System

Abstract

A system is provided.SOLUTION: A system in a social networking platform for senior citizens, comprising: means for collecting and storing user information; means for analyzing the collected user information by applying a AI model; and means for recommending content, a friend candidate, or an event based on a result of the analysis.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Social isolation and lack of engagement are serious problems for the elderly. These have a negative impact on mental and physical health and significantly reduce quality of life. Traditional social networking platforms lack features and services specifically designed for seniors, making them difficult for seniors to use and unable to adequately meet their needs. As a result, community participation and health management become difficult. [Means for solving the problem]

[0005] The present invention provides a system for providing a social networking platform for seniors, including a means for collecting and storing user data, a means for applying an AI model to the collected user data and analyzing it, and a means for recommending content, friend candidates, and events based on the analysis results. The system also includes a means for acquiring and storing local event information and community information from external data sources, and a means for recommending relevant local events based on the user's location information. The system further includes a means for providing an intuitive user interface that is easy for users to operate, a means for accepting user input and sending requests to a server, and a means for displaying responses from the server to the user, thereby effectively promoting social interactions, health management, and community participation among seniors. This solves the problems of conventional social networking platforms and improves the quality of life for seniors.

[0006] A "social networking platform for seniors" is an online platform that provides social interaction, community participation, and access to essential services primarily targeted at seniors.

[0007] "User Data" refers to any personal information or usage data relating to users of the Platform, including profile information, behavioral data, and health information.

[0008] "Collection means" refers to the technical features and processes by which User Data is entered into the Platform and stored in a database.

[0009] "Storage means" refers to a storage device or database system for safely storing collected user data.

[0010] "Means of applying and analyzing AI models" refers to the process of applying artificial intelligence algorithms to collected data to analyze the data and derive meaningful results.

[0011] "Means of recommending content, potential friends, and events" refers to a system that presents highly relevant information, people, and activities to users based on the results of analysis.

[0012] "Local event information and community information" refers to information about various events and activities held in the area related to the user's location and interests.

[0013] "Means of obtaining and storing data from external data sources" refers to the process of collecting necessary information using databases or APIs provided by third parties and storing it within the platform.

[0014] "User location information" refers to data about the current location of platform users, and is primarily obtained from GPS and IP addresses.

[0015] "User interface" refers to the screens and operating elements that users can directly operate and use, with emphasis placed on ease of use and intuitive operability.

[0016] "Means for sending a request" refers to the process of sending information or processing requests to a server in response to operations or inputs from a user.

[0017] "Response from a server to a request" refers to information or processing results returned by a server in response to a request from a user.

[0018] "Means for displaying a response to a user" refers to the process of displaying information from the server on a screen in a format that can be understood by the user. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] The present invention relates to a social networking platform for seniors, and provides a means for collecting and storing user data, a means for analyzing the data by applying an AI model, a means for recommending content, friend candidates, and events based on the analysis results, and a means for acquiring and storing local event information and community information. A specific embodiment of this system is described below.

[0041] Server-side implementation

[0042] 1. User Data Collection and Storage:

[0043] Overview: The server collects profile information, behavioral data, and health information of elderly users and stores it in a database.

[0044] Example: When user A enters his / her hobbies and location on the profile page, this information is sent from the device to the server and stored in the server's database.

[0045] 2. Data analysis and recommendations:

[0046] Overview: The server applies an AI model to the collected data to analyze it, and based on the results, recommends the most suitable content, friend candidates, and events to the user.

[0047] Example: If User B has frequently viewed health-related content in the past, the server can analyze their behavioral patterns and recommend new health articles or online fitness classes.

[0048] 3. Acquisition and provision of local event information:

[0049] Overview: The server obtains local event and community information from external data sources, stores it in a database, and recommends related events based on the user's location information.

[0050] Example: If user C lives in a particular area, information about craft workshops for seniors held in that area is retrieved from an external data source and recommended to user C.

[0051] Terminal side embodiment

[0052] 1. User Interface (UI):

[0053] Overview: The device provides an intuitive UI that is easy for seniors to operate, and includes features such as voice control and uppercase fonts.

[0054] Example: If user D uses a voice command to say "Find friends," the device will recognize the voice command, launch the friend search function, and display the search results in capital letters.

[0055] User-Side Embodiment

[0056] 1. Update your profile:

[0057] Overview: Users update their profile information and send that data to a server via their device.

[0058] Example: User E adds "gardening" as a new hobby. This information is immediately sent to the server and saved.

[0059] 2. Participate in community events:

[0060] Overview: Users can easily access and register for local events through their devices.

[0061] Example: User F selects an event he or she is interested in from a list of local events displayed within the platform and presses the "Participate" button. The request to participate is sent to the server, and the event participation is completed.

[0062] In this way, the present invention effectively promotes social interaction, health management, and community participation for the elderly through collaboration between servers, terminals, and users, thereby resolving the problems of traditional social networking platforms and improving the quality of life for the elderly.

[0063] The processing flow will be explained below.

[0064] User Data Collection and Storage Process Steps

[0065] Step 1:

[0066] The user enters profile information.

[0067] User: Enters their hobbies, location, health information, etc. on their profile page.

[0068] Example: User A enters "gardening" as a hobby.

[0069] Step 2:

[0070] The entered data is sent to the server.

[0071] Terminal: Sends input information to the server in real time.

[0072] Example: The terminal sends user A's hobby information to the server as a data packet.

[0073] Step 3:

[0074] Save the data to a database.

[0075] Server: Validates the received data and stores it in the database.

[0076] Example: The server adds the hobby "gardening" to User A's profile.

[0077] Data analysis and recommendation processing steps

[0078] Step 1:

[0079] Periodically read the stored data.

[0080] Server: Periodically reads user data from the database.

[0081] Example: The server reads user A's behavior data once a day.

[0082] Step 2:

[0083] Apply AI models to analyze the data.

[0084] Server: Analyzes the stored data using AI models to analyze user trends.

[0085] Example: The server analyzes which genre of content User A has frequently viewed in the past month.

[0086] Step 3:

[0087] Generate recommendations based on the analysis results.

[0088] Server: Based on the analysis results, it generates the most suitable content, friend suggestions, and events for the user.

[0089] Example: The server recommends to user A new articles about "gardening" and other users with the same hobby.

[0090] Step 4:

[0091] Prepare the recommendations in the form of a notice.

[0092] Server: Formats the recommendation information and prepares it to be sent to the device as a notification message.

[0093] Example: A server creates a notification that says "Join an online group for gardening enthusiasts."

[0094] Processing steps for obtaining and providing local event information

[0095] Step 1:

[0096] Retrieve local event information from an external data source.

[0097] Server: Collects local event information from external APIs and databases.

[0098] Example: The server retrieves the events calendar from the API of a local cultural center.

[0099] Step 2:

[0100] Save the retrieved data in the database.

[0101] Server: Validates the acquired event information and stores it in an internal database.

[0102] Example: The server stores the obtained information about the craft workshop in a database.

[0103] Step 3:

[0104] Recommend events based on the user's location.

[0105] Server: Obtains the user's location and recommends relevant events.

[0106] Example: User B is notified of a craft workshop near where he currently lives.

[0107] User interface provision and operation processing steps

[0108] Step 1:

[0109] The user logs in and sees the main dashboard.

[0110] Terminal: Receives login information, authenticates the user, and displays the main dashboard.

[0111] Example: When User C logs in, the dashboard displays recent notifications and recommended content.

[0112] Step 2:

[0113] Accepts interaction from the user.

[0114] Device: Accepts actions such as button presses, swipes, and voice commands.

[0115] Example: User D enters the voice command "Find friends."

[0116] Step 3:

[0117] Send the request to the server.

[0118] Terminal: Sends appropriate requests to the server based on user actions.

[0119] Example: The device analyzes user D's voice command and sends a friend search request to the server.

[0120] Step 4:

[0121] Displays the response from the server.

[0122] Terminal: Receives the response from the server and displays it to the user.

[0123] Example: The device displays the search results from the server on the screen and provides new friend candidates to User D.

[0124] In this way, the platform of the present invention provides a high-level user experience through cooperation between users, terminals, and servers.

[0125] Example 1

[0126] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0127] When seniors use social networking platforms, they face challenges such as difficulty in operation, social isolation, and digital divides. Furthermore, it is difficult to efficiently recommend content, friend candidates, and local event information specifically for seniors. Therefore, there is a need to provide a platform that seniors can easily operate and that allows them to receive appropriate information and content.

[0128] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0129] In this invention, the server includes means for collecting and storing user data, means for applying a machine learning model to the collected user data and analyzing it, means for recommending content, friend candidates, and events based on the analysis results, means for acquiring and storing local event information and community information from external data sources, a terminal for providing a user interface, means for a user to update their own profile information and send the updated information to the server via the terminal, means for providing a user interface that the user can easily operate using voice commands and uppercase fonts, means for transmitting data collected by the terminal and user-input data to the server, means for displaying responses from the server to the user, means for recommending related local events based on the user's location information, and means for accepting and transmitting requests to participate in local events to the server. This allows elderly people to easily operate the device and receive information and content that meets their individual needs.

[0130] "User Data" refers to information about an individual user, such as the elderly user's profile information, behavioral data, and health information.

[0131] A "machine learning model" refers to an artificial intelligence algorithm that analyzes data and makes predictions or classifications based on the results.

[0132] "Content" refers to any information or material provided on the Platform, including articles, videos, and event information.

[0133] "Friend Suggestions" refers to other users on the social networking platform who are recommended to you based on your interests and behavioral data.

[0134] "Event" means a local or online gathering or activity that users can participate in.

[0135] "External data sources" refers to sources for obtaining data from outside the platform, such as information providers or APIs outside the platform.

[0136] "User interface" refers to the screens and operating means that allow users to interact with the system, and includes those that are particularly easy for seniors to use.

[0137] "Terminal" refers to the device through which a user accesses the platform, such as a smartphone or tablet.

[0138] "Voice command" refers to a voice input method in which a user gives instructions to a system using voice.

[0139] "Server" refers to a remote computer system that stores data, analyzes data, generates recommendations, etc.

[0140] "Location information" is information that indicates the user's geographical location and is used to recommend related local events.

[0141] "Local Events" refers to events such as workshops and gatherings that take place in a specific geographic area.

[0142] A "participation request" refers to a request by a user to indicate their intention to participate in a particular event and to convey that information to the system.

[0143] "Storage" refers to the act of keeping collected data or information in a database or storage.

[0144] The present invention relates to a social networking platform for seniors, and includes means for collecting and storing user data, means for analyzing the data by applying a machine learning model, means for recommending content, friend candidates, and events based on the analysis results, means for acquiring and storing local event information and community information from external data sources, a terminal for providing a user interface, and means for providing a user interface that can be easily operated by users using voice commands and uppercase fonts. Specific embodiments are described below.

[0145] Server-side implementation

[0146] The server performs the following process.

[0147] 1. Collection and storage of user data

[0148] Hardware: Servers, data servers (e.g. Dell PowerEdge)

[0149] Software: Database management system (e.g., MySQL), collection program (e.g., written in Python)

[0150] The server collects the user's profile information, behavioral data, and health information and stores them in a database. For example, when a user enters their hobbies and location on the profile page, this information is sent from the device to the server and stored in the server's database.

[0151] 2. Data analysis and recommendation

[0152] Hardware: Server, GPU (e.g. NVIDIA Tesla)

[0153] Software: Machine learning libraries (e.g., TensorFlow), data analysis programs (e.g., written in Python)

[0154] The server applies machine learning models to the collected data and analyzes it, and based on the results, recommends the most suitable content, friend candidates, and events to the user. For example, if a user has frequently viewed health-related content in the past, the server can analyze their behavioral patterns and recommend new health articles or online fitness classes.

[0155] 3. Acquisition and provision of local event information

[0156] Hardware: Server

[0157] Software: External API client (e.g. written in Python), database management system (e.g. MySQL)

[0158] The server obtains local event and community information from external data sources, stores it in a database, and recommends related events based on the user's location information. For example, if a user lives in a specific area, the server obtains information about handicraft workshops for seniors held in that area from an external data source and recommends them to the user.

[0159] Terminal side embodiment

[0160] The terminal performs the following processing.

[0161] 1. User Interface (UI)

[0162] Hardware: Tablets, smartphones (e.g. iPad)

[0163] Software: UI frameworks (e.g., Flutter), speech recognition systems (e.g., Google Speech-to-Text)

[0164] The device provides an intuitive UI that is easy for seniors to operate. For example, if a user uses a voice command to say "Find friends," the device recognizes the voice command and activates the friend search function. The device also displays search results in capital letters.

[0165] User-Side Embodiment

[0166] The user performs the following process.

[0167] 1. Update your profile

[0168] Users update their profile information and send the data to the server via their devices. For example, a user adds "gardening" as a new hobby. This information is immediately sent to the server and stored.

[0169] 2. Participate in community events

[0170] Users can easily access local events through their devices and register to participate. For example, users select an event they are interested in from a list of local events displayed within the platform and press the "Participate" button. Their participation request is then sent to the server, completing their participation in the event.

[0171] Example of a generative AI model prompt

[0172] Update Profile function description prompt:

[0173] Please explain the profile update function of a social networking platform for seniors. Please provide a detailed description of the specific processes that are performed from the perspectives of the server, device, and user, including both hardware and software. Include specific examples.

[0174] Event participation function description generation prompt:

[0175] Please explain the event participation function of a social networking platform for seniors. Please provide a detailed description of the specific processes that are performed from the perspectives of the server, device, and user, including both hardware and software. Include specific examples.

[0176] In this way, the entire system functions with the server, terminals, and users working together to promote social interaction, health management, and community participation among the elderly.

[0177] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0178] Step 1:

[0179] User enters profile information

[0180] Input: A user accesses a profile page on their device and enters personal information such as hobbies and location.

[0181] Specific operation: The user enters "Hobby: Gardening" and "Location: Tokyo" and presses the "Save" button.

[0182] Data processing and calculation: None

[0183] Output: Input data (hobbies, location)

[0184] Step 2:

[0185] The device sends the data to the server

[0186] Input: Profile information entered by the user

[0187] Specific behavior: The device generates the following JSON data and sends it to the server: {"hobby": "gardening", "location": "Tokyo"}

[0188] Data processing and calculation: Convert data into JSON format.

[0189] Output: JSON data sent to the server

[0190] Step 3:

[0191] The server saves the data to a database

[0192] Input: JSON data sent from the terminal

[0193] What happens: The server executes the following SQL query: INSERT INTO users (hobby, location) VALUES ('Gardening', 'Tokyo')

[0194] Data processing and calculation: Convert JSON data into SQL statements and save them in the database.

[0195] Output: User information stored in the database

[0196] Step 4:

[0197] The server analyzes the user data

[0198] Input: User information stored in the database

[0199] What it does: The server runs a Python script to analyze user behavior data using a machine learning model (e.g., TensorFlow).

[0200] Data processing and computation: Data analysis using machine learning models.

[0201] Output: Analysis results (user interests, behavioral patterns)

[0202] Step 5:

[0203] The server generates recommended content

[0204] Input: Analysis results

[0205] What it does: The server lists content, potential friends, and events based on the user's interests.

[0206] Data processing and calculation: The analysis results are compared with the information in the database to create the optimal recommendation list.

[0207] Output: Recommendation list

[0208] Step 6:

[0209] The server sends the recommendation list to the device.

[0210] Input: Recommendation list

[0211] What happens: The server generates the following JSON data and sends it to the device: {"recommendations": ["health-related articles", "online fitness classes"]}

[0212] Data processing and calculation: Convert the recommendation list into JSON format.

