing attribute information and emotional states obtained from the user and extracting characteristics.

[0657] A "prediction means" is a device that has the function of predicting compatibility between users and selecting the optimal interaction partner.

[0658] An "information notification device" is a device that has the function of informing the user of the results obtained from analysis or estimation.

[0659] A "communication support device" is a device that provides the infrastructure for users to make calls and communicate, and has functions to promote communication.

[0660] A "content suggestion device" is a device that has the function of providing users with topics and information for interaction using a generative model.

[0661] An "emotion recognition suggestion device" is a device that has the function of detecting the user's emotional state and suggesting an appropriate topic according to that state.

[0662] A "community activity suggestion device" is a device that has the function of suggesting events and activities within a community based on the user's emotional state and local information.

[0663] An "automated interaction support device" is a device that uses robots or other means to provide real-time interaction support tailored to the user's emotional state.

[0664] A "health analysis device" is a device that analyzes the user's emotional state and generates personalized health management advice.

[0665] To implement this invention, first, the terminal receives attribute information from the user and transmits it to the server. The server stores this attribute information in a storage means and extracts the user's characteristics using an analysis means. Next, an estimation means calculates the compatibility between users based on these characteristics and selects the optimal interaction partner. This result is communicated to the user via an information notification means.

[0666] When a user begins interacting, the emotion recognition suggestion system uses hardware such as cameras and microphones to recognize the user's emotional state in real time and provides appropriate topics based on that situation using a generative AI model. For example, if the generative AI model detects that the user is excited, it will generate a prompt such as, "How about talking about the recent weather or seasons?"

[0667] Furthermore, the server uses a local activity suggestion system to combine the user's emotional state with local event information and suggests participation in events if it determines that going out is appropriate. In addition, robots equipped with automated interaction support systems provide real-time support for interactions with the user in stores and other locations. This allows users to maintain social connections with peace of mind.

[0668] Simultaneously, the health analysis system generates personalized health advice based on the user's emotional data. This allows users to receive specific advice that helps maintain their health. Thus, the present invention is a system that provides comprehensive support for the social interaction and health management of the elderly.

[0669] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0670] Step 1:

[0671] The terminal receives attribute information (name, age, hobbies, lifestyle, etc.) from the user and sends that data to the server. Its operation involves acquiring the user's attribute information as input and sending it to the server using a communication method. The output is the user's attribute information sent to the server.

[0672] Step 2:

[0673] The server stores the attribute information it receives in its memory. Its operation involves receiving attribute information sent from a terminal as input and saving it to a database as preparation for analysis. The output is the data saved for analysis.

[0674] Step 3:

[0675] The server uses analytical means to analyze the user's characteristics using a generative AI model and generates a feature vector for the user. The input is attribute information stored in a memory device, and the operation involves vectorizing the data using the generative model and extracting features. The output is the feature-vectorized user information.

[0676] Step 4:

[0677] The server uses estimation methods to calculate compatibility scores between users based on feature vectors and selects the most suitable interaction partners. The input is the user's feature vector, and the operation involves applying a compatibility calculation algorithm to select the optimal partner. The output is the interaction partners determined to be compatible.

[0678] Step 5:

[0679] The server notifies the terminal of the selected communication target via an information notification mechanism. The input is data of the optimal communication target, which is sent to the terminal using the communication mechanism to inform the user. The output is the notification information sent to the user.

[0680] Step 6:

[0681] When a user begins interacting, the terminal's emotion recognition system uses a camera and microphone to detect the user's emotional state in real time. The input consists of camera video and microphone audio data, and the system uses analysis software to analyze the emotional state. The output is information about the detected emotions.

[0682] Step 7:

[0683] The server, through an emotion recognition suggestion mechanism, utilizes a generative AI model to generate topics corresponding to the user's emotions and displays them on the terminal. The input is detected emotion information, and the generative AI model generates prompt sentences based on this data. The output is the suggested topic that is displayed.

[0684] Step 8:

[0685] The server combines the user's emotional state with local event information using a local activity suggestion system, and suggests events as needed. The input consists of emotional state information and local information, and the system's operation involves selecting and presenting appropriate events using an algorithm. The output is the event information suggested to the user.

[0686] Step 9:

[0687] The robot uses automated interaction support mechanisms to provide real-time communication tailored to the user's emotional state within the store. The input is the user's real-time emotional information, and the robot's operation involves adaptive interaction and support. The output is real-time interaction support.

[0688] Step 10:

[0689] The server uses health analysis tools to generate personalized health advice based on the user's emotional data and sends it to the terminal. The input is emotional data, and the system operates by generating health advice using a health management algorithm. The output is health advice information for the user.