[0213] Output: JSON data sent to the device

[0214] Step 7:

[0215] The device displays the UI

[0216] Input: Profile information, recommendation list

[0217] What it does: The device displays information on the main menu screen with large icons and fonts.

[0218] Data processing and calculation: None

[0219] Output: The UI that the user sees

[0220] Step 8:

[0221] The device recognizes your voice commands

[0222] Input: User's voice command

[0223] What it does: When a user says "Find friends," the device uses a voice recognition system (e.g., Google Speech-to-Text) to interpret the voice command.

[0224] Data processing and computation: Converting voice data into text.

[0225] Output: Text representation of voice commands

[0226] Step 9:

[0227] Your device will display the search results.

[0228] Input: Text form of voice command

[0229] What it does: Your device will display a list of potential "Find Friends" search results in capital letters.

[0230] Data processing and calculation: None

[0231] Output: Search results displayed in the UI

[0232] Step 10:

[0233] User views the event list

[0234] Input: Recommendation list

[0235] What happens: The user opens the Events section.

[0236] Data processing and calculation: None

[0237] Output: Event list

[0238] Step 11:

[0239] User chooses to attend the event

[0240] Input: Event list

[0241] Specific actions: The user selects "Craft Workshop" and presses the "Participate" button.

[0242] Data processing and calculation: None

[0243] Output: Join request

[0244] Step 12:

[0245] The device sends a join request to the server

[0246] Input: Join request

[0247] Specific operation: The device generates the following JSON data and sends it to the server: {"event": "Craft Workshop", "user": "F"}

[0248] Data processing and calculation: Convert the join request into JSON format.

[0249] Output: JSON data sent to the server

[0250] In this way, the entire system functions with the server, terminals, and users working together to promote social interaction, health management, and community participation among the elderly.

[0251] (Application example 1)

[0252] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0253] It has been difficult to effectively recommend content, friend candidates, and events that users are interested in on social networking platforms for seniors, as well as provide information about local food events. A user interface that is visually easy to operate is also required. To solve these challenges, a system is needed to support the dietary habits of seniors and promote social interaction.

[0254] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0255] In this invention, the server includes means for collecting and storing user data, means for applying an AI model to the collected user data and analyzing it, means for recommending content, friend candidates, and events based on the analysis results, means for recommending food items and delivery options, means for acquiring local food event information from an external data source, and means for storing the acquired food event information. This makes it possible to accurately recommend not only content, friend candidates, and events that interest elderly people, but also food items and local food events that interest them.

[0256] "User Data" refers to any data relating to a user, such as a user's profile information, behavioral data, and preference information.

[0257] "Means for storage" refers to a mechanism for storing collected user data in a database.

[0258] An "AI model" is a collection of algorithms that use artificial intelligence to analyze data and make predictions.

[0259] "Means of analysis" refers to the process of applying an AI model to collected user data to analyze and evaluate that data.

[0260] The "means for recommending content, friend candidates, and events" is a function for presenting content, friend candidates, and events that are suitable for the user based on the analysis results.

[0261] The "means for recommending food items and delivery options" is a function for presenting appropriate food items and delivery services to a user based on the user's preference data.

[0262] An "external data source" is a mechanism for collecting information from data providers outside the system.

[0263] "Local food event information" is information about food-related events held in a specific region.

[0264] An "intuitive user interface" is an easy-to-understand screen designed to allow users to operate it easily.

[0265] "Visual display means" refers to a mechanism for outputting information on the screen in a form that is easy for the user to understand.

[0266] "Server" means a centralized management system used to manage user data, perform analysis, and store results.

[0267] This invention realizes a system that provides a wide range of recommendations, including food items and food events, on a social networking platform for seniors.

[0268] Server-side implementation

[0269] 1. Collection and storage of user data

[0270] Overview: The server collects user profile information, behavioral data, and preference information and stores it in a database.

[0271] Software used: Database management system (DBMS)

[0272] Example: When a user enters their hobbies and location on their profile page, this information is sent to the server and automatically stored in a database.

[0273] 2. Data analysis and recommendation

[0274] Overview: The server applies an AI model to the collected data to analyze it, and based on the results, recommends the most suitable content, friend candidates, food items, and food events to the user.

[0275] Software used: Generative AI model algorithms, machine learning libraries (e.g., TensorFlow, PyTorch)

[0276] Example: If a user has frequently viewed "pizza" related content in the past, the server can analyze their behavioral patterns and recommend new pizza-related delivery options or local pizza festivals.

[0277] 3. Acquisition and provision of information on local food events

[0278] Overview: The server obtains local food event information from external data sources, stores it in a database, and recommends relevant events based on the user's location information.

[0279] Software used: External API (e.g., event information API)

[0280] Example: If the user lives in "Yokohama City", information about pizza festivals held in the area is retrieved from an external data source and recommended to the user.

[0281] Terminal side embodiment

[0282] 1. Intuitive User Interface (UI)

[0283] Overview: The device provides an intuitive UI that is easy for seniors to operate, and includes features such as voice control and uppercase fonts.

[0284] Hardware used: smartphone, head-mounted display (HMD)

[0285] Example: If a user uses a voice command to say, "Tell me what pizzas are best," the device recognizes the voice command and displays related food items and events in a large font.

[0286] 2. Visual display of local food event information

[0287] Overview: Visually displays recommendation information and event information from the server.

[0288] Software used: GUI library (e.g. React Native, Flutter)

[0289] Example: A list of local food events is displayed, and users can select an event that interests them and view more information.

[0290] User-Side Embodiment

[0291] 1. Update your profile

[0292] Overview: A user updates his or her profile information and sends the data to a server via the device.

[0293] Example: When a user adds a new hobby to their profile, "making pizza," this information is immediately sent to the server and stored.

[0294] 2. Participating in food events

[0295] Overview: Users use their devices to access local food events and register to participate.

[0296] Example: A user selects an event of interest from a list of local food events displayed within the platform and presses the "Attend" button.

[0297] These efforts will help promote eating habits and social interactions among the elderly and increase the convenience of the platform.

[0298] Example prompt sentence:

[0299] If a user enters "I like Twice Cooked Pork" in their profile, the server will recommend "food items and related events related to Twice Cooked Pork."

[0300] For example, if the user sets the location information as "Yokohama City," information about the Twice Cooked Pork Festival will be provided.

[0301] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0302] Step 1:

[0303] The server collects and stores user data

[0304] Input: Users input profile information and preference information

[0305] Processing: The server receives this information and stores it in a database. Specifically, it analyzes the data sent from the smartphone or head-mounted display (HMD) and stores it in the database in an appropriate format.

[0306] Output: User information stored in the database

[0307] Step 2:

[0308] The server applies an AI model to the collected data and analyzes it.

[0309] Input: User data stored in the database

[0310] Processing: The server analyzes the data using machine learning libraries (e.g., TensorFlow, PyTorch) to understand user preferences and behavioral patterns. An AI model analyzes the data and identifies recommendations.

[0311] Output: Analysis results, list of recommended targets

[0312] Step 3:

[0313] The server uses the analysis to recommend content, friend suggestions, events, food items, and delivery options.

[0314] Input: Analysis results, list of recommended targets

[0315] Processing: The server categorizes recommendations into categories and selects the most suitable content, friend suggestions, events, food items, and delivery options for the user, using a generative AI model algorithm.

[0316] Output: Recommended content for the user, friend suggestions, events, food items, and delivery options

[0317] Step 4:

[0318] The server retrieves local food event information from an external data source.

[0319] Input: User's location

[0320] Processing: The server uses an external API (e.g., an event information API) to obtain local food event information based on the user's location. Specifically, the server sends an API request and temporarily stores the obtained data.

[0321] Output: Local food event information

[0322] Step 5:

[0323] The server stores the food event information it has obtained.

[0324] Input: Retrieved local food event information

[0325] Processing: The server formats the food event information and stores it in a database, allowing for fast responses to user requests.

[0326] Output: Food event information stored in the database

[0327] Step 6:

[0328] The device accepts input from the user through the user interface (UI) and sends a request to the server.

[0329] Input: Voice commands and touch input from the user

[0330] Processing: The device receives the user's input, converts it into an appropriate format, and sends a request to the server. Specifically, it uses voice recognition technology to convert voice commands into text data.

[0331] Output: Request data to the server

[0332] Step 7:

[0333] The terminal displays the response from the server to the user.

[0334] Input: Response data from the server

[0335] Processing: The device visually displays the response data received from the server, specifically by displaying the information in large font on the smartphone or HMD screen so that the user can easily understand it.

[0336] Output: Information displayed to the user

[0337] Step 8:

[0338] The device visually displays information about local food events.

[0339] Input: Local food event information obtained from the server

[0340] Processing: The device displays food event information in a visually easy-to-understand format, such as a list or card format, allowing the user to view the details.

[0341] Output: Visual display of local food event information

[0342] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0343] The present invention relates to a system for providing more personalized services on a social networking platform for seniors by combining the collection and storage of user data, data analysis using AI models, recommendations of content, friend candidates, and events, as well as an emotion engine that recognizes user emotions. Specific embodiments of this system are described below.

[0344] Server-side implementation

[0345] 1. User Data Collection and Storage:

[0346] Overview: The server collects profile information, behavioral data, and emotional information of elderly users and stores them in a database.

[0347] Example: User A enters his / her hobbies and location on a profile page, and the information is sent from the device to the server and stored in the server's database. In addition, the user's emotional reactions while watching a video are also recorded as emotional data.

[0348] 2. Data analysis and recommendations:

[0349] Overview: The server applies AI models to the collected data, analyzes the user's behavioral patterns and emotional data, and based on the results, recommends the most suitable content, friend candidates, and events to the user.

[0350] Example: If User B has frequently viewed health-related content in the past and the emotion engine detects a positive reaction to it, the server can recommend new health articles or online fitness classes.

[0351] 3. Acquisition and provision of local event information:

[0352] Overview: The server obtains local event and community information from external data sources, stores it in a database, and recommends related events based on the user's location and emotion data.

[0353] Example: If user C is interested in crafts and has positive feelings about that interest, the server will recommend information about craft workshops taking place in the area.

[0354] Terminal side embodiment

[0355] 1. User Interface (UI):

[0356] Overview: The device provides an intuitive UI that is easy for seniors to operate, including features such as voice control and uppercase fonts.

[0357] Example: If user D uses a voice command to say "Find friends," the device will recognize the voice command, launch the friend search function, and display the search results in capital letters.

[0358] 2. Emotion Engine Operation:

[0359] Overview: The device is equipped with an emotion engine that analyzes the user's emotions in real time from their facial expressions and tone of voice, and sends the data to a server.

[0360] Example: While user E is watching a video, the device analyzes the user's facial expressions with a camera and transmits emotional data to the server in real time.

[0361] User-Side Embodiment

[0362] 1. Update your profile:

[0363] Overview: Users update their profile information and emotional information and send it to the server via their device.

[0364] Example: User F adds "gardening" as a new hobby, and emotion data about the hobby is also sent to the server.

[0365] 2. Participate in community events:

[0366] Summary: Users can easily access local events through their devices and select recommended events using emotional data when registering to attend.

[0367] Example: User G selects an event of interest from a list of local events displayed within the platform, and presses the "Participate" button based on the emotional data for that event.

[0368] In this way, by combining the emotion engine, the system of the present invention provides a more personalized user experience and improves the quality of life for the elderly. The server, terminal, and user work together to provide optimal services tailored to the user's emotional state.

[0369] The processing flow will be explained below.

[0370] User Data Collection and Storage Process Steps

[0371] Step 1:

[0372] The user enters profile information.

[0373] User: Enter their hobbies, location, health information, etc. on their profile page.

[0374] Example: User A enters "gardening" as a hobby.

[0375] Step 2:

[0376] The entered data is sent to the server.

[0377] Terminal: Sends input information to the server in real time.

[0378] Example: The terminal sends user A's hobby information to the server as a data packet.

[0379] Step 3:

[0380] Save the data to a database.

[0381] Server: Validates the received data and stores it in the database.

[0382] Example: The server adds the hobby "gardening" to User A's profile.

[0383] Processing steps for collecting and storing emotion data

[0384] Step 1:

[0385] Start your emotion engine.

[0386] Device: Activate the emotion engine when watching videos or browsing content.

[0387] Example: When a user starts watching a fitness video, the device's emotion engine is activated.

[0388] Step 2:

[0389] Emotion data is analyzed and sent to the server.

[0390] Device: Analyzes the user's facial expressions and tone of voice in real time and sends the results to the server.

[0391] Example: If a user smiles while watching a video, send that positive emotion data to the server.

[0392] Step 3:

[0393] Emotion data is stored in a database.

[0394] Server: Validates the received emotion data and stores it in a database.

[0395] Example: The server integrates user emotion data into User A's profile.

[0396] Data analysis and recommendation processing steps

[0397] Step 1:

[0398] Periodically read the stored data.

[0399] Server: Periodically reads user data and emotion data from the database.

[0400] Example: The server reads user A's behavioral and emotional data every day.

[0401] Step 2:

[0402] Apply AI models to analyze the data.

[0403] Server: Analyzes the stored data using AI models to analyze user trends.

[0404] Example: The server analyzes which genres of content User A has frequently viewed in the past month and which content he has responded positively to.

[0405] Step 3:

[0406] Generate recommendations based on the analysis results.

[0407] Server: Based on the analysis results, it generates the most suitable content, friend suggestions, and events for the user.

[0408] Example: The server recommends to user A new articles about "gardening" and other users with the same hobby.

[0409] Step 4:

[0410] Prepare the recommendations in the form of a notice.

[0411] Server: Formats the recommendation information and prepares it to be sent to the device as a notification message.

[0412] Example: A server creates a notification that says "Join an online group for gardening enthusiasts."

[0413] Processing steps for obtaining and providing local event information

[0414] Step 1:

[0415] Retrieve local event information from an external data source.

[0416] Server: Collects local event information from external APIs and databases.

[0417] Example: The server retrieves the events calendar from the API of a local cultural center.

[0418] Step 2:

[0419] Save the retrieved data in the database.

[0420] Server: Validates the acquired event information and stores it in an internal database.

[0421] Example: The server stores the obtained information about the craft workshop in a database.

[0422] Step 3:

[0423] Recommend events based on user location and emotion data.

[0424] Server: Obtains user location and emotion data and recommends relevant events.

[0425] Example: Notify user B of a craft workshop near where they currently live. If the user has a strong interest in crafts, the event will be recommended even more strongly.

[0426] User interface provision and operation processing steps

[0427] Step 1:

[0428] The user logs in and sees the main dashboard.

[0429] Terminal: Receives login information, authenticates the user, and displays the main dashboard.

[0430] Example: When User C logs in, the dashboard displays recent notifications and recommended content.

[0431] Step 2:

[0432] Accepts interaction from the user.

[0433] Device: Accepts actions such as button presses, swipes, and voice commands.

[0434] Example: User D enters the voice command "Find friends."

[0435] Step 3:

[0436] Send the request to the server.

[0437] Terminal: Sends appropriate requests to the server based on user actions.

[0438] Example: The device analyzes user D's voice command and sends a friend search request to the server.

[0439] Step 4:

[0440] Displays the response from the server.

[0441] Terminal: Receives the response from the server and displays it to the user.

[0442] Example: The device displays the search results from the server on the screen and provides new friend candidates to User D.

[0443] In this way, the platform of the present invention provides a high-level user experience that includes emotional data by linking the terminal, server, and user.