[0690] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0691] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0692] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0693] [Fourth Embodiment]

[0694] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0695] As shown in Figure 7, the 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.

[0696] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0697] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0698] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0699] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0700] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0701] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0702] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0703] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0704] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0705] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0706] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0707] This invention is an innovative system designed to prevent social isolation among the elderly and foster new relationships. The system provides technology for selecting optimal interaction partners based on user attribute information. Specifically, it accumulates data from users and analyzes it using a generative model to match compatible users.

[0708] First, the terminal provides the user with an input interface, allowing them to enter attribute information such as name, age, hobbies, and lifestyle. Once the information is entered, the terminal sends it to the server.

[0709] The server stores the received attribute information in a database using a data storage mechanism. Subsequently, a generative model analyzes the patterns of each user's hobbies and interests. The generative model extracts features from the data and generates an index to estimate the compatibility between users with similar characteristics.

[0710] For matched users, the server uses a notification system to send the result to the device, preparing to notify the user. This allows the user to connect online with compatible partners. The device provides communication methods such as messaging and video calls to facilitate online interaction.

[0711] Furthermore, the generative model automatically suggests useful topics during conversations, supporting the development of mutual interest. This facilitates smooth communication between users.

[0712] Furthermore, the server selects and suggests appropriate events based on local information, increasing opportunities for users to interact offline. This feature makes it easier for seniors to participate in community activities.

[0713] Health-related functions are also incorporated into this system. The terminal provides an interface for users to input their health status, and the server collects and analyzes this information. Based on the analysis results, it generates and presents personalized health advice to the user.

[0714] This system is expected to enable elderly people to build new relationships, avoid isolation, and lead fulfilling lives.

[0715] The following describes the processing flow.

[0716] Step 1:

[0717] The terminal displays an information input interface to the user. The user enters attribute information such as name, age, hobbies, past occupations, and lifestyle. Once the user has finished entering the information, the terminal sends the entered information to the server.

[0718] Step 2:

[0719] The server stores the received attribute information in a database. Using the stored data, it activates a generative model to analyze the user's hobbies and interests. This generates a feature vector for each user.

[0720] Step 3:

[0721] Based on the feature vectors calculated by the generative model, the server calculates a compatibility score between users. It selects the most compatible user pairs and generates this information as a matching result.

[0722] Step 4:

[0723] The server uses a notification mechanism to send information about the selected pair to the terminal in order to notify the user of the matching results. The receiving terminal displays this information to the user, allowing them to confirm the matching results.

[0724] Step 5:

[0725] Users can review the matching results and, if they wish to begin interacting, initiate video calls or messaging through their device. The device establishes the means of communication and supports interaction between users.

[0726] Step 6:

[0727] During interaction, the server uses a generative model to suggest topics based on shared hobbies and interests. This information is displayed to the user via their device and used to facilitate conversation.

[0728] Step 7:

[0729] The server verifies the user's location and collects information on events happening in the area. It analyzes the collected event information and generates data to select and suggest events that are suitable for the user to attend.

[0730] Step 8:

[0731] Regarding the health management function, the terminal provides a health information input screen, and the user enters their own health information. The server analyzes the collected health data and generates and provides personalized health advice to the user.

[0732] (Example 1)

[0733] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0734] In modern society, the problem of social isolation and difficulty in building new relationships exists among the elderly. These social problems increase the risk of negative mental and physical effects on the elderly. Traditional methods are ineffective in solving these problems, and a more efficient and individualized system for promoting social interaction is needed.

[0735] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0736] In this invention, the server includes an information recording means for storing attribute information collected from the user, a feature analysis means for analyzing the user's characteristics using a generative model based on the attribute information, and a compatibility evaluation means for predicting compatibility between users and selecting the optimal interaction partner. This enables the efficient search for appropriate interaction partners based on the user's attributes, making it possible for elderly people to build new relationships.

[0737] "Information recording means" refers to means for securely and efficiently storing attribute information collected from users.

[0738] A "feature analysis method" is a means of analyzing the characteristics of a user in detail using a generative model based on the user's attribute information that has been collected.

[0739] A "compatibility evaluation method" is a means of predicting compatibility between users and selecting the most suitable interaction partners.

[0740] A "notification function" is a means of quickly and accurately notifying the user of the matching results.

[0741] "Communication support means" refers to means that provide communication functions to enable users to interact smoothly with other users.

[0742] A "topic suggestion tool" is a method that uses generative models to suggest useful topics in order to facilitate interaction among users.

[0743] An "event recommendation method" is a means of suggesting activities or events suitable for users based on local information.

[0744] A "health promotion tool" is a means of analyzing a user's health status information and generating personalized health advice.

[0745] This invention is a system designed to prevent social isolation among the elderly and to help them build new relationships. This system provides technology for selecting the most suitable partners for interaction based on the user's attribute information.

[0746] The terminal provides the user with an input interface, allowing them to enter attribute information such as name, age, hobbies, and lifestyle. This interface is designed to allow for accurate information entry using a touchscreen or keyboard. The entered information is transmitted to the server via protocols such as SSL over the internet.

[0747] The server stores the received attribute information in a database system (e.g., MySQL, PostgreSQL). This information is securely managed to protect user privacy and maintain data consistency. Subsequently, a generative AI model is used to analyze each user's hobbies and interests. The machine learning algorithms used (e.g., clustering, classification) are designed to efficiently process large amounts of data and perform feature extraction.

[0748] Users can receive matching results sent from their devices and interact online. Chat apps and video call tools are provided as means of interaction, enabling communication that transcends physical distance.

[0749] This system also features a generative AI model that automatically suggests topics to support the conversation as needed. A possible example of a prompt would be: "A 75-year-old man, whose hobbies are gardening and local history. Please recommend someone suitable to interact with." Upon entering this prompt, the AI ​​begins processing to recommend a suitable partner.

[0750] Furthermore, the system has a function that suggests events suitable for the user based on local information, thereby increasing opportunities for offline interaction. This event suggestion function uses a map service API to provide appropriate event information based on the user's location.

[0751] Finally, the terminal provides an interface for users to input information about their health status, and the server analyzes this information to generate personalized health advice. Through these processes, users can implement health management tailored to their individual needs.

[0752] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0753] Step 1:

[0754] The terminal provides the user with an input interface, allowing them to enter attribute information such as name, age, hobbies, and lifestyle. Input is performed by typing or selecting information into a form on the screen. The data is confirmed when the user presses the submit button. The entered information is then sent to the next processing step with the user's consent.

[0755] Step 2:

[0756] The terminal sends the entered attribute information to the server using the SSL protocol. The transmitted data is encrypted and securely transferred over the network. Specifically, after pressing the send button, the data packet arrives on the server via the internet.

[0757] Step 3:

[0758] The server verifies the received attribute information, confirms its security, and then stores it in the database. This process uses a database management system and performs database insertion operations to ensure the data is mapped to the correct fields. The input is user attribute information, and the output is the successfully stored information.

[0759] Step 4:

[0760] The server activates a generated AI model based on stored attribute information to analyze the user's characteristics. This analysis uses machine learning algorithms (clustering and classification) to analyze patterns and trends from the resulting dataset. The input is the user's attribute information, and the output is the analyzed characteristic data.

[0761] Step 5:

[0762] The server performs compatibility evaluations based on feature data analyzed by a generative AI model and selects the most suitable interaction partners. This evaluation includes similarity calculations, quantifying compatibility with other users who have similar characteristics. The input is feature data, and the output is a compatibility evaluation value and a list of optimal partners.

[0763] Step 6:

[0764] The server sends the compatibility evaluation results to the terminal and notifies the user of the results. Real-time push notifications and email notifications are used as notification methods, allowing the user to check the results immediately. The input is the compatibility evaluation result, and the output is the notification message.

[0765] Step 7:

[0766] The device provides users with online communication tools through messaging and video call functions. This allows them to communicate directly with selected individuals. Specific actions include launching related applications and starting sessions.

[0767] Step 8:

[0768] The generative AI model suggests useful topics during conversations as needed. The suggested topics are tailored to the user's interests based on pre-set prompt sentences. The input is a prompt sentence, and the output is a list of recommended topics.

[0769] Step 9:

[0770] The server suggests events based on local information, recommending activities that match the user's geographical location. This function accesses a map service API and filters and provides events based on the user's location. The input is the user's location information, and the output is a list of suggested events.

[0771] (Application Example 1)

[0772] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0773] To help older adults overcome social isolation and build new relationships, it is crucial to find appropriate partners and engage in meaningful conversations and activities. However, finding suitable partners and providing opportunities for interaction in the real world is difficult. Furthermore, opportunities for natural conversations with people who share similar hobbies and interests are also challenging. Therefore, there is a need for systems that support such interactions.

[0774] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0775] In this invention, the server includes data storage means for storing attribute information collected from users, analysis means for analyzing the characteristics of users using a generative model based on the attribute information, and compatibility estimation means for estimating compatibility between users and selecting the most suitable interaction partners. This enables users to engage in meaningful conversations and easily build new relationships in real-world interaction environments, with support from topic suggestion means.

[0776] A "data storage means" is a function that stores attribute information collected from users and makes it available for later analysis.

[0777] "Analysis tools" refer to functions that utilize generative models based on collected attribute information to analyze user characteristics in detail.