[0444] Example 2

[0445] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0446] Current social networking platforms for seniors lack personalized services, making it difficult for them to find content, friends, and events that suit them. Another issue is that few services utilize emotional data, making it difficult to provide appropriate recommendations that match current emotions.

[0447] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for collecting and storing user data, a means for applying a generative AI model to the collected user data and analyzing it, a means for recommending content, friend candidates, and events based on the analysis results, a means for collecting and storing user emotion data, and a means including an emotion analysis engine for performing analysis based on the emotion data. This makes it possible to provide personalized services by utilizing the user's behavioral data and emotion data.

[0448] "User Data" refers to a user's profile information, behavioral data, location information, and any other data related to the use of the Platform.

[0449] A "generative AI model" is a model that uses machine learning algorithms to analyze data and generate new information and predictions based on the learning results.

[0450] An "emotion analysis engine" refers to software or hardware functionality that analyzes emotional data from a user's facial expressions, voice, etc. in real time.

[0451] "Content" refers to articles, videos, music, images, and any other information provided to users.

[0452] "Friend candidates" refers to data for recommending other users who may be of interest or related to the user.

[0453] "Event" refers to a workshop, seminar, sporting event, or other gathering held in the community.

[0454] An "intuitive user interface" refers to a simple and easy-to-understand screen layout and operating procedures designed to be easy for seniors to operate.

[0455] "Voice operation" refers to a function that allows the user to perform various operations on the system using voice commands.

[0456] "Capital font" refers to a font that is displayed in a larger-than-normal character size to improve legibility.

[0457] "External data sources" refers to online services or APIs that provide various data that can be accessed from outside the system.

[0458] "Location information" refers to geographic data that indicates a user's current location.

[0459] MODE FOR CARRYING OUT THE INVENTION

[0460] The present invention relates to a system for providing more personalized services on a social networking platform for seniors by combining the collection and storage of user data, data analysis using a generative AI model, recommendations of content, friend candidates, and events, as well as a sentiment analysis engine that recognizes user emotions. Specific embodiments of this system are described below.

[0461] Server-side implementation

[0462] User Data Collection and Storage:

[0463] The server obtains the profile information, behavioral data, and emotional information of the elderly user and stores this information in a database. For example, when a user enters their hobbies or location on the profile page, the device sends this information to the server as an HTTP POST request. The server then saves the received data in a database (e.g., MySQL) using an INSERT statement. If the saving process is successful, the server returns a status indicating that the save was successful to the device.

[0464] Data analysis and recommendations:

[0465] The server applies a generative AI model to the collected data and analyzes the user's behavioral patterns and emotional data. Based on the results, it recommends optimal content, friend candidates, and events to the user. For example, the server periodically retrieves user data from the database using a SELECT statement and transfers that data to the AI ​​analysis server. This analysis is performed using Python and TensorFlow. Based on the analysis results, recommended items are generated and cached in the database. These recommendations are displayed the next time the user logs in.

[0466] Acquiring and providing local event information:

[0467] The server retrieves local event information from external data sources and recommends relevant events to users based on location and emotion data. For example, the server periodically calls an external API (e.g., Eventbrite API) to retrieve local event information, extracts the necessary information, and stores it in a database. When a user logs in, the server picks up and recommends events held in the surrounding area.

[0468] Terminal side embodiment

[0469] User Interface (UI):

[0470] The device provides an intuitive UI that seniors can easily operate, including features such as voice control and capital font. For example, when a user says the voice command "Find friends," the device converts the speech to text using the Google Cloud Speech-to-Text API, creates a search query based on that text, and sends it to the server. The device then displays the search results from the server in capital font.

[0471] Sentiment Analysis Engine:

[0472] The device is equipped with an emotion analysis engine that analyzes emotions in real time from the user's facial expressions and tone of voice and sends the data to a server. For example, while the user is watching a video, the device's camera captures facial expressions in real time and sends the analysis data to a server. This analysis uses OpenCV and deep learning libraries (e.g., OpenFace).

[0473] User-Side Embodiment

[0474] Update your profile:

[0475] Users update their profile information and emotional information and send it to the server via their devices. For example, if a user adds "gardening" as a new hobby, the changes are sent to the server as an HTTP POST request, and the server updates the database.

[0476] Participate in community events:

[0477] Users can easily access local events through their devices and register to participate. Emotional data can also be used to select recommended events. For example, when a user selects an event they are interested in from the event list and presses the "Participate" button, the device sends the information to the server, which then stores the participation information in a database.

[0478] Prompt Sentence Examples

[0479] "Suggest new health articles or online fitness classes to users who have previously expressed positive feelings about health-related content."

[0480] This system allows the server, device, and user to work together to utilize user behavioral and emotional data, providing a personalized user experience and improving the quality of life for the elderly.

[0481] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0482] Program processing flow

[0483] Server Action:

[0484] Step 1:

[0485] The server receives user data sent from the device. The input includes user profile information and behavioral data. Specifically, the server receives an HTTP POST request and stores the data in temporary memory.

[0486] Step 2:

[0487] The server saves the received user data in a database. MySQL is used as the database. For data processing, the received data is converted into an INSERT statement and inserted into the database. As output, a status indicating successful saving is generated and returned to the terminal.

[0488] Step 3:

[0489] The server periodically retrieves user data from the database. The input includes user profile information and behavioral data stored in the database. It executes SELECT statements to retrieve data from the database and loads the retrieved data into memory.

[0490] Step 4:

[0491] The server inputs the acquired user data into the generative AI model and performs data analysis. Specifically, it runs the generative AI model using Python and TensorFlow. Data calculations involve clustering and pattern recognition of user behavior patterns and emotional data. The output is the analysis results.

[0492] Step 5:

[0493] The server generates recommended items based on the analysis results. The input includes the analysis results of the AI ​​model. The generated recommended items are cached in a database. The output is the cached recommended items.

[0494] Step 6:

[0495] The server retrieves local event information from an external data source. Specifically, it calls an external API (e.g., Eventbrite API) to retrieve local event information. The input includes the API request. The retrieved event information is parsed in JSON format and the necessary fields are extracted. The extracted event information is obtained as output.

[0496] Step 7:

[0497] The server saves the acquired event information in the database. Specifically, it creates an INSERT statement based on the extracted event information and inserts it into the database. As an output, it generates a status indicating that the save was successful.

[0498] Step 8:

[0499] The server recommends local events based on the user's location and emotion data. The input includes the user's location and emotion data. Based on this, the server searches for appropriate events and lists them as recommended items. The output is a list of related events.

[0500] Terminal handling:

[0501] Step 1:

[0502] The device accepts input from the user, including voice commands and touch gestures. Specific operations include capturing voice data for voice input and recognizing screen gestures for touch input.

[0503] Step 2:

[0504] The device processes the received user input and sends a request to the server. The input includes the user input data. Specifically, in the case of voice input, the device converts the voice to text using the Google Cloud Speech-to-Text API, generates an HTTP request, and sends it to the server. The output is a request to the server.

[0505] Step 3:

[0506] The terminal receives the response from the server. Specifically, it receives the HTTP response and analyzes its contents. The input includes the response data from the server. The output is the analyzed data.

[0507] Step 4:

[0508] The terminal displays the server's response to the user. Specific display operations include displaying text in uppercase font and outputting voice using speech synthesis. The output allows the user to confirm the information visually or audibly.

[0509] Step 5:

[0510] The device collects the user's facial expressions and voice tone in real time. Specifically, it captures facial expression data with a camera and records voice data with a microphone. The input includes the user's real-time facial expressions and voice data.

[0511] Step 6:

[0512] The device inputs the collected facial expression and voice data into an emotion analysis engine for analysis. Libraries such as OpenCV and OpenFace are used for the analysis. Data calculations involve facial expression recognition and voice tone analysis. The output is analyzed emotion data.

[0513] Step 7:

[0514] The device sends the emotion data obtained as a result of the analysis to the server. Specifically, it generates an HTTP POST request and sends it to the server. The input includes the analyzed emotion data. The output is the completion of the emotion data transfer to the server.

[0515] User Action:

[0516] Step 1:

[0517] A user enters or updates profile information, including new hobbies, location, etc. The user enters the data on the device's profile editing page.

[0518] Step 2:

[0519] The user sends profile information to the server through the device. After checking the input data, the user presses the send button to generate an HTTP POST request, which the device then sends to the server. As an output, a send request to the server is generated.

[0520] Step 3:

[0521] The user operates the device to browse the local event list. Specifically, the user opens the event list page on the device and selects an event they are interested in. The input includes the user's selection data.

[0522] Step 4:

[0523] A user registers to participate in an event. After selecting an event, the user presses the "Participate" button to generate a request to send information about the selected event to the server. The output is a participation request sent to the server.

[0524] Step 5:

[0525] The user waits for a response from the server confirming their participation in the event. Specifically, the user receives the response from the server using the notification function on the device. The input includes the response data from the server. The output is a notification confirming their participation.

[0526] (Application example 2)

[0527] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0528] Conventional social networking platforms for seniors have difficulty providing personalized services that fully reflect users' emotions and preferences. Furthermore, conventional technologies are insufficient when it comes to providing a user interface that is easy for seniors to use and recommending local event information. In particular, there is a demand for technology that can analyze seniors' emotions and recommend the most appropriate content and events based on that analysis.

[0529] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0530] In this invention, the server includes means for collecting and storing user data, means for applying a generative AI model to the collected user data and analyzing it, means for recommending content, friend candidates, and events based on the analysis results, means for operating an emotion engine that analyzes emotions from the user's facial expressions and tone of voice in real time, and means for transmitting emotion data to the server, thereby enabling the provision of personalized services based on the user's emotional state.

[0531] A "communication platform for the elderly" is an online system aimed primarily at elderly people for the purpose of mutual interaction.

[0532] "User data" refers to various information about an individual, including a user's profile information, behavioral data, emotional data, and the like.

[0533] A "generative AI model" is an artificial intelligence algorithm used to analyze user behavioral and emotional data.

[0534] "Means for analysis" refers to the function of applying a generative AI model to collected user data and performing analysis.

[0535] "Content" includes information or entertainment elements such as articles, videos, images, etc. provided to users.

[0536] "Friend candidates" refer to other users with whom the user may potentially build new friendships.

[0537] "Event" means any gathering or activity, held online or offline, in which users can participate.

[0538] The "Emotion Engine" is a system that analyzes emotions in real time from a user's facial expressions and tone of voice.

[0539] "Emotion data" is information about the user's emotional state obtained by the emotion engine.

[0540] "Server" means the primary computer system that collects, stores, and analyzes user data and uses the generative AI model.

[0541] "External Data Sources" refers to information sources outside the Platform that provide information such as local event information.

[0542] "Location information" is data indicating the user's current location and movement information.

[0543] An "intuitive user interface" is a graphical or audio-based interface designed to be easy for users to operate.

[0544] "Recommendation" refers to the activity of suggesting specific content, potential friends, events, etc. to the user based on the analysis results.

[0545] "Real-time" refers to immediate processing and feedback without delay.

[0546] This system is designed to provide a communication platform for the elderly and recommend personalized services by analyzing users' emotional data. The system operates in cooperation with the server, terminals, and users.

[0547] Server-side implementation

[0548] User Data Collection and Storage:

[0549] The server collects user profile information, behavioral data, and emotional data and stores them in a database. Specifically, the profile information and behavioral history entered by the user into the device, as well as the emotional data analyzed by the emotion engine, are sent to the server and stored there.

[0550] Data analysis and recommendations:

[0551] The server applies generative AI models to the collected data to analyze the user's behavioral patterns and emotional data. Based on the analysis results, the server can recommend content, friend suggestions, and local events that are most suitable for the user. For example, if a user prefers health-related content, the server can recommend new health articles and online fitness classes.

[0552] Retrieving information from external data sources:

[0553] The server retrieves necessary data from external data sources to obtain local event and community information and stores it in a database, which enables recommendations of local events based on the user's location and emotion data.

[0554] Terminal side embodiment

[0555] User Interface (UI):

[0556] The device offers an intuitive UI that seniors can easily operate, including voice control, large font, and touch control. For example, if a user uses the voice command "Find friends," the device recognizes the command and launches the friend search function.

[0557] Emotion Engine Operation:

[0558] The device has an emotion engine built in that analyzes the user's facial expressions and tone of voice to generate emotion data. This data is sent to a server in real time. For example, while the user is watching a video, the camera analyzes the user's facial expressions and sends the emotion data to the server.

[0559] User-Side Embodiment

[0560] Update your profile:

[0561] A user can update his / her profile information and emotional data and send it to the server through the terminal, for example, by adding a new hobby to his / her profile and sending the emotional data related to that hobby to the server.

[0562] Participate in the event:

[0563] Users can easily access local events through their devices and register to participate. Related events are recommended using emotion data, making it easier for users to participate in events that interest them. For example, a user who is interested in handicrafts will be recommended information about handicraft workshops being held in their area and can register to participate in those events.

[0564] Hardware and Software Use

[0565] Hardware:

[0566] Server: The main server for running the database and AI models

[0567] Camera: Analyzes the user's facial expressions

[0568] Microphone: Analyzes the user's voice tone

[0569] Smartphones and head-mounted displays (HMDs)

[0570] software:

[0571] Python, TensorFlow, OpenCV: Implementing a sentiment analysis engine and AI model

[0572] API server: Acquires and stores user data, receives emotion data

[0573] User Interface: UI that supports voice recognition and touch operation

[0574] Examples and prompts

[0575] example:

[0576] Example: When a user uses a virtual community assistant in an app installed on their smartphone, the camera analyzes the user's facial expressions and recommends products and events that the user is interested in in real time.

[0577] Prompt for the generative AI model:

[0578] "Analyze the reactions of users to products they are looking at while shopping and recommend other products related to the products that showed positive emotions."

[0579] In this way, the system can improve the quality of life for the elderly and provide more personalized services.

[0580] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0581] Step 1:

[0582] Entering and saving user data (terminal and server)

[0583] Users input their profile information and behavioral data through their devices. The devices then send this data to the server, which then stores it in a database. For example, a user might add a new hobby. The information entered includes profile information, behavioral history, and emotional data, and all of this data is managed centrally by the server.

[0584] Step 2:

[0585] Acquiring emotion data (device)

[0586] The device uses an emotion engine to obtain emotion data in real time from the user's facial expressions and voice tone. The emotion engine uses a camera and microphone to analyze the user's emotions and generate the results as data. The input in this step is the user's facial expressions and voice tone, and the output is the analyzed emotion data.

[0587] Step 3:

[0588] Sending emotional data (device and server)

[0589] The device transmits the acquired emotional data to a server in real time. The server receives this data and stores it in a database along with the user profile and behavioral data. Continuous acquisition of emotional data enables more precise analysis. The input is emotional data, and the output is transmission to the server and storage in the database.

[0590] Step 4:

[0591] Data analysis and information recommendation (server)

[0592] The server applies a generative AI model to the collected user data, analyzing behavioral patterns and emotional data. The analysis results in data that can be used to recommend content, friend candidates, and local events that are best suited to the user. The input for this step is the stored data, and the output is a recommendation list. Specifically, new health articles and online fitness classes will be recommended to users who prefer health-related content.

[0593] Step 5:

[0594] Obtaining information from external data sources (server)

[0595] The server retrieves the necessary data from external data sources to obtain local event and community information. The retrieved data is stored in a database and becomes the basis for recommendations based on the user's location and emotion data. The input is external data, and the output is stored in the database.