[0778] The "compatibility estimation method" is a function that analyzes commonalities and interests between users and selects the most suitable person to interact with.

[0779] A "notification method" is a function that quickly communicates matching results to the user and prompts them to take the next action.

[0780] "Means of facilitating interaction" refers to a function that provides the necessary communication means to enable users to interact effectively with each other.

[0781] A "topic suggestion tool" is a function that uses a generative model to automatically suggest topics useful for interaction, thereby facilitating smooth conversation.

[0782] A "display means" is a function that visually presents appropriate interaction targets or events to the user in a real-world interaction environment.

[0783] "Communication support means" refers to functions that support real-time interaction with other users and facilitate smooth communication.

[0784] To implement this invention, the system includes a program that collects and analyzes attribute information and performs appropriate matching between users. The server stores user attribute information obtained from devices such as smartphones and tablets in a data storage means. This information includes name, age, interests, lifestyle, and health status. This information is managed by a database management system (e.g., PostgreSQL). Furthermore, a wide-area network (e.g., the Internet) is used as a means of communication to enable bidirectional transmission and reception of information.

[0785] The server utilizes generative AI models based on TensorFlow and PyTorch to analyze the received attribute information and understand the user's characteristics, such as interests and hobbies. Based on this analysis, it estimates compatibility between users with shared interests and uses AI to select appropriate interaction partners. Users are notified in real time of matching results and interaction events using notification methods such as Firebase Cloud Messaging.

[0786] To facilitate interaction, the display system visualizes relevant interaction targets and related event information on the terminal's screen in a real-world interaction environment, making them suitable for the user. Furthermore, to facilitate conversation, a topic suggestion system is used, where a generative model automatically suggests topics that are likely to pique the user's interest. For example, a prompt might look like this:

[0787] Example of a prompt:

[0788] User A's information: Age = 70, Hobbies = Gardening, Health status = Good

[0789] Candidate information list: [User B: Age=72, Hobby=Gardening, Health=Good, User C: Age=65, Hobby=Reading, Health=Good]

[0790] Please use an AI model to suggest the most compatible match for user A.

[0791] Furthermore, communication support means allow users to interact with each other through real-time chat and video calls. This function is implemented using technologies such as WebRTC. For example, in a cafe space, if another user who enjoys gardening is approached by the AI, the AI ​​might suggest a topic like, "What kind of techniques do you use when growing this flower?", facilitating a conversation based on shared interests. Through these processes, users can build new relationships and deepen their social connections.

[0792] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0793] Step 1:

[0794] The device receives attribute information from the user, such as name, age, hobbies, lifestyle, and health status, through an input interface. This information becomes input data sent to the server and is formatted as a user profile.

[0795] Step 2:

[0796] The server registers the received user attribute information in the database using a data storage mechanism. The input here is raw data sent from the terminal, which is then stored as structured data by the database management system.

[0797] Step 3:

[0798] The server processes user information retrieved from the database using analytical tools and performs user characteristic analysis using a generative AI model (using TensorFlow or PyTorch). The input is attribute information, and the output is a user characteristic vector. This process extracts commonalities and interest trends.

[0799] Step 4:

[0800] The server uses a compatibility estimation method based on the analyzed feature vectors to estimate the compatibility between users. The input is a list of feature vectors, and the output is a list including matching scores. The generative AI model identifies users with high similarity and selects matching candidates.

[0801] Step 5:

[0802] The server sends the matching results to the terminal via a notification system, informing the user of information about potential matches. The input is the matching score and a list of candidates, and the output is a notification signal to the user. Because notifications are sent in real time, Firebase Cloud Messaging is used.

[0803] Step 6:

[0804] On the device, interaction facilitators are activated based on the matching information received by the user, providing communication functions such as video calls and chat. Input consists of notified interaction candidates and topic suggestions, while output is the actual communication log. WebRTC is used to enable real-time conversations.

[0805] Step 7:

[0806] The server then uses a generative AI model to execute a topic suggestion mechanism, proposing conversation topics based on shared hobbies and interests between users. The input is the profiles of the matching users, and the output is a list of suggested topics. This facilitates smooth interaction between users.

[0807] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0808] This invention is a system for promoting social interaction among the elderly while taking into account the user's emotional state. Based on the user's attribute information and emotional state, this system selects the most suitable person to interact with and supports smooth interaction.

[0809] First, the terminal provides an interface for the user to input their personal information. The user enters information about their name, age, hobbies, and lifestyle, and the terminal sends that information to the server.

[0810] Next, the server stores the transmitted attribute information in a database. It also activates an emotion engine to recognize the user's emotional state in real time from the video and audio captured during video calls and messaging. The acquired emotion data, combined with a generative model, constitutes the user's feature vector.

[0811] The server uses feature vectors to calculate the user's compatibility score and selects the most suitable interaction partners. During this process, consideration is also given to the user's emotional state, prioritizing matches where positive compatibility is expected. Information about the selected interaction partners is sent to the user's device via a notification system.

[0812] Upon receiving the notification, the user can begin interacting with the person presented via their device. The device provides the means for the user to make video calls and send messages.

[0813] During the interaction, the server suggests the most appropriate topics based on the user's emotions, as recognized by the emotion engine. These suggestions are displayed on the terminal and play a role in stimulating the interaction.

[0814] In addition, the server collects information on local events based on the user's location. If the emotional state recognized by the emotion engine is deemed suitable for going out or participating in social activities, the server suggests that the user participate in the event.

[0815] Regarding health management, the emotional engine considers the user's emotional state and generates specific health advice tailored to stress levels and mood swings. This allows users to benefit from more personalized health management.

[0816] Thus, by utilizing an emotion engine, the present invention can provide appropriate support tailored to the user's state, enabling more fulfilling social interaction and health management.

[0817] The following describes the processing flow.

[0818] Step 1:

[0819] The terminal displays a screen for the user to input attribute information. The user enters information such as name, age, hobbies, and lifestyle into the terminal. After input, the terminal sends the data to the server.

[0820] Step 2:

[0821] The server stores the received attribute information in a database. Based on the stored information, a generative model is used to generate a feature vector for the user. This feature vector indicates the user's preferences and interests.

[0822] Step 3:

[0823] When a user starts a conversation, the device monitors the video or voice call and passes the acquired audio and video data to the emotion engine. The emotion engine analyzes the user's tone of voice and facial expressions to generate emotion data.

[0824] Step 4:

[0825] The server combines the generated feature vectors with sentiment data to calculate a compatibility score between users. Based on the compatibility score, the matching system selects the most suitable interaction partners for each user.

[0826] Step 5:

[0827] The server sends the matching results to the device using a notification system. The device displays the notification to the user, encouraging interaction with the matched person. The notification also includes hints on the appropriate timing for interaction based on emotions.

[0828] Step 6:

[0829] During interaction, the server monitors the latest emotional data from the emotion engine. Based on this data, the server selects the most appropriate topics and sends suggestions to the terminal to enhance the interaction.

[0830] Step 7:

[0831] The server obtains the user's current location information and collects local event information. Considering the user's emotional state, it selects events appropriate to that situation and suggests participation.

[0832] Step 8:

[0833] The device collects health-related information entered by the user and sends it to a server. The server generates health advice, taking into account the user's emotional state, and provides it to the user. The tailored advice includes suggestions for stress management and activity levels.

[0834] (Example 2)

[0835] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0836] Social isolation and health management challenges among the elderly are becoming increasingly important. There is a need for support that allows seniors to connect with appropriate people and live healthy lives based on their emotional state, without feeling isolated. However, current systems do not adequately address the emotional states and individual health needs of users. Against this backdrop, there is a demand for a comprehensive and flexible system that enables seniors to lead richer social lives.

[0837] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0838] In this invention, the server includes data storage means for storing demographic data collected from users, analysis means for analyzing the individual characteristics of users using a generative model based on the demographic data and the users' emotional data, and compatibility selection means for estimating compatibility considering the emotional states between users and selecting the most suitable interaction partners. This enables users to prevent isolation and lead healthy and vibrant lives through appropriate interactions based on their emotional states.

[0839] A "data storage method" is a function that can stably store demographic data and sentiment data collected from users and retrieve them quickly as needed.

[0840] "Analysis tools" refer to functions that utilize collected data and generative models to comprehensively analyze the individual characteristics of users.

[0841] The "compatibility selection method" is a function that evaluates the user's emotional state, estimates their compatibility with other users based on that evaluation, and selects the most suitable person to interact with.

[0842] "Information provision means" refers to a function for transmitting information about selected interaction targets to users in an appropriate format.

[0843] A "communication support system" is a system that provides functions to enable users to communicate smoothly over long distances.

[0844] The "agenda proposal tool" is a function that uses a generative model to present agenda items suitable for the user, with the aim of stimulating interaction.

[0845] A "health guidance tool" is a function that develops and guides individual health plans based on the user's emotional state and health-related data.

[0846] The "activity suggestion tool" is a function that suggests social activities and events suitable for the user based on local information.

[0847] A "health management tool" is a function that evaluates the user's psychological state and generates and provides an individualized health strategy based on that evaluation.

[0848] This invention is a social interaction promotion system specifically designed for the elderly. This system utilizes user demographic and emotional data to select the most suitable interaction partners and support a healthy lifestyle.