[0596] Step 6:

[0597] User Interface (Terminal)

[0598] The device provides an intuitive user interface designed for seniors. Users can easily operate it using voice commands, touch operations, and capital fonts. For example, if you use the voice command "Find friends," the device recognizes the command and activates the friend search function. In this step, the input is a voice command or touch operation, and the output is the activation of the corresponding function.

[0599] Step 7:

[0600] Event and content recommendations (device)

[0601] The content and events desired by the user are displayed on the device. Based on the recommendation list sent from the server, the most suitable content and event information for the user is displayed. The input is the recommendation data from the server, and the output is the display on the user interface. Specifically, for a user who prefers health-related information, related new articles and events are displayed.

[0602] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0603] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0604] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0605] [Second embodiment]

[0606] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0607] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0608] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0609] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0610] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0611] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0612] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0613] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0614] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0615] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0616] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0617] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0618] The present invention relates to a social networking platform for seniors, and provides a means for collecting and storing user data, a means for analyzing the data by applying an AI model, a means for recommending content, friend candidates, and events based on the analysis results, and a means for acquiring and storing local event information and community information. A specific embodiment of this system is described below.

[0619] Server-side implementation

[0620] 1. User Data Collection and Storage:

[0621] Overview: The server collects profile information, behavioral data, and health information of elderly users and stores it in a database.

[0622] Example: When user A enters his / her hobbies and location on the profile page, this information is sent from the device to the server and stored in the server's database.

[0623] 2. Data analysis and recommendations:

[0624] Overview: The server applies an AI model to the collected data to analyze it, and based on the results, recommends the most suitable content, friend candidates, and events to the user.

[0625] Example: If User B has frequently viewed health-related content in the past, the server can analyze their behavioral patterns and recommend new health articles or online fitness classes.

[0626] 3. Acquisition and provision of local event information:

[0627] Overview: The server obtains local event and community information from external data sources, stores it in a database, and recommends related events based on the user's location information.

[0628] Example: If user C lives in a particular area, information about craft workshops for seniors held in that area is retrieved from an external data source and recommended to user C.

[0629] Terminal side embodiment

[0630] 1. User Interface (UI):

[0631] Overview: The device provides an intuitive UI that is easy for seniors to operate, and includes features such as voice control and uppercase fonts.

[0632] Example: If user D uses a voice command to say "Find friends," the device will recognize the voice command, launch the friend search function, and display the search results in capital letters.

[0633] User-Side Embodiment

[0634] 1. Update your profile:

[0635] Overview: Users update their profile information and send that data to a server via their device.

[0636] Example: User E adds "gardening" as a new hobby. This information is immediately sent to the server and saved.

[0637] 2. Participate in community events:

[0638] Overview: Users can easily access and register for local events through their devices.

[0639] Example: User F selects an event he or she is interested in from a list of local events displayed within the platform and presses the "Participate" button. The request to participate is sent to the server, and the event participation is completed.

[0640] In this way, the present invention effectively promotes social interaction, health management, and community participation for the elderly through collaboration between servers, terminals, and users, thereby resolving the problems of traditional social networking platforms and improving the quality of life for the elderly.

[0641] The processing flow will be explained below.

[0642] User Data Collection and Storage Process Steps

[0643] Step 1:

[0644] The user enters profile information.

[0645] User: Enters their hobbies, location, health information, etc. on their profile page.

[0646] Example: User A enters "gardening" as a hobby.

[0647] Step 2:

[0648] The entered data is sent to the server.

[0649] Terminal: Sends input information to the server in real time.

[0650] Example: The terminal sends user A's hobby information to the server as a data packet.

[0651] Step 3:

[0652] Save the data to a database.

[0653] Server: Validates the received data and stores it in the database.

[0654] Example: The server adds the hobby "gardening" to User A's profile.

[0655] Data analysis and recommendation processing steps

[0656] Step 1:

[0657] Periodically read the stored data.

[0658] Server: Periodically reads user data from the database.

[0659] Example: The server reads user A's behavior data once a day.

[0660] Step 2:

[0661] Apply AI models to analyze the data.

[0662] Server: Analyzes the stored data using AI models to analyze user trends.

[0663] Example: The server analyzes which genre of content User A has frequently viewed in the past month.

[0664] Step 3:

[0665] Generate recommendations based on the analysis results.

[0666] Server: Based on the analysis results, it generates the most suitable content, friend suggestions, and events for the user.

[0667] Example: The server recommends to user A new articles about "gardening" and other users with the same hobby.

[0668] Step 4:

[0669] Prepare the recommendations in the form of a notice.

[0670] Server: Formats the recommendation information and prepares it to be sent to the device as a notification message.

[0671] Example: A server creates a notification that says "Join an online group for gardening enthusiasts."

[0672] Processing steps for obtaining and providing local event information

[0673] Step 1:

[0674] Retrieve local event information from an external data source.

[0675] Server: Collects local event information from external APIs and databases.

[0676] Example: The server retrieves the events calendar from the API of a local cultural center.

[0677] Step 2:

[0678] Save the retrieved data in the database.

[0679] Server: Validates the acquired event information and stores it in an internal database.

[0680] Example: The server stores the obtained information about the craft workshop in a database.

[0681] Step 3:

[0682] Recommend events based on the user's location.

[0683] Server: Obtains the user's location and recommends relevant events.

[0684] Example: User B is notified of a craft workshop near where he currently lives.

[0685] User interface provision and operation processing steps

[0686] Step 1:

[0687] The user logs in and sees the main dashboard.

[0688] Terminal: Receives login information, authenticates the user, and displays the main dashboard.

[0689] Example: When User C logs in, the dashboard displays recent notifications and recommended content.

[0690] Step 2:

[0691] Accepts interaction from the user.

[0692] Device: Accepts actions such as button presses, swipes, and voice commands.

[0693] Example: User D enters the voice command "Find friends."

[0694] Step 3:

[0695] Send the request to the server.

[0696] Terminal: Sends appropriate requests to the server based on user actions.

[0697] Example: The device analyzes user D's voice command and sends a friend search request to the server.

[0698] Step 4:

[0699] Displays the response from the server.

[0700] Terminal: Receives the response from the server and displays it to the user.

[0701] Example: The device displays the search results from the server on the screen and provides new friend candidates to User D.

[0702] In this way, the platform of the present invention provides a high-level user experience through cooperation between users, terminals, and servers.

[0703] Example 1

[0704] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0705] When seniors use social networking platforms, they face challenges such as difficulty in operation, social isolation, and digital divides. Furthermore, it is difficult to efficiently recommend content, friend candidates, and local event information specifically for seniors. Therefore, there is a need to provide a platform that seniors can easily operate and that allows them to receive appropriate information and content.

[0706] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0707] In this invention, the server includes means for collecting and storing user data, means for applying a machine learning model to the collected user data and analyzing it, means for recommending content, friend candidates, and events based on the analysis results, means for acquiring and storing local event information and community information from external data sources, a terminal for providing a user interface, means for a user to update their own profile information and send the updated information to the server via the terminal, means for providing a user interface that the user can easily operate using voice commands and uppercase fonts, means for transmitting data collected by the terminal and user-input data to the server, means for displaying responses from the server to the user, means for recommending related local events based on the user's location information, and means for accepting and transmitting requests to participate in local events to the server. This allows elderly people to easily operate the device and receive information and content that meets their individual needs.

[0708] "User Data" refers to information about an individual user, such as the elderly user's profile information, behavioral data, and health information.

[0709] A "machine learning model" refers to an artificial intelligence algorithm that analyzes data and makes predictions or classifications based on the results.

[0710] "Content" refers to any information or material provided on the Platform, including articles, videos, and event information.

[0711] "Friend Suggestions" refers to other users on the social networking platform who are recommended to you based on your interests and behavioral data.

[0712] "Event" means a local or online gathering or activity that users can participate in.

[0713] "External data sources" refers to sources for obtaining data from outside the platform, such as information providers or APIs outside the platform.

[0714] "User interface" refers to the screens and operating means that allow users to interact with the system, and includes those that are particularly easy for seniors to use.

[0715] "Terminal" refers to the device through which a user accesses the platform, such as a smartphone or tablet.

[0716] "Voice command" refers to a voice input method in which a user gives instructions to a system using voice.

[0717] "Server" refers to a remote computer system that stores data, analyzes data, generates recommendations, etc.

[0718] "Location information" is information that indicates the user's geographical location and is used to recommend related local events.

[0719] "Local Events" refers to events such as workshops and gatherings that take place in a specific geographic area.

[0720] A "participation request" refers to a request by a user to indicate their intention to participate in a particular event and to convey that information to the system.

[0721] "Storage" refers to the act of keeping collected data or information in a database or storage.

[0722] The present invention relates to a social networking platform for seniors, and includes means for collecting and storing user data, means for analyzing the data by applying a machine learning model, means for recommending content, friend candidates, and events based on the analysis results, means for acquiring and storing local event information and community information from external data sources, a terminal for providing a user interface, and means for providing a user interface that can be easily operated by users using voice commands and uppercase fonts. Specific embodiments are described below.

[0723] Server-side implementation

[0724] The server performs the following process.

[0725] 1. Collection and storage of user data

[0726] Hardware: Servers, data servers (e.g. Dell PowerEdge)

[0727] Software: Database management system (e.g., MySQL), collection program (e.g., written in Python)

[0728] The server collects the user's profile information, behavioral data, and health information and stores them in a database. For example, when a user enters their hobbies and location on the profile page, this information is sent from the device to the server and stored in the server's database.

[0729] 2. Data analysis and recommendation

[0730] Hardware: Server, GPU (e.g. NVIDIA Tesla)

[0731] Software: Machine learning libraries (e.g., TensorFlow), data analysis programs (e.g., written in Python)

[0732] The server applies machine learning models to the collected data and analyzes it, and based on the results, recommends the most suitable content, friend candidates, and events to the user. For example, if a user has frequently viewed health-related content in the past, the server can analyze their behavioral patterns and recommend new health articles or online fitness classes.

[0733] 3. Acquisition and provision of local event information

[0734] Hardware: Server

[0735] Software: External API client (e.g. written in Python), database management system (e.g. MySQL)

[0736] The server obtains local event and community information from external data sources, stores it in a database, and recommends related events based on the user's location information. For example, if a user lives in a specific area, the server obtains information about handicraft workshops for seniors held in that area from an external data source and recommends them to the user.

[0737] Terminal side embodiment

[0738] The terminal performs the following processing.

[0739] 1. User Interface (UI)

[0740] Hardware: Tablets, smartphones (e.g. iPad)

[0741] Software: UI frameworks (e.g., Flutter), speech recognition systems (e.g., Google Speech-to-Text)

[0742] The device provides an intuitive UI that is easy for seniors to operate. For example, if a user uses a voice command to say "Find friends," the device recognizes the voice command and activates the friend search function. The device also displays search results in capital letters.

[0743] User-Side Embodiment

[0744] The user performs the following process.

[0745] 1. Update your profile

[0746] Users update their profile information and send the data to the server via their devices. For example, a user adds "gardening" as a new hobby. This information is immediately sent to the server and stored.

[0747] 2. Participate in community events

[0748] Users can easily access local events through their devices and register to participate. For example, users select an event they are interested in from a list of local events displayed within the platform and press the "Participate" button. Their participation request is then sent to the server, completing their participation in the event.

[0749] Example of a generative AI model prompt

[0750] Update Profile function description prompt:

[0751] Please explain the profile update function of a social networking platform for seniors. Please provide a detailed description of the specific processes that are performed from the perspectives of the server, device, and user, including both hardware and software. Include specific examples.

[0752] Event participation function description generation prompt:

[0753] Please explain the event participation function of a social networking platform for seniors. Please provide a detailed description of the specific processes that are performed from the perspectives of the server, device, and user, including both hardware and software. Include specific examples.

[0754] In this way, the entire system functions with the server, terminals, and users working together to promote social interaction, health management, and community participation among the elderly.

[0755] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0756] Step 1:

[0757] User enters profile information

[0758] Input: A user accesses a profile page on their device and enters personal information such as hobbies and location.

[0759] Specific operation: The user enters "Hobby: Gardening" and "Location: Tokyo" and presses the "Save" button.

[0760] Data processing and calculation: None

[0761] Output: Input data (hobbies, location)

[0762] Step 2:

[0763] The device sends the data to the server

[0764] Input: Profile information entered by the user

[0765] Specific behavior: The device generates the following JSON data and sends it to the server: {"hobby": "gardening", "location": "Tokyo"}

[0766] Data processing and calculation: Convert data into JSON format.

[0767] Output: JSON data sent to the server

[0768] Step 3:

[0769] The server saves the data to a database

[0770] Input: JSON data sent from the terminal

[0771] What happens: The server executes the following SQL query: INSERT INTO users (hobby, location) VALUES ('Gardening', 'Tokyo')

[0772] Data processing and calculation: Convert JSON data into SQL statements and save them in the database.

[0773] Output: User information stored in the database

[0774] Step 4:

[0775] The server analyzes the user data

[0776] Input: User information stored in the database

[0777] What it does: The server runs a Python script to analyze user behavior data using a machine learning model (e.g., TensorFlow).

[0778] Data processing and computation: Data analysis using machine learning models.

[0779] Output: Analysis results (user interests, behavioral patterns)

[0780] Step 5:

[0781] The server generates recommended content

[0782] Input: Analysis results

[0783] What it does: The server lists content, potential friends, and events based on the user's interests.

[0784] Data processing and calculation: The analysis results are compared with the information in the database to create the optimal recommendation list.

[0785] Output: Recommendation list

[0786] Step 6:

[0787] The server sends the recommendation list to the device.

[0788] Input: Recommendation list

[0789] What happens: The server generates the following JSON data and sends it to the device: {"recommendations": ["health-related articles", "online fitness classes"]}

[0790] Data processing and calculation: Convert the recommendation list into JSON format.

[0791] Output: JSON data sent to the device

[0792] Step 7:

[0793] The device displays the UI

[0794] Input: Profile information, recommendation list

[0795] What it does: The device displays information on the main menu screen with large icons and fonts.

[0796] Data processing and calculation: None

[0797] Output: The UI that the user sees

[0798] Step 8:

[0799] The device recognizes your voice commands

[0800] Input: User's voice command

[0801] What it does: When a user says "Find friends," the device uses a voice recognition system (e.g., Google Speech-to-Text) to interpret the voice command.

[0802] Data processing and computation: Converting voice data into text.

[0803] Output: Text representation of voice commands

[0804] Step 9:

[0805] Your device will display the search results.

[0806] Input: Text form of voice command

[0807] What it does: Your device will display a list of potential "Find Friends" search results in capital letters.

[0808] Data processing and calculation: None

[0809] Output: Search results displayed in the UI

[0810] Step 10:

[0811] User views the event list

[0812] Input: Recommendation list

[0813] What happens: The user opens the Events section.

[0814] Data processing and calculation: None

[0815] Output: Event list

[0816] Step 11:

[0817] User chooses to attend the event

[0818] Input: Event list

[0819] Specific actions: The user selects "Craft Workshop" and presses the "Participate" button.

[0820] Data processing and calculation: None

[0821] Output: Join request

[0822] Step 12:

[0823] The device sends a join request to the server

[0824] Input: Join request

[0825] Specific operation: The device generates the following JSON data and sends it to the server: {"event": "Craft Workshop", "user": "F"}

[0826] Data processing and calculation: Convert the join request into JSON format.

[0827] Output: JSON data sent to the server

[0828] In this way, the entire system functions with the server, terminals, and users working together to promote social interaction, health management, and community participation among the elderly.

[0829] (Application example 1)

[0830] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0831] It has been difficult to effectively recommend content, friend candidates, and events that users are interested in on social networking platforms for seniors, as well as provide information about local food events. A user interface that is visually easy to operate is also required. To solve these challenges, a system is needed to support the dietary habits of seniors and promote social interaction.

[0832] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0833] In this invention, the server includes means for collecting and storing user data, means for applying an AI model to the collected user data and analyzing it, means for recommending content, friend candidates, and events based on the analysis results, means for recommending food items and delivery options, means for acquiring local food event information from an external data source, and means for storing the acquired food event information. This makes it possible to accurately recommend not only content, friend candidates, and events that interest elderly people, but also food items and local food events that interest them.

[0834] "User Data" refers to any data relating to a user, such as a user's profile information, behavioral data, and preference information.

[0835] "Means for storage" refers to a mechanism for storing collected user data in a database.

[0836] An "AI model" is a collection of algorithms that use artificial intelligence to analyze data and make predictions.

[0837] "Means of analysis" refers to the process of applying an AI model to collected user data to analyze and evaluate that data.

[0838] The "means for recommending content, friend candidates, and events" is a function for presenting content, friend candidates, and events that are suitable for the user based on the analysis results.

[0839] The "means for recommending food items and delivery options" is a function for presenting appropriate food items and delivery services to a user based on the user's preference data.

[0840] An "external data source" is a mechanism for collecting information from data providers outside the system.

[0841] "Local food event information" is information about food-related events held in a specific region.

[0842] An "intuitive user interface" is an easy-to-understand screen designed to allow users to operate it easily.

[0843] "Visual display means" refers to a mechanism for outputting information on the screen in a form that is easy for the user to understand.

[0844] "Server" means a centralized management system used to manage user data, perform analysis, and store results.

[0845] This invention realizes a system that provides a wide range of recommendations, including food items and food events, on a social networking platform for seniors.

[0846] Server-side implementation

[0847] 1. Collection and storage of user data

[0848] Overview: The server collects user profile information, behavioral data, and preference information and stores it in a database.

[0849] Software used: Database management system (DBMS)

[0850] Example: When a user enters their hobbies and location on their profile page, this information is sent to the server and automatically stored in a database.

[0851] 2. Data analysis and recommendation

[0852] Overview: The server applies an AI model to the collected data to analyze it, and based on the results, recommends the most suitable content, friend candidates, food items, and food events to the user.

[0853] Software used: Generative AI model algorithms, machine learning libraries (e.g., TensorFlow, PyTorch)

[0854] Example: If a user has frequently viewed "pizza" related content in the past, the server can analyze their behavioral patterns and recommend new pizza-related delivery options or local pizza festivals.

[0855] 3. Acquisition and provision of information on local food events

[0856] Overview: The server obtains local food event information from external data sources, stores it in a database, and recommends relevant events based on the user's location information.

[0857] Software used: External API (e.g., event information API)

[0858] Example: If the user lives in "Yokohama City", information about pizza festivals held in the area is retrieved from an external data source and recommended to the user.

[0859] Terminal side embodiment

[0860] 1. Intuitive User Interface (UI)

[0861] Overview: The device provides an intuitive UI that is easy for seniors to operate, and includes features such as voice control and uppercase fonts.

[0862] Hardware used: smartphone, head-mounted display (HMD)

[0863] Example: If a user uses a voice command to say, "Tell me what pizzas are best," the device recognizes the voice command and displays related food items and events in a large font.

[0864] 2. Visual display of local food event information

[0865] Overview: Visually displays recommendation information and event information from the server.

[0866] Software used: GUI library (e.g. React Native, Flutter)

[0867] Example: A list of local food events is displayed, and users can select an event that interests them and view more information.

[0868] User-Side Embodiment

[0869] 1. Update your profile

[0870] Overview: A user updates his or her profile information and sends the data to a server via the device.

[0871] Example: When a user adds a new hobby to their profile, "making pizza," this information is immediately sent to the server and stored.

[0872] 2. Participating in food events

[0873] Overview: Users use their devices to access local food events and register to participate.

[0874] Example: A user selects an event of interest from a list of local food events displayed within the platform and presses the "Attend" button.

[0875] These efforts will help promote eating habits and social interactions among the elderly and increase the convenience of the platform.

[0876] Example prompt sentence:

[0877] If a user enters "I like Twice Cooked Pork" in their profile, the server will recommend "food items and related events related to Twice Cooked Pork."

[0878] For example, if the user sets the location information as "Yokohama City," information about the Twice Cooked Pork Festival will be provided.

[0879] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0880] Step 1:

[0881] The server collects and stores user data

[0882] Input: Users input profile information and preference information

[0883] Processing: The server receives this information and stores it in a database. Specifically, it analyzes the data sent from the smartphone or head-mounted display (HMD) and stores it in the database in an appropriate format.

[0884] Output: User information stored in the database

[0885] Step 2:

[0886] The server applies an AI model to the collected data and analyzes it.

[0887] Input: User data stored in the database

[0888] Processing: The server analyzes the data using machine learning libraries (e.g., TensorFlow, PyTorch) to understand user preferences and behavioral patterns. An AI model analyzes the data and identifies recommendations.

[0889] Output: Analysis results, list of recommended targets

[0890] Step 3:

[0891] The server uses the analysis to recommend content, friend suggestions, events, food items, and delivery options.

[0892] Input: Analysis results, list of recommended targets

[0893] Processing: The server categorizes recommendations into categories and selects the most suitable content, friend suggestions, events, food items, and delivery options for the user, using a generative AI model algorithm.

[0894] Output: Recommended content for the user, friend suggestions, events, food items, and delivery options

[0895] Step 4:

[0896] The server retrieves local food event information from an external data source.

[0897] Input: User's location

[0898] Processing: The server uses an external API (e.g., an event information API) to obtain local food event information based on the user's location. Specifically, the server sends an API request and temporarily stores the obtained data.

[0899] Output: Local food event information

[0900] Step 5:

[0901] The server stores the food event information it has obtained.

[0902] Input: Retrieved local food event information

[0903] Processing: The server formats the food event information and stores it in a database, allowing for fast responses to user requests.

[0904] Output: Food event information stored in the database

[0905] Step 6:

[0906] The device accepts input from the user through the user interface (UI) and sends a request to the server.

[0907] Input: Voice commands and touch input from the user

[0908] Processing: The device receives the user's input, converts it into an appropriate format, and sends a request to the server. Specifically, it uses voice recognition technology to convert voice commands into text data.

[0909] Output: Request data to the server

[0910] Step 7:

[0911] The terminal displays the response from the server to the user.

[0912] Input: Response data from the server

[0913] Processing: The device visually displays the response data received from the server, specifically by displaying the information in large font on the smartphone or HMD screen so that the user can easily understand it.

[0914] Output: Information displayed to the user

[0915] Step 8:

[0916] The device visually displays information about local food events.

[0917] Input: Local food event information obtained from the server

[0918] Processing: The device displays food event information in a visually easy-to-understand format, such as a list or card format, allowing the user to view the details.

[0919] Output: Visual display of local food event information

[0920] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0921] The present invention relates to a system for providing more personalized services on a social networking platform for seniors by combining the collection and storage of user data, data analysis using AI models, recommendations of content, friend candidates, and events, as well as an emotion engine that recognizes user emotions. Specific embodiments of this system are described below.

[0922] Server-side implementation

[0923] 1. User Data Collection and Storage:

[0924] Overview: The server collects profile information, behavioral data, and emotional information of elderly users and stores them in a database.

[0925] Example: User A enters his / her hobbies and location on a profile page, and the information is sent from the device to the server and stored in the server's database. In addition, the user's emotional reactions while watching a video are also recorded as emotional data.

[0926] 2. Data analysis and recommendations:

[0927] Overview: The server applies AI models to the collected data, analyzes the user's behavioral patterns and emotional data, and based on the results, recommends the most suitable content, friend candidates, and events to the user.

[0928] Example: If User B has frequently viewed health-related content in the past and the emotion engine detects a positive reaction to it, the server can recommend new health articles or online fitness classes.

[0929] 3. Acquisition and provision of local event information:

[0930] Overview: The server obtains local event and community information from external data sources, stores it in a database, and recommends related events based on the user's location and emotion data.

[0931] Example: If user C is interested in crafts and has positive feelings about that interest, the server will recommend information about craft workshops taking place in the area.

[0932] Terminal side embodiment

[0933] 1. User Interface (UI):

[0934] Overview: The device provides an intuitive UI that is easy for seniors to operate, including features such as voice control and uppercase fonts.

[0935] Example: If user D uses a voice command to say "Find friends," the device will recognize the voice command, launch the friend search function, and display the search results in capital letters.

[0936] 2. Emotion Engine Operation:

[0937] Overview: The device is equipped with an emotion engine that analyzes the user's emotions in real time from their facial expressions and tone of voice, and sends the data to a server.

[0938] Example: While user E is watching a video, the device analyzes the user's facial expressions with a camera and transmits emotional data to the server in real time.

[0939] User-Side Embodiment

[0940] 1. Update your profile:

[0941] Overview: Users update their profile information and emotional information and send it to the server via their device.

[0942] Example: User F adds "gardening" as a new hobby, and emotion data about the hobby is also sent to the server.

[0943] 2. Participate in community events:

[0944] Summary: Users can easily access local events through their devices and select recommended events using emotional data when registering to attend.

[0945] Example: User G selects an event of interest from a list of local events displayed within the platform, and presses the "Participate" button based on the emotional data for that event.

[0946] In this way, by combining the emotion engine, the system of the present invention provides a more personalized user experience and improves the quality of life for the elderly. The server, terminal, and user work together to provide optimal services tailored to the user's emotional state.

[0947] The processing flow will be explained below.

[0948] User Data Collection and Storage Process Steps

[0949] Step 1:

[0950] The user enters profile information.

[0951] User: Enter their hobbies, location, health information, etc. on their profile page.

[0952] Example: User A enters "gardening" as a hobby.

[0953] Step 2:

[0954] The entered data is sent to the server.

[0955] Terminal: Sends input information to the server in real time.

[0956] Example: The terminal sends user A's hobby information to the server as a data packet.

[0957] Step 3:

[0958] Save the data to a database.

[0959] Server: Validates the received data and stores it in the database.

[0960] Example: The server adds the hobby "gardening" to User A's profile.

[0961] Processing steps for collecting and storing emotion data

[0962] Step 1:

[0963] Start your emotion engine.

[0964] Device: Activate the emotion engine when watching videos or browsing content.

[0965] Example: When a user starts watching a fitness video, the device's emotion engine is activated.

[0966] Step 2:

[0967] Emotion data is analyzed and sent to the server.

[0968] Device: Analyzes the user's facial expressions and tone of voice in real time and sends the results to the server.

[0969] Example: If a user smiles while watching a video, send that positive emotion data to the server.

[0970] Step 3:

[0971] Emotion data is stored in a database.

[0972] Server: Validates the received emotion data and stores it in a database.

[0973] Example: The server integrates user emotion data into User A's profile.

[0974] Data analysis and recommendation processing steps

[0975] Step 1:

[0976] Periodically read the stored data.

[0977] Server: Periodically reads user data and emotion data from the database.

[0978] Example: The server reads user A's behavioral and emotional data every day.

[0979] Step 2:

[0980] Apply AI models to analyze the data.

[0981] Server: Analyzes the stored data using AI models to analyze user trends.

[0982] Example: The server analyzes which genres of content User A has frequently viewed in the past month and which content he has responded positively to.

[0983] Step 3:

[0984] Generate recommendations based on the analysis results.

[0985] Server: Based on the analysis results, it generates the most suitable content, friend suggestions, and events for the user.

[0986] Example: The server recommends to user A new articles about "gardening" and other users with the same hobby.

[0987] Step 4:

[0988] Prepare the recommendations in the form of a notice.

[0989] Server: Formats the recommendation information and prepares it to be sent to the device as a notification message.

[0990] Example: A server creates a notification that says "Join an online group for gardening enthusiasts."

[0991] Processing steps for obtaining and providing local event information

[0992] Step 1:

[0993] Retrieve local event information from an external data source.

[0994] Server: Collects local event information from external APIs and databases.

[0995] Example: The server retrieves the events calendar from the API of a local cultural center.

[0996] Step 2:

[0997] Save the retrieved data in the database.

[0998] Server: Validates the acquired event information and stores it in an internal database.

[0999] Example: The server stores the obtained information about the craft workshop in a database.

[1000] Step 3:

[1001] Recommend events based on user location and emotion data.

[1002] Server: Obtains user location and emotion data and recommends relevant events.

[1003] Example: Notify user B of a craft workshop near where they currently live. If the user has a strong interest in crafts, the event will be recommended even more strongly.

[1004] User interface provision and operation processing steps

[1005] Step 1:

[1006] The user logs in and sees the main dashboard.

[1007] Terminal: Receives login information, authenticates the user, and displays the main dashboard.

[1008] Example: When User C logs in, the dashboard displays recent notifications and recommended content.

[1009] Step 2:

[1010] Accepts interaction from the user.

[1011] Device: Accepts actions such as button presses, swipes, and voice commands.

[1012] Example: User D enters the voice command "Find friends."

[1013] Step 3:

[1014] Send the request to the server.

[1015] Terminal: Sends appropriate requests to the server based on user actions.

[1016] Example: The device analyzes user D's voice command and sends a friend search request to the server.

[1017] Step 4:

[1018] Displays the response from the server.

[1019] Terminal: Receives the response from the server and displays it to the user.

[1020] Example: The device displays the search results from the server on the screen and provides new friend candidates to User D.

[1021] In this way, the platform of the present invention provides a high-level user experience that includes emotional data by linking the terminal, server, and user.

[1022] Example 2

[1023] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1024] Current social networking platforms for seniors lack personalized services, making it difficult for them to find content, friends, and events that suit them. Another issue is that few services utilize emotional data, making it difficult to provide appropriate recommendations that match current emotions.

[1025] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for collecting and storing user data, a means for applying a generative AI model to the collected user data and analyzing it, a means for recommending content, friend candidates, and events based on the analysis results, a means for collecting and storing user emotion data, and a means including an emotion analysis engine for performing analysis based on the emotion data. This makes it possible to provide personalized services by utilizing the user's behavioral data and emotion data.

[1026] "User Data" refers to a user's profile information, behavioral data, location information, and any other data related to the use of the Platform.

[1027] A "generative AI model" is a model that uses machine learning algorithms to analyze data and generate new information and predictions based on the learning results.

[1028] An "emotion analysis engine" refers to software or hardware functionality that analyzes emotional data from a user's facial expressions, voice, etc. in real time.

[1029] "Content" refers to articles, videos, music, images, and any other information provided to users.

[1030] "Friend candidates" refers to data for recommending other users who may be of interest or related to the user.

[1031] "Event" refers to a workshop, seminar, sporting event, or other gathering held in the community.

[1032] An "intuitive user interface" refers to a simple and easy-to-understand screen layout and operating procedures designed to be easy for seniors to operate.

[1033] "Voice operation" refers to a function that allows the user to perform various operations on the system using voice commands.

[1034] "Capital font" refers to a font that is displayed in a larger-than-normal character size to improve legibility.

[1035] "External data sources" refers to online services or APIs that provide various data that can be accessed from outside the system.

[1036] "Location information" refers to geographic data that indicates a user's current location.