[0849] First, the device provides an interface for users to input their demographic data, such as age, hobbies, and lifestyle. This typically involves a touchscreen or keyboard. It also includes a camera and microphone to collect emotional data.

[0850] The input data is transmitted to the server in real time. The server uses a high-performance database system to manage the data and general emotion engine software to analyze emotional data. A specific example of such software would be emotion recognition software. The server analyzes this data using a generative AI model (for example, a large-scale language model) to understand the user's individual characteristics.

[0851] Based on this analysis, the server selects the most suitable contact and notifies the user of that information. The notification is sent to the device via email or app push notification. The user then decides whether to interact based on the information presented.

[0852] Furthermore, the server collects information on local social activities and events based on the user's location and makes suggestions tailored to the user. Location-based services are used for this purpose. It can suggest events that will help the user refresh themselves, such as local concerts or craft classes.

[0853] In health management, the server uses collected information to suggest healthy lifestyle habits tailored to each individual user. For example, when a specific emotional state is detected, it can provide guidance on appropriate relaxation methods.

[0854] As a concrete example, the system operates based on the following prompt:

[0855] "Please suggest how to address the emotional state of users in order to promote social interaction among the elderly."

[0856] This system aims to support users in leading fulfilling lives while maintaining their health and avoiding social isolation.

[0857] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0858] Step 1:

[0859] The device collects demographic data from users. Specifically, users input information such as age, hobbies, and lifestyle through a touch panel or keyboard interface. This information is output as structured data, such as in JSON format, and sent to the server.

[0860] Step 2:

[0861] The server stores demographic data received from the terminal in a database. The received JSON data is stored as a database record, allowing for fast retrieval when needed. This is the data storage method, and the output is the data stored in the database.

[0862] Step 3:

[0863] The device collects user emotional data in real time. Specifically, it uses a camera to capture facial expressions and a microphone to record voice. This raw data is immediately transmitted to the server.

[0864] Step 4:

[0865] The server uses an emotion engine to analyze the received emotion data. It analyzes emotional states from video footage using facial recognition technology and measures tone from audio using speech analysis technology. This process outputs numerical data representing the emotional state.

[0866] Step 5:

[0867] The server uses demographic and sentiment data to analyze individual user characteristics using a generative AI model. Specifically, it uses a sentiment engine and machine learning libraries to represent user characteristics as feature vectors. These feature vectors are the output of the analysis.

[0868] Step 6:

[0869] The server uses a machine learning algorithm to calculate compatibility scores and select the most suitable interaction partners. Here, it analyzes the user's feature vectors and compares their compatibility with other users to select the most appropriate interaction partners. The selected candidates are then generated as output.

[0870] Step 7:

[0871] The server sends a notification to the user's device based on the information of the selected interaction partners. Using email or push notifications, it presents the user with the profiles and contact information of the selected partners. This is the output of the information provision.

[0872] Step 8:

[0873] The user initiates interaction via their device based on a notification from the server. Specifically, they use a video call application as a means of remote communication to communicate with the selected interaction partner. In this step, the output is successful communication.

[0874] (Application Example 2)

[0875] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0876] There is a need to promote social interaction among the elderly and provide appropriate communication tailored to their emotional state. However, existing systems have had problems in promoting interaction while adequately considering the user's feelings. Furthermore, the provision of information to support individual interactions and participation in social activities has been limited, and there has been a lack of mechanisms that allow the elderly to actively participate in particular.

[0877] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0878] In this invention, the server includes a storage means for storing attribute information collected from the user, an analysis means for analyzing the user's characteristics, and an emotion recognition suggestion means for analyzing the user's emotional state and suggesting appropriate topics. This makes it possible to select the optimal interaction partners, suggest topics for interaction, and provide information on local activities while taking the user's emotional state into consideration.

[0879] A "memory device" is a device that has the function of storing the user's attribute information.

[0880] An "analysis tool" is a device that has the function of analyzing attribute information and emotional states obtained from the user and extracting characteristics.

[0881] A "prediction means" is a device that has the function of predicting compatibility between users and selecting the optimal interaction partner.

[0882] An "information notification device" is a device that has the function of informing the user of the results obtained from analysis or estimation.

[0883] A "communication support device" is a device that provides the infrastructure for users to make calls and communicate, and has functions to promote communication.

[0884] A "content suggestion device" is a device that has the function of providing users with topics and information for interaction using a generative model.

[0885] An "emotion recognition suggestion device" is a device that has the function of detecting the user's emotional state and suggesting an appropriate topic according to that state.

[0886] A "community activity suggestion device" is a device that has the function of suggesting events and activities within a community based on the user's emotional state and local information.