[1037] MODE FOR CARRYING OUT THE INVENTION

[1038] The present invention relates to a system for providing more personalized services on a social networking platform for seniors by combining the collection and storage of user data, data analysis using a generative AI model, recommendations of content, friend candidates, and events, as well as a sentiment analysis engine that recognizes user emotions. Specific embodiments of this system are described below.

[1039] Server-side implementation

[1040] User Data Collection and Storage:

[1041] The server obtains the profile information, behavioral data, and emotional information of the elderly user and stores this information in a database. For example, when a user enters their hobbies or location on the profile page, the device sends this information to the server as an HTTP POST request. The server then saves the received data in a database (e.g., MySQL) using an INSERT statement. If the saving process is successful, the server returns a status indicating that the save was successful to the device.

[1042] Data analysis and recommendations:

[1043] The server applies a generative AI model to the collected data and analyzes the user's behavioral patterns and emotional data. Based on the results, it recommends optimal content, friend candidates, and events to the user. For example, the server periodically retrieves user data from the database using a SELECT statement and transfers that data to the AI ​​analysis server. This analysis is performed using Python and TensorFlow. Based on the analysis results, recommended items are generated and cached in the database. These recommendations are displayed the next time the user logs in.

[1044] Acquiring and providing local event information:

[1045] The server retrieves local event information from external data sources and recommends relevant events to users based on location and emotion data. For example, the server periodically calls an external API (e.g., Eventbrite API) to retrieve local event information, extracts the necessary information, and stores it in a database. When a user logs in, the server picks up and recommends events held in the surrounding area.

[1046] Terminal side embodiment

[1047] User Interface (UI):

[1048] The device provides an intuitive UI that seniors can easily operate, including features such as voice control and capital font. For example, when a user says the voice command "Find friends," the device converts the speech to text using the Google Cloud Speech-to-Text API, creates a search query based on that text, and sends it to the server. The device then displays the search results from the server in capital font.

[1049] Sentiment Analysis Engine:

[1050] The device is equipped with an emotion analysis engine that analyzes emotions in real time from the user's facial expressions and tone of voice and sends the data to a server. For example, while the user is watching a video, the device's camera captures facial expressions in real time and sends the analysis data to a server. This analysis uses OpenCV and deep learning libraries (e.g., OpenFace).

[1051] User-Side Embodiment

[1052] Update your profile:

[1053] Users update their profile information and emotional information and send it to the server via their devices. For example, if a user adds "gardening" as a new hobby, the changes are sent to the server as an HTTP POST request, and the server updates the database.

[1054] Participate in community events:

[1055] Users can easily access local events through their devices and register to participate. Emotional data can also be used to select recommended events. For example, when a user selects an event they are interested in from the event list and presses the "Participate" button, the device sends the information to the server, which then stores the participation information in a database.

[1056] Prompt Sentence Examples

[1057] "Suggest new health articles or online fitness classes to users who have previously expressed positive feelings about health-related content."

[1058] This system allows the server, device, and user to work together to utilize user behavioral and emotional data, providing a personalized user experience and improving the quality of life for the elderly.

[1059] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1060] Program processing flow

[1061] Server Action:

[1062] Step 1:

[1063] The server receives user data sent from the device. The input includes user profile information and behavioral data. Specifically, the server receives an HTTP POST request and stores the data in temporary memory.

[1064] Step 2:

[1065] The server saves the received user data in a database. MySQL is used as the database. For data processing, the received data is converted into an INSERT statement and inserted into the database. As output, a status indicating successful saving is generated and returned to the terminal.

[1066] Step 3:

[1067] The server periodically retrieves user data from the database. The input includes user profile information and behavioral data stored in the database. It executes SELECT statements to retrieve data from the database and loads the retrieved data into memory.

[1068] Step 4:

[1069] The server inputs the acquired user data into the generative AI model and performs data analysis. Specifically, it runs the generative AI model using Python and TensorFlow. Data calculations involve clustering and pattern recognition of user behavior patterns and emotional data. The output is the analysis results.

[1070] Step 5:

[1071] The server generates recommended items based on the analysis results. The input includes the analysis results of the AI ​​model. The generated recommended items are cached in a database. The output is the cached recommended items.

[1072] Step 6:

[1073] The server retrieves local event information from an external data source. Specifically, it calls an external API (e.g., Eventbrite API) to retrieve local event information. The input includes the API request. The retrieved event information is parsed in JSON format and the necessary fields are extracted. The extracted event information is obtained as output.

[1074] Step 7:

[1075] The server saves the acquired event information in the database. Specifically, it creates an INSERT statement based on the extracted event information and inserts it into the database. As an output, it generates a status indicating that the save was successful.

[1076] Step 8:

[1077] The server recommends local events based on the user's location and emotion data. The input includes the user's location and emotion data. Based on this, the server searches for appropriate events and lists them as recommended items. The output is a list of related events.

[1078] Terminal handling:

[1079] Step 1:

[1080] The device accepts input from the user, including voice commands and touch gestures. Specific operations include capturing voice data for voice input and recognizing screen gestures for touch input.

[1081] Step 2:

[1082] The device processes the received user input and sends a request to the server. The input includes the user input data. Specifically, in the case of voice input, the device converts the voice to text using the Google Cloud Speech-to-Text API, generates an HTTP request, and sends it to the server. The output is a request to the server.

[1083] Step 3:

[1084] The terminal receives the response from the server. Specifically, it receives the HTTP response and analyzes its contents. The input includes the response data from the server. The output is the analyzed data.

[1085] Step 4:

[1086] The terminal displays the server's response to the user. Specific display operations include displaying text in uppercase font and outputting voice using speech synthesis. The output allows the user to confirm the information visually or audibly.

[1087] Step 5:

[1088] The device collects the user's facial expressions and voice tone in real time. Specifically, it captures facial expression data with a camera and records voice data with a microphone. The input includes the user's real-time facial expressions and voice data.

[1089] Step 6:

[1090] The device inputs the collected facial expression and voice data into an emotion analysis engine for analysis. Libraries such as OpenCV and OpenFace are used for the analysis. Data calculations involve facial expression recognition and voice tone analysis. The output is analyzed emotion data.

[1091] Step 7:

[1092] The device sends the emotion data obtained as a result of the analysis to the server. Specifically, it generates an HTTP POST request and sends it to the server. The input includes the analyzed emotion data. The output is the completion of the emotion data transfer to the server.

[1093] User Action:

[1094] Step 1:

[1095] A user enters or updates profile information, including new hobbies, location, etc. The user enters the data on the device's profile editing page.

[1096] Step 2:

[1097] The user sends profile information to the server through the device. After checking the input data, the user presses the send button to generate an HTTP POST request, which the device then sends to the server. As an output, a send request to the server is generated.

[1098] Step 3:

[1099] The user operates the device to browse the local event list. Specifically, the user opens the event list page on the device and selects an event they are interested in. The input includes the user's selection data.

[1100] Step 4:

[1101] A user registers to participate in an event. After selecting an event, the user presses the "Participate" button to generate a request to send information about the selected event to the server. The output is a participation request sent to the server.

[1102] Step 5:

[1103] The user waits for a response from the server confirming their participation in the event. Specifically, the user receives the response from the server using the notification function on the device. The input includes the response data from the server. The output is a notification confirming their participation.

[1104] (Application example 2)

[1105] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1106] Conventional social networking platforms for seniors have difficulty providing personalized services that fully reflect users' emotions and preferences. Furthermore, conventional technologies are insufficient when it comes to providing a user interface that is easy for seniors to use and recommending local event information. In particular, there is a demand for technology that can analyze seniors' emotions and recommend the most appropriate content and events based on that analysis.

[1107] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1108] In this invention, the server includes means for collecting and storing user data, means for applying a generative AI model to the collected user data and analyzing it, means for recommending content, friend candidates, and events based on the analysis results, means for operating an emotion engine that analyzes emotions from the user's facial expressions and tone of voice in real time, and means for transmitting emotion data to the server, thereby enabling the provision of personalized services based on the user's emotional state.

[1109] A "communication platform for the elderly" is an online system aimed primarily at elderly people for the purpose of mutual interaction.

[1110] "User data" refers to various information about an individual, including a user's profile information, behavioral data, emotional data, and the like.

[1111] A "generative AI model" is an artificial intelligence algorithm used to analyze user behavioral and emotional data.

[1112] "Means for analysis" refers to the function of applying a generative AI model to collected user data and performing analysis.

[1113] "Content" includes information or entertainment elements such as articles, videos, images, etc. provided to users.

[1114] "Friend candidates" refer to other users with whom the user may potentially build new friendships.

[1115] "Event" means any gathering or activity, held online or offline, in which users can participate.

[1116] The "Emotion Engine" is a system that analyzes emotions in real time from a user's facial expressions and tone of voice.

[1117] "Emotion data" is information about the user's emotional state obtained by the emotion engine.

[1118] "Server" means the primary computer system that collects, stores, and analyzes user data and uses the generative AI model.

[1119] "External Data Sources" refers to information sources outside the Platform that provide information such as local event information.

[1120] "Location information" is data indicating the user's current location and movement information.

[1121] An "intuitive user interface" is a graphical or audio-based interface designed to be easy for users to operate.

[1122] "Recommendation" refers to the activity of suggesting specific content, potential friends, events, etc. to the user based on the analysis results.

[1123] "Real-time" refers to immediate processing and feedback without delay.

[1124] This system is designed to provide a communication platform for the elderly and recommend personalized services by analyzing users' emotional data. The system operates in cooperation with the server, terminals, and users.

[1125] Server-side implementation

[1126] User Data Collection and Storage:

[1127] The server collects user profile information, behavioral data, and emotional data and stores them in a database. Specifically, the profile information and behavioral history entered by the user into the device, as well as the emotional data analyzed by the emotion engine, are sent to the server and stored there.

[1128] Data analysis and recommendations:

[1129] The server applies generative AI models to the collected data to analyze the user's behavioral patterns and emotional data. Based on the analysis results, the server can recommend content, friend suggestions, and local events that are most suitable for the user. For example, if a user prefers health-related content, the server can recommend new health articles and online fitness classes.

[1130] Retrieving information from external data sources:

[1131] The server retrieves necessary data from external data sources to obtain local event and community information and stores it in a database, which enables recommendations of local events based on the user's location and emotion data.

[1132] Terminal side embodiment

[1133] User Interface (UI):

[1134] The device offers an intuitive UI that seniors can easily operate, including voice control, large font, and touch control. For example, if a user uses the voice command "Find friends," the device recognizes the command and launches the friend search function.

[1135] Emotion Engine Operation:

[1136] The device has an emotion engine built in that analyzes the user's facial expressions and tone of voice to generate emotion data. This data is sent to a server in real time. For example, while the user is watching a video, the camera analyzes the user's facial expressions and sends the emotion data to the server.

[1137] User-Side Embodiment

[1138] Update your profile:

[1139] A user can update his / her profile information and emotional data and send it to the server through the terminal, for example, by adding a new hobby to his / her profile and sending the emotional data related to that hobby to the server.

[1140] Participate in the event:

[1141] Users can easily access local events through their devices and register to participate. Related events are recommended using emotion data, making it easier for users to participate in events that interest them. For example, a user who is interested in handicrafts will be recommended information about handicraft workshops being held in their area and can register to participate in those events.

[1142] Hardware and Software Use

[1143] Hardware:

[1144] Server: The main server for running the database and AI models

[1145] Camera: Analyzes the user's facial expressions

[1146] Microphone: Analyzes the user's voice tone

[1147] Smartphones and head-mounted displays (HMDs)

[1148] software:

[1149] Python, TensorFlow, OpenCV: Implementing a sentiment analysis engine and AI model

[1150] API server: Acquires and stores user data, receives emotion data

[1151] User Interface: UI that supports voice recognition and touch operation

[1152] Examples and prompts

[1153] example:

[1154] Example: When a user uses a virtual community assistant in an app installed on their smartphone, the camera analyzes the user's facial expressions and recommends products and events that the user is interested in in real time.

[1155] Prompt for the generative AI model:

[1156] "Analyze the reactions of users to products they are looking at while shopping and recommend other products related to the products that showed positive emotions."

[1157] In this way, the system can improve the quality of life for the elderly and provide more personalized services.

[1158] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1159] Step 1:

[1160] Entering and saving user data (terminal and server)

[1161] Users input their profile information and behavioral data through their devices. The devices then send this data to the server, which then stores it in a database. For example, a user might add a new hobby. The information entered includes profile information, behavioral history, and emotional data, and all of this data is managed centrally by the server.

[1162] Step 2:

[1163] Acquiring emotion data (device)

[1164] The device uses an emotion engine to obtain emotion data in real time from the user's facial expressions and voice tone. The emotion engine uses a camera and microphone to analyze the user's emotions and generate the results as data. The input in this step is the user's facial expressions and voice tone, and the output is the analyzed emotion data.

[1165] Step 3:

[1166] Sending emotional data (device and server)

[1167] The device transmits the acquired emotional data to a server in real time. The server receives this data and stores it in a database along with the user profile and behavioral data. Continuous acquisition of emotional data enables more precise analysis. The input is emotional data, and the output is transmission to the server and storage in the database.

[1168] Step 4:

[1169] Data analysis and information recommendation (server)

[1170] The server applies a generative AI model to the collected user data, analyzing behavioral patterns and emotional data. The analysis results in data that can be used to recommend content, friend candidates, and local events that are best suited to the user. The input for this step is the stored data, and the output is a recommendation list. Specifically, new health articles and online fitness classes will be recommended to users who prefer health-related content.

[1171] Step 5:

[1172] Obtaining information from external data sources (server)

[1173] The server retrieves the necessary data from external data sources to obtain local event and community information. The retrieved data is stored in a database and becomes the basis for recommendations based on the user's location and emotion data. The input is external data, and the output is stored in the database.

[1174] Step 6:

[1175] User Interface (Terminal)

[1176] The device provides an intuitive user interface designed for seniors. Users can easily operate it using voice commands, touch operations, and capital fonts. For example, if you use the voice command "Find friends," the device recognizes the command and activates the friend search function. In this step, the input is a voice command or touch operation, and the output is the activation of the corresponding function.

[1177] Step 7:

[1178] Event and content recommendations (device)

[1179] The content and events desired by the user are displayed on the device. Based on the recommendation list sent from the server, the most suitable content and event information for the user is displayed. The input is the recommendation data from the server, and the output is the display on the user interface. Specifically, for a user who prefers health-related information, related new articles and events are displayed.

[1180] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1181] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1182] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1183] [Third embodiment]

[1184] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1185] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1186] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1187] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1188] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1189] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1190] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1191] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1192] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1193] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1194] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1195] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1196] The present invention relates to a social networking platform for seniors, and provides a means for collecting and storing user data, a means for analyzing the data by applying an AI model, a means for recommending content, friend candidates, and events based on the analysis results, and a means for acquiring and storing local event information and community information. A specific embodiment of this system is described below.

[1197] Server-side implementation

[1198] 1. User Data Collection and Storage:

[1199] Overview: The server collects profile information, behavioral data, and health information of elderly users and stores it in a database.

[1200] Example: When user A enters his / her hobbies and location on the profile page, this information is sent from the device to the server and stored in the server's database.

[1201] 2. Data analysis and recommendations:

[1202] Overview: The server applies an AI model to the collected data to analyze it, and based on the results, recommends the most suitable content, friend candidates, and events to the user.

[1203] Example: If User B has frequently viewed health-related content in the past, the server can analyze their behavioral patterns and recommend new health articles or online fitness classes.