[0887] An "automated interaction support device" is a device that uses robots or other means to provide real-time interaction support tailored to the user's emotional state.

[0888] A "health analysis device" is a device that analyzes the user's emotional state and generates personalized health management advice.

[0889] To implement this invention, first, the terminal receives attribute information from the user and transmits it to the server. The server stores this attribute information in a storage means and extracts the user's characteristics using an analysis means. Next, an estimation means calculates the compatibility between users based on these characteristics and selects the optimal interaction partner. This result is communicated to the user via an information notification means.

[0890] When a user begins interacting, the emotion recognition suggestion system uses hardware such as cameras and microphones to recognize the user's emotional state in real time and provides appropriate topics based on that situation using a generative AI model. For example, if the generative AI model detects that the user is excited, it will generate a prompt such as, "How about talking about the recent weather or seasons?"

[0891] Furthermore, the server uses a local activity suggestion system to combine the user's emotional state with local event information and suggests participation in events if it determines that going out is appropriate. In addition, robots equipped with automated interaction support systems provide real-time support for interactions with the user in stores and other locations. This allows users to maintain social connections with peace of mind.

[0892] Simultaneously, the health analysis system generates personalized health advice based on the user's emotional data. This allows users to receive specific advice that helps maintain their health. Thus, the present invention is a system that provides comprehensive support for the social interaction and health management of the elderly.

[0893] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0894] Step 1:

[0895] The terminal receives attribute information (name, age, hobbies, lifestyle, etc.) from the user and sends that data to the server. Its operation involves acquiring the user's attribute information as input and sending it to the server using a communication method. The output is the user's attribute information sent to the server.

[0896] Step 2:

[0897] The server stores the attribute information it receives in its memory. Its operation involves receiving attribute information sent from a terminal as input and saving it to a database as preparation for analysis. The output is the data saved for analysis.

[0898] Step 3:

[0899] The server uses analytical means to analyze the user's characteristics using a generative AI model and generates a feature vector for the user. The input is attribute information stored in a memory device, and the operation involves vectorizing the data using the generative model and extracting features. The output is the feature-vectorized user information.

[0900] Step 4:

[0901] The server uses estimation methods to calculate compatibility scores between users based on feature vectors and selects the most suitable interaction partners. The input is the user's feature vector, and the operation involves applying a compatibility calculation algorithm to select the optimal partner. The output is the interaction partners determined to be compatible.

[0902] Step 5:

[0903] The server notifies the terminal of the selected communication target via an information notification mechanism. The input is data of the optimal communication target, which is sent to the terminal using the communication mechanism to inform the user. The output is the notification information sent to the user.

[0904] Step 6:

[0905] When a user begins interacting, the terminal's emotion recognition system uses a camera and microphone to detect the user's emotional state in real time. The input consists of camera video and microphone audio data, and the system uses analysis software to analyze the emotional state. The output is information about the detected emotions.

[0906] Step 7:

[0907] The server, through an emotion recognition suggestion mechanism, utilizes a generative AI model to generate topics corresponding to the user's emotions and displays them on the terminal. The input is detected emotion information, and the generative AI model generates prompt sentences based on this data. The output is the suggested topic that is displayed.

[0908] Step 8:

[0909] The server combines the user's emotional state with local event information using a local activity suggestion system, and suggests events as needed. The input consists of emotional state information and local information, and the system's operation involves selecting and presenting appropriate events using an algorithm. The output is the event information suggested to the user.

[0910] Step 9:

[0911] The robot uses automated interaction support mechanisms to provide real-time communication tailored to the user's emotional state within the store. The input is the user's real-time emotional information, and the robot's operation involves adaptive interaction and support. The output is real-time interaction support.

[0912] Step 10:

[0913] The server uses health analysis tools to generate personalized health advice based on the user's emotional data and sends it to the terminal. The input is emotional data, and the system operates by generating health advice using a health management algorithm. The output is health advice information for the user.

[0914] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0915] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0916] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0917] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0918] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0919] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0920] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0921] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0922] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0923] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0924] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0925] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0926] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0927] 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.

[0928] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0929] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0930] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0931] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0932] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0933] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0934] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0935] The following is further disclosed regarding the embodiments described above.

[0936] (Claim 1)

[0937] A data storage means for storing attribute information collected from users,

[0938] An analysis means for analyzing the user's characteristics using a generative model based on the attribute information,

[0939] A compatibility estimation method that estimates compatibility between users and selects the most suitable interaction partner,

[0940] A notification method for informing the user of the matching results,

[0941] A means of facilitating communication that provides a means of communication for users to interact with each other,

[0942] A topic suggestion method that proposes topics for interaction using a generative model,

[0943] A system that includes this.