[1204] 3. Acquisition and provision of local event information:

[1205] Overview: The server obtains local event and community information from external data sources, stores it in a database, and recommends related events based on the user's location information.

[1206] Example: If user C lives in a particular area, information about craft workshops for seniors held in that area is retrieved from an external data source and recommended to user C.

[1207] Terminal side embodiment

[1208] 1. User Interface (UI):

[1209] Overview: The device provides an intuitive UI that is easy for seniors to operate, and includes features such as voice control and uppercase fonts.

[1210] Example: If user D uses a voice command to say "Find friends," the device will recognize the voice command, launch the friend search function, and display the search results in capital letters.

[1211] User-Side Embodiment

[1212] 1. Update your profile:

[1213] Overview: Users update their profile information and send that data to a server via their device.

[1214] Example: User E adds "gardening" as a new hobby. This information is immediately sent to the server and saved.

[1215] 2. Participate in community events:

[1216] Overview: Users can easily access and register for local events through their devices.

[1217] Example: User F selects an event he or she is interested in from a list of local events displayed within the platform and presses the "Participate" button. The request to participate is sent to the server, and the event participation is completed.

[1218] In this way, the present invention effectively promotes social interaction, health management, and community participation for the elderly through collaboration between servers, terminals, and users, thereby resolving the problems of traditional social networking platforms and improving the quality of life for the elderly.

[1219] The processing flow will be explained below.

[1220] User Data Collection and Storage Process Steps

[1221] Step 1:

[1222] The user enters profile information.

[1223] User: Enters their hobbies, location, health information, etc. on their profile page.

[1224] Example: User A enters "gardening" as a hobby.

[1225] Step 2:

[1226] The entered data is sent to the server.

[1227] Terminal: Sends input information to the server in real time.

[1228] Example: The terminal sends user A's hobby information to the server as a data packet.

[1229] Step 3:

[1230] Save the data to a database.

[1231] Server: Validates the received data and stores it in the database.

[1232] Example: The server adds the hobby "gardening" to User A's profile.

[1233] Data analysis and recommendation processing steps

[1234] Step 1:

[1235] Periodically read the stored data.

[1236] Server: Periodically reads user data from the database.

[1237] Example: The server reads user A's behavior data once a day.

[1238] Step 2:

[1239] Apply AI models to analyze the data.

[1240] Server: Analyzes the stored data using AI models to analyze user trends.

[1241] Example: The server analyzes which genre of content User A has frequently viewed in the past month.

[1242] Step 3:

[1243] Generate recommendations based on the analysis results.

[1244] Server: Based on the analysis results, it generates the most suitable content, friend suggestions, and events for the user.

[1245] Example: The server recommends to user A new articles about "gardening" and other users with the same hobby.

[1246] Step 4:

[1247] Prepare the recommendations in the form of a notice.

[1248] Server: Formats the recommendation information and prepares it to be sent to the device as a notification message.

[1249] Example: A server creates a notification that says "Join an online group for gardening enthusiasts."

[1250] Processing steps for obtaining and providing local event information

[1251] Step 1:

[1252] Retrieve local event information from an external data source.

[1253] Server: Collects local event information from external APIs and databases.

[1254] Example: The server retrieves the events calendar from the API of a local cultural center.

[1255] Step 2:

[1256] Save the retrieved data in the database.

[1257] Server: Validates the acquired event information and stores it in an internal database.

[1258] Example: The server stores the obtained information about the craft workshop in a database.

[1259] Step 3:

[1260] Recommend events based on the user's location.

[1261] Server: Obtains the user's location and recommends relevant events.

[1262] Example: User B is notified of a craft workshop near where he currently lives.

[1263] User interface provision and operation processing steps

[1264] Step 1:

[1265] The user logs in and sees the main dashboard.

[1266] Terminal: Receives login information, authenticates the user, and displays the main dashboard.

[1267] Example: When User C logs in, the dashboard displays recent notifications and recommended content.

[1268] Step 2:

[1269] Accepts interaction from the user.

[1270] Device: Accepts actions such as button presses, swipes, and voice commands.

[1271] Example: User D enters the voice command "Find friends."

[1272] Step 3:

[1273] Send the request to the server.

[1274] Terminal: Sends appropriate requests to the server based on user actions.

[1275] Example: The device analyzes user D's voice command and sends a friend search request to the server.

[1276] Step 4:

[1277] Displays the response from the server.

[1278] Terminal: Receives the response from the server and displays it to the user.

[1279] Example: The device displays the search results from the server on the screen and provides new friend candidates to User D.

[1280] In this way, the platform of the present invention provides a high-level user experience through cooperation between users, terminals, and servers.

[1281] Example 1

[1282] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1283] When seniors use social networking platforms, they face challenges such as difficulty in operation, social isolation, and digital divides. Furthermore, it is difficult to efficiently recommend content, friend candidates, and local event information specifically for seniors. Therefore, there is a need to provide a platform that seniors can easily operate and that allows them to receive appropriate information and content.

[1284] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1285] In this invention, the server includes means for collecting and storing user data, means for applying a machine learning model to the collected user data and analyzing it, means for recommending content, friend candidates, and events based on the analysis results, means for acquiring and storing local event information and community information from external data sources, a terminal for providing a user interface, means for a user to update their own profile information and send the updated information to the server via the terminal, means for providing a user interface that the user can easily operate using voice commands and uppercase fonts, means for transmitting data collected by the terminal and user-input data to the server, means for displaying responses from the server to the user, means for recommending related local events based on the user's location information, and means for accepting and transmitting requests to participate in local events to the server. This allows elderly people to easily operate the device and receive information and content that meets their individual needs.

[1286] "User Data" refers to information about an individual user, such as the elderly user's profile information, behavioral data, and health information.

[1287] A "machine learning model" refers to an artificial intelligence algorithm that analyzes data and makes predictions or classifications based on the results.

[1288] "Content" refers to any information or material provided on the Platform, including articles, videos, and event information.

[1289] "Friend Suggestions" refers to other users on the social networking platform who are recommended to you based on your interests and behavioral data.

[1290] "Event" means a local or online gathering or activity that users can participate in.

[1291] "External data sources" refers to sources for obtaining data from outside the platform, such as information providers or APIs outside the platform.

[1292] "User interface" refers to the screens and operating means that allow users to interact with the system, and includes those that are particularly easy for seniors to use.

[1293] "Terminal" refers to the device through which a user accesses the platform, such as a smartphone or tablet.

[1294] "Voice command" refers to a voice input method in which a user gives instructions to a system using voice.

[1295] "Server" refers to a remote computer system that stores data, analyzes data, generates recommendations, etc.

[1296] "Location information" is information that indicates the user's geographical location and is used to recommend related local events.

[1297] "Local Events" refers to events such as workshops and gatherings that take place in a specific geographic area.

[1298] A "participation request" refers to a request by a user to indicate their intention to participate in a particular event and to convey that information to the system.

[1299] "Storage" refers to the act of keeping collected data or information in a database or storage.

[1300] The present invention relates to a social networking platform for seniors, and includes means for collecting and storing user data, means for analyzing the data by applying a machine learning model, means for recommending content, friend candidates, and events based on the analysis results, means for acquiring and storing local event information and community information from external data sources, a terminal for providing a user interface, and means for providing a user interface that can be easily operated by users using voice commands and uppercase fonts. Specific embodiments are described below.

[1301] Server-side implementation

[1302] The server performs the following process.

[1303] 1. Collection and storage of user data

[1304] Hardware: Servers, data servers (e.g. Dell PowerEdge)

[1305] Software: Database management system (e.g., MySQL), collection program (e.g., written in Python)

[1306] The server collects the user's profile information, behavioral data, and health information and stores them in a database. For example, when a user enters their hobbies and location on the profile page, this information is sent from the device to the server and stored in the server's database.

[1307] 2. Data analysis and recommendation

[1308] Hardware: Server, GPU (e.g. NVIDIA Tesla)

[1309] Software: Machine learning libraries (e.g., TensorFlow), data analysis programs (e.g., written in Python)

[1310] The server applies machine learning models to the collected data and analyzes it, and based on the results, recommends the most suitable content, friend candidates, and events to the user. For example, if a user has frequently viewed health-related content in the past, the server can analyze their behavioral patterns and recommend new health articles or online fitness classes.

[1311] 3. Acquisition and provision of local event information

[1312] Hardware: Server

[1313] Software: External API client (e.g. written in Python), database management system (e.g. MySQL)

[1314] The server obtains local event and community information from external data sources, stores it in a database, and recommends related events based on the user's location information. For example, if a user lives in a specific area, the server obtains information about handicraft workshops for seniors held in that area from an external data source and recommends them to the user.

[1315] Terminal side embodiment

[1316] The terminal performs the following processing.

[1317] 1. User Interface (UI)

[1318] Hardware: Tablets, smartphones (e.g. iPad)

[1319] Software: UI frameworks (e.g., Flutter), speech recognition systems (e.g., Google Speech-to-Text)

[1320] The device provides an intuitive UI that is easy for seniors to operate. For example, if a user uses a voice command to say "Find friends," the device recognizes the voice command and activates the friend search function. The device also displays search results in capital letters.

[1321] User-Side Embodiment

[1322] The user performs the following process.

[1323] 1. Update your profile

[1324] Users update their profile information and send the data to the server via their devices. For example, a user adds "gardening" as a new hobby. This information is immediately sent to the server and stored.

[1325] 2. Participate in community events

[1326] Users can easily access local events through their devices and register to participate. For example, users select an event they are interested in from a list of local events displayed within the platform and press the "Participate" button. Their participation request is then sent to the server, completing their participation in the event.

[1327] Example of a generative AI model prompt

[1328] Update Profile function description prompt:

[1329] Please explain the profile update function of a social networking platform for seniors. Please provide a detailed description of the specific processes that are performed from the perspectives of the server, device, and user, including both hardware and software. Include specific examples.

[1330] Event participation function description generation prompt:

[1331] Please explain the event participation function of a social networking platform for seniors. Please provide a detailed description of the specific processes that are performed from the perspectives of the server, device, and user, including both hardware and software. Include specific examples.

[1332] In this way, the entire system functions with the server, terminals, and users working together to promote social interaction, health management, and community participation among the elderly.

[1333] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1334] Step 1:

[1335] User enters profile information

[1336] Input: A user accesses a profile page on their device and enters personal information such as hobbies and location.

[1337] Specific operation: The user enters "Hobby: Gardening" and "Location: Tokyo" and presses the "Save" button.

[1338] Data processing and calculation: None

[1339] Output: Input data (hobbies, location)

[1340] Step 2:

[1341] The device sends the data to the server

[1342] Input: Profile information entered by the user

[1343] Specific behavior: The device generates the following JSON data and sends it to the server: {"hobby": "gardening", "location": "Tokyo"}

[1344] Data processing and calculation: Convert data into JSON format.

[1345] Output: JSON data sent to the server

[1346] Step 3:

[1347] The server saves the data to a database

[1348] Input: JSON data sent from the terminal

[1349] What happens: The server executes the following SQL query: INSERT INTO users (hobby, location) VALUES ('Gardening', 'Tokyo')

[1350] Data processing and calculation: Convert JSON data into SQL statements and save them in the database.

[1351] Output: User information stored in the database

[1352] Step 4:

[1353] The server analyzes the user data

[1354] Input: User information stored in the database

[1355] What it does: The server runs a Python script to analyze user behavior data using a machine learning model (e.g., TensorFlow).

[1356] Data processing and computation: Data analysis using machine learning models.

[1357] Output: Analysis results (user interests, behavioral patterns)

[1358] Step 5:

[1359] The server generates recommended content

[1360] Input: Analysis results

[1361] What it does: The server lists content, potential friends, and events based on the user's interests.

[1362] Data processing and calculation: The analysis results are compared with the information in the database to create the optimal recommendation list.

[1363] Output: Recommendation list

[1364] Step 6:

[1365] The server sends the recommendation list to the device.

[1366] Input: Recommendation list

[1367] What happens: The server generates the following JSON data and sends it to the device: {"recommendations": ["health-related articles", "online fitness classes"]}

[1368] Data processing and calculation: Convert the recommendation list into JSON format.

[1369] Output: JSON data sent to the device

[1370] Step 7:

[1371] The device displays the UI

[1372] Input: Profile information, recommendation list

[1373] What it does: The device displays information on the main menu screen with large icons and fonts.

[1374] Data processing and calculation: None

[1375] Output: The UI that the user sees

[1376] Step 8:

[1377] The device recognizes your voice commands

[1378] Input: User's voice command

[1379] What it does: When a user says "Find friends," the device uses a voice recognition system (e.g., Google Speech-to-Text) to interpret the voice command.

[1380] Data processing and computation: Converting voice data into text.

[1381] Output: Text representation of voice commands

[1382] Step 9:

[1383] Your device will display the search results.

[1384] Input: Text form of voice command

[1385] What it does: Your device will display a list of potential "Find Friends" search results in capital letters.

[1386] Data processing and calculation: None

[1387] Output: Search results displayed in the UI

[1388] Step 10:

[1389] User views the event list

[1390] Input: Recommendation list

[1391] What happens: The user opens the Events section.

[1392] Data processing and calculation: None

[1393] Output: Event list

[1394] Step 11:

[1395] User chooses to attend the event

[1396] Input: Event list

[1397] Specific actions: The user selects "Craft Workshop" and presses the "Participate" button.

[1398] Data processing and calculation: None

[1399] Output: Join request

[1400] Step 12:

[1401] The device sends a join request to the server

[1402] Input: Join request

[1403] Specific operation: The device generates the following JSON data and sends it to the server: {"event": "Craft Workshop", "user": "F"}

[1404] Data processing and calculation: Convert the join request into JSON format.

[1405] Output: JSON data sent to the server

[1406] In this way, the entire system functions with the server, terminals, and users working together to promote social interaction, health management, and community participation among the elderly.

[1407] (Application example 1)

[1408] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1409] It has been difficult to effectively recommend content, friend candidates, and events that users are interested in on social networking platforms for seniors, as well as provide information about local food events. A user interface that is visually easy to operate is also required. To solve these challenges, a system is needed to support the dietary habits of seniors and promote social interaction.

[1410] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1411] In this invention, the server includes means for collecting and storing user data, means for applying an AI model to the collected user data and analyzing it, means for recommending content, friend candidates, and events based on the analysis results, means for recommending food items and delivery options, means for acquiring local food event information from an external data source, and means for storing the acquired food event information. This makes it possible to accurately recommend not only content, friend candidates, and events that interest elderly people, but also food items and local food events that interest them.

[1412] "User Data" refers to any data relating to a user, such as a user's profile information, behavioral data, and preference information.

[1413] "Means for storage" refers to a mechanism for storing collected user data in a database.

[1414] An "AI model" is a collection of algorithms that use artificial intelligence to analyze data and make predictions.

[1415] "Means of analysis" refers to the process of applying an AI model to collected user data to analyze and evaluate that data.

[1416] The "means for recommending content, friend candidates, and events" is a function for presenting content, friend candidates, and events that are suitable for the user based on the analysis results.

[1417] The "means for recommending food items and delivery options" is a function for presenting appropriate food items and delivery services to a user based on the user's preference data.

[1418] An "external data source" is a mechanism for collecting information from data providers outside the system.

[1419] "Local food event information" is information about food-related events held in a specific region.

[1420] An "intuitive user interface" is an easy-to-understand screen designed to allow users to operate it easily.

[1421] "Visual display means" refers to a mechanism for outputting information on the screen in a form that is easy for the user to understand.