[0944] (Claim 2)

[0945] The system according to claim 1, further comprising an event suggestion means that suggests activities or events suitable for the user based on local information.

[0946] (Claim 3)

[0947] The system according to claim 1, further comprising a health management means for analyzing the user's health-related information and generating personalized health advice.

[0948] "Example 1"

[0949] (Claim 1)

[0950] Information recording means for storing attribute information collected from users,

[0951] A feature analysis means that analyzes the user's characteristics using a generative model based on the attribute information,

[0952] A compatibility evaluation method that predicts compatibility between users and selects the optimal interaction partner,

[0953] A notification function means for notifying the user of the matching results,

[0954] A communication support means that provides communication functions for users to interact with each other,

[0955] A topic suggestion method that provides topics for interaction using a generative model,

[0956] A system that includes this.

[0957] (Claim 2)

[0958] The system according to claim 1, further comprising an event recommendation means that suggests activities or events suitable for the user based on local information.

[0959] (Claim 3)

[0960] The system according to claim 1, further comprising a health promotion means for analyzing the user's health status information and generating personalized health advice.

[0961] "Application Example 1"

[0962] (Claim 1)

[0963] A data storage means for storing attribute information collected from users,

[0964] An analysis means for analyzing the user's characteristics using a generative model based on the attribute information,

[0965] A compatibility estimation method that estimates compatibility between users and selects the most suitable interaction partner,

[0966] A notification method for informing the user of the matching results,

[0967] A means of facilitating communication that provides a means of communication for users to interact with each other,

[0968] A topic suggestion method that proposes topics for interaction using a generative model,

[0969] A display means that visualizes and provides information to users regarding appropriate interaction targets and events in real-world interaction environments,

[0970] A communication support means that assists in real-time interaction with other users,

[0971] A system that includes this.

[0972] (Claim 2)

[0973] The system according to claim 1, further comprising an event suggestion means that suggests activities or events suitable for the user based on local information.

[0974] (Claim 3)

[0975] The system according to claim 1, further comprising a health management means for analyzing the user's health-related information and generating personalized health advice.

[0976] "Example 2 of combining an emotion engine"

[0977] (Claim 1)

[0978] A data storage means for storing demographic data collected from users,

[0979] An analytical means for analyzing the individual characteristics of users using a generative model based on the aforementioned demographic data and user sentiment data,

[0980] A compatibility selection method that estimates compatibility by considering the emotional states of the users and selects the most suitable interaction partner,

[0981] Information provision means that provide users with information about selected interaction targets,

[0982] A means of communication that provides communication functions for users to communicate using remote communication,

[0983] A means of proposing topics for exchange using a generative model,

[0984] A health guidance tool that provides individualized health plans tailored to the user's emotional state,

[0985] A system that includes this.

[0986] (Claim 2)

[0987] The system according to claim 1, comprising an activity suggestion means that suggests social activities or gatherings suitable for the user based on local information.

[0988] (Claim 3)

[0989] The system according to claim 1, comprising a health management means for analyzing the user's psychological state and generating an individualized health strategy.

[0990] "Application example 2 when combining with an emotional engine"

[0991] (Claim 1)

[0992] A storage means for storing attribute information collected from the user,

[0993] An analysis means for analyzing the user's characteristics using a generative model based on the attribute information,

[0994] An estimation method for estimating compatibility between users and selecting the most suitable interaction partner,

[0995] A means of notifying the user of the matching results,

[0996] Communication support means that provides communication means for users to make calls and communicate,

[0997] A content suggestion method that proposes topics for interaction using a generative model,

[0998] An emotion recognition suggestion tool that analyzes emotional states and proposes appropriate topics to the user during interactions,

[0999] A means of proposing community activities that collects event information within the region and makes suggestions based on emotional states,

[1000] A system that includes this.

[1001] (Claim 2)

[1002] The system according to claim 1, further comprising an automated interaction support means that uses a robot to provide real-time interaction support in response to the user's emotions.

[1003] (Claim 3)

[1004] The system according to claim 1, further comprising a health analysis means for analyzing the emotional state of the user and generating personalized health advice. [Explanation of Symbols]

[1005] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A data storage means for storing attribute information collected from users, An analysis means for analyzing the user's characteristics using a generative model based on the attribute information, A compatibility estimation method that estimates compatibility between users and selects the most suitable interaction partner, A notification method for informing the user of the matching results, A means of facilitating communication that provides a means of communication for users to interact with each other, A topic suggestion method that proposes topics for interaction using a generative model, A system that includes this.

2. The system according to claim 1, further comprising an event suggestion means that suggests activities or events suitable for the user based on local information.

3. The system according to claim 1, further comprising a health management means for analyzing the user's health-related information and generating personalized health advice.

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