[1422] "Server" means a centralized management system used to manage user data, perform analysis, and store results.

[1423] This invention realizes a system that provides a wide range of recommendations, including food items and food events, on a social networking platform for seniors.

[1424] Server-side implementation

[1425] 1. Collection and storage of user data

[1426] Overview: The server collects user profile information, behavioral data, and preference information and stores it in a database.

[1427] Software used: Database management system (DBMS)

[1428] Example: When a user enters their hobbies and location on their profile page, this information is sent to the server and automatically stored in a database.

[1429] 2. Data analysis and recommendation

[1430] Overview: The server applies an AI model to the collected data to analyze it, and based on the results, recommends the most suitable content, friend candidates, food items, and food events to the user.

[1431] Software used: Generative AI model algorithms, machine learning libraries (e.g., TensorFlow, PyTorch)

[1432] Example: If a user has frequently viewed "pizza" related content in the past, the server can analyze their behavioral patterns and recommend new pizza-related delivery options or local pizza festivals.

[1433] 3. Acquisition and provision of information on local food events

[1434] Overview: The server obtains local food event information from external data sources, stores it in a database, and recommends relevant events based on the user's location information.

[1435] Software used: External API (e.g., event information API)

[1436] Example: If the user lives in "Yokohama City", information about pizza festivals held in the area is retrieved from an external data source and recommended to the user.

[1437] Terminal side embodiment

[1438] 1. Intuitive User Interface (UI)

[1439] Overview: The device provides an intuitive UI that is easy for seniors to operate, and includes features such as voice control and uppercase fonts.

[1440] Hardware used: smartphone, head-mounted display (HMD)

[1441] Example: If a user uses a voice command to say, "Tell me what pizzas are best," the device recognizes the voice command and displays related food items and events in a large font.

[1442] 2. Visual display of local food event information

[1443] Overview: Visually displays recommendation information and event information from the server.

[1444] Software used: GUI library (e.g. React Native, Flutter)

[1445] Example: A list of local food events is displayed, and users can select an event that interests them and view more information.

[1446] User-Side Embodiment

[1447] 1. Update your profile

[1448] Overview: A user updates his or her profile information and sends the data to a server via the device.

[1449] Example: When a user adds a new hobby to their profile, "making pizza," this information is immediately sent to the server and stored.

[1450] 2. Participating in food events

[1451] Overview: Users use their devices to access local food events and register to participate.

[1452] Example: A user selects an event of interest from a list of local food events displayed within the platform and presses the "Attend" button.

[1453] These efforts will help promote eating habits and social interactions among the elderly and increase the convenience of the platform.

[1454] Example prompt sentence:

[1455] If a user enters "I like Twice Cooked Pork" in their profile, the server will recommend "food items and related events related to Twice Cooked Pork."

[1456] For example, if the user sets the location information as "Yokohama City," information about the Twice Cooked Pork Festival will be provided.

[1457] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1458] Step 1:

[1459] The server collects and stores user data

[1460] Input: Users input profile information and preference information

[1461] Processing: The server receives this information and stores it in a database. Specifically, it analyzes the data sent from the smartphone or head-mounted display (HMD) and stores it in the database in an appropriate format.

[1462] Output: User information stored in the database

[1463] Step 2:

[1464] The server applies an AI model to the collected data and analyzes it.

[1465] Input: User data stored in the database

[1466] Processing: The server analyzes the data using machine learning libraries (e.g., TensorFlow, PyTorch) to understand user preferences and behavioral patterns. An AI model analyzes the data and identifies recommendations.

[1467] Output: Analysis results, list of recommended targets

[1468] Step 3:

[1469] The server uses the analysis to recommend content, friend suggestions, events, food items, and delivery options.

[1470] Input: Analysis results, list of recommended targets

[1471] Processing: The server categorizes recommendations into categories and selects the most suitable content, friend suggestions, events, food items, and delivery options for the user, using a generative AI model algorithm.

[1472] Output: Recommended content for the user, friend suggestions, events, food items, and delivery options

[1473] Step 4:

[1474] The server retrieves local food event information from an external data source.

[1475] Input: User's location

[1476] Processing: The server uses an external API (e.g., an event information API) to obtain local food event information based on the user's location. Specifically, the server sends an API request and temporarily stores the obtained data.

[1477] Output: Local food event information

[1478] Step 5:

[1479] The server stores the food event information it has obtained.

[1480] Input: Retrieved local food event information

[1481] Processing: The server formats the food event information and stores it in a database, allowing for fast responses to user requests.

[1482] Output: Food event information stored in the database

[1483] Step 6:

[1484] The device accepts input from the user through the user interface (UI) and sends a request to the server.

[1485] Input: Voice commands and touch input from the user

[1486] Processing: The device receives the user's input, converts it into an appropriate format, and sends a request to the server. Specifically, it uses voice recognition technology to convert voice commands into text data.

[1487] Output: Request data to the server

[1488] Step 7:

[1489] The terminal displays the response from the server to the user.

[1490] Input: Response data from the server

[1491] Processing: The device visually displays the response data received from the server, specifically by displaying the information in large font on the smartphone or HMD screen so that the user can easily understand it.

[1492] Output: Information displayed to the user

[1493] Step 8:

[1494] The device visually displays information about local food events.

[1495] Input: Local food event information obtained from the server

[1496] Processing: The device displays food event information in a visually easy-to-understand format, such as a list or card format, allowing the user to view the details.

[1497] Output: Visual display of local food event information

[1498] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1499] The present invention relates to a system for providing more personalized services on a social networking platform for seniors by combining the collection and storage of user data, data analysis using AI models, recommendations of content, friend candidates, and events, as well as an emotion engine that recognizes user emotions. Specific embodiments of this system are described below.

[1500] Server-side implementation

[1501] 1. User Data Collection and Storage:

[1502] Overview: The server collects profile information, behavioral data, and emotional information of elderly users and stores them in a database.

[1503] Example: User A enters his / her hobbies and location on a profile page, and the information is sent from the device to the server and stored in the server's database. In addition, the user's emotional reactions while watching a video are also recorded as emotional data.

[1504] 2. Data analysis and recommendations:

[1505] Overview: The server applies AI models to the collected data, analyzes the user's behavioral patterns and emotional data, and based on the results, recommends the most suitable content, friend candidates, and events to the user.

[1506] Example: If User B has frequently viewed health-related content in the past and the emotion engine detects a positive reaction to it, the server can recommend new health articles or online fitness classes.

[1507] 3. Acquisition and provision of local event information:

[1508] Overview: The server obtains local event and community information from external data sources, stores it in a database, and recommends related events based on the user's location and emotion data.

[1509] Example: If user C is interested in crafts and has positive feelings about that interest, the server will recommend information about craft workshops taking place in the area.

[1510] Terminal side embodiment

[1511] 1. User Interface (UI):

[1512] Overview: The device provides an intuitive UI that is easy for seniors to operate, including features such as voice control and uppercase fonts.

[1513] Example: If user D uses a voice command to say "Find friends," the device will recognize the voice command, launch the friend search function, and display the search results in capital letters.

[1514] 2. Emotion Engine Operation:

[1515] Overview: The device is equipped with an emotion engine that analyzes the user's emotions in real time from their facial expressions and tone of voice, and sends the data to a server.

[1516] Example: While user E is watching a video, the device analyzes the user's facial expressions with a camera and transmits emotional data to the server in real time.

[1517] User-Side Embodiment

[1518] 1. Update your profile:

[1519] Overview: Users update their profile information and emotional information and send it to the server via their device.

[1520] Example: User F adds "gardening" as a new hobby, and emotion data about the hobby is also sent to the server.

[1521] 2. Participate in community events:

[1522] Summary: Users can easily access local events through their devices and select recommended events using emotional data when registering to attend.

[1523] Example: User G selects an event of interest from a list of local events displayed within the platform, and presses the "Participate" button based on the emotional data for that event.

[1524] In this way, by combining the emotion engine, the system of the present invention provides a more personalized user experience and improves the quality of life for the elderly. The server, terminal, and user work together to provide optimal services tailored to the user's emotional state.

[1525] The processing flow will be explained below.

[1526] User Data Collection and Storage Process Steps

[1527] Step 1:

[1528] The user enters profile information.

[1529] User: Enter their hobbies, location, health information, etc. on their profile page.

[1530] Example: User A enters "gardening" as a hobby.

[1531] Step 2:

[1532] The entered data is sent to the server.

[1533] Terminal: Sends input information to the server in real time.

[1534] Example: The terminal sends user A's hobby information to the server as a data packet.

[1535] Step 3:

[1536] Save the data to a database.

[1537] Server: Validates the received data and stores it in the database.

[1538] Example: The server adds the hobby "gardening" to User A's profile.

[1539] Processing steps for collecting and storing emotion data

[1540] Step 1:

[1541] Start your emotion engine.

[1542] Device: Activate the emotion engine when watching videos or browsing content.

[1543] Example: When a user starts watching a fitness video, the device's emotion engine is activated.

[1544] Step 2:

[1545] Emotion data is analyzed and sent to the server.

[1546] Device: Analyzes the user's facial expressions and tone of voice in real time and sends the results to the server.

[1547] Example: If a user smiles while watching a video, send that positive emotion data to the server.

[1548] Step 3:

[1549] Emotion data is stored in a database.

[1550] Server: Validates the received emotion data and stores it in a database.

[1551] Example: The server integrates user emotion data into User A's profile.

[1552] Data analysis and recommendation processing steps

[1553] Step 1:

[1554] Periodically read the stored data.

[1555] Server: Periodically reads user data and emotion data from the database.

[1556] Example: The server reads user A's behavioral and emotional data every day.

[1557] Step 2:

[1558] Apply AI models to analyze the data.

[1559] Server: Analyzes the stored data using AI models to analyze user trends.

[1560] Example: The server analyzes which genres of content User A has frequently viewed in the past month and which content he has responded positively to.

[1561] Step 3:

[1562] Generate recommendations based on the analysis results.

[1563] Server: Based on the analysis results, it generates the most suitable content, friend suggestions, and events for the user.

[1564] Example: The server recommends to user A new articles about "gardening" and other users with the same hobby.

[1565] Step 4:

[1566] Prepare the recommendations in the form of a notice.

[1567] Server: Formats the recommendation information and prepares it to be sent to the device as a notification message.

[1568] Example: A server creates a notification that says "Join an online group for gardening enthusiasts."

[1569] Processing steps for obtaining and providing local event information

[1570] Step 1:

[1571] Retrieve local event information from an external data source.

[1572] Server: Collects local event information from external APIs and databases.

[1573] Example: The server retrieves the events calendar from the API of a local cultural center.

[1574] Step 2:

[1575] Save the retrieved data in the database.

[1576] Server: Validates the acquired event information and stores it in an internal database.

[1577] Example: The server stores the obtained information about the craft workshop in a database.

[1578] Step 3:

[1579] Recommend events based on user location and emotion data.

[1580] Server: Obtains user location and emotion data and recommends relevant events.

[1581] Example: Notify user B of a craft workshop near where they currently live. If the user has a strong interest in crafts, the event will be recommended even more strongly.

[1582] User interface provision and operation processing steps

[1583] Step 1:

[1584] The user logs in and sees the main dashboard.

[1585] Terminal: Receives login information, authenticates the user, and displays the main dashboard.

[1586] Example: When User C logs in, the dashboard displays recent notifications and recommended content.

[1587] Step 2:

[1588] Accepts interaction from the user.

[1589] Device: Accepts actions such as button presses, swipes, and voice commands.

[1590] Example: User D enters the voice command "Find friends."

[1591] Step 3:

[1592] Send the request to the server.

[1593] Terminal: Sends appropriate requests to the server based on user actions.

[1594] Example: The device analyzes user D's voice command and sends a friend search request to the server.

[1595] Step 4:

[1596] Displays the response from the server.

[1597] Terminal: Receives the response from the server and displays it to the user.

[1598] Example: The device displays the search results from the server on the screen and provides new friend candidates to User D.

[1599] In this way, the platform of the present invention provides a high-level user experience that includes emotional data by linking the terminal, server, and user.

[1600] Example 2

[1601] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1602] Current social networking platforms for seniors lack personalized services, making it difficult for them to find content, friends, and events that suit them. Another issue is that few services utilize emotional data, making it difficult to provide appropriate recommendations that match current emotions.

[1603] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for collecting and storing user data, a means for applying a generative AI model to the collected user data and analyzing it, a means for recommending content, friend candidates, and events based on the analysis results, a means for collecting and storing user emotion data, and a means including an emotion analysis engine for performing analysis based on the emotion data. This makes it possible to provide personalized services by utilizing the user's behavioral data and emotion data.

[1604] "User Data" refers to a user's profile information, behavioral data, location information, and any other data related to the use of the Platform.

[1605] A "generative AI model" is a model that uses machine learning algorithms to analyze data and generate new information and predictions based on the learning results.

[1606] An "emotion analysis engine" refers to software or hardware functionality that analyzes emotional data from a user's facial expressions, voice, etc. in real time.

[1607] "Content" refers to articles, videos, music, images, and any other information provided to users.

[1608] "Friend candidates" refers to data for recommending other users who may be of interest or related to the user.

[1609] "Event" refers to a workshop, seminar, sporting event, or other gathering held in the community.

[1610] An "intuitive user interface" refers to a simple and easy-to-understand screen layout and operating procedures designed to be easy for seniors to operate.

[1611] "Voice operation" refers to a function that allows the user to perform various operations on the system using voice commands.

[1612] "Capital font" refers to a font that is displayed in a larger-than-normal character size to improve legibility.

[1613] "External data sources" refers to online services or APIs that provide various data that can be accessed from outside the system.

[1614] "Location information" refers to geographic data that indicates a user's current location.

[1615] MODE FOR CARRYING OUT THE INVENTION

[1616] The present invention relates to a system for providing more personalized services on a social networking platform for seniors by combining the collection and storage of user data, data analysis using a generative AI model, recommendations of content, friend candidates, and events, as well as a sentiment analysis engine that recognizes user emotions. Specific embodiments of this system are described below.

[1617] Server-side implementation

[1618] User Data Collection and Storage:

[1619] The server obtains the profile information, behavioral data, and emotional information of the elderly user and stores this information in a database. For example, when a user enters their hobbies or location on the profile page, the device sends this information to the server as an HTTP POST request. The server then saves the received data in a database (e.g., MySQL) using an INSERT statement. If the saving process is successful, the server returns a status indicating that the save was successful to the device.

[1620] Data analysis and recommendations:

[1621] The server applies a generative AI model to the collected data and analyzes the user's behavioral patterns and emotional data. Based on the results, it recommends optimal content, friend candidates, and events to the user. For example, the server periodically retrieves user data from the database using a SELECT statement and transfers that data to the AI ​​analysis server. This analysis is performed using Python and TensorFlow. Based on the analysis results, recommended items are generated and cached in the database. These recommendations are displayed the next time the user logs in.

[1622] Acquiring and providing local event information:

[1623] The server retrieves local event information from external data sources and recommends relevant events to users based on location and emotion data. For example, the server periodically calls an external API (e.g., Eventbrite API) to retrieve local event information, extracts the necessary information, and stores it in a database. When a user logs in, the server picks up and recommends events held in the surrounding area.

[1624] Terminal side embodiment

[1625] User Interface (UI):

[1626] The device provides an intuitive UI that seniors can easily operate, including features such as voice control and capital font. For example, when a user says the voice command "Find friends," the device converts the speech to text using the Google Cloud Speech-to-Text API, creates a search query based on that text, and sends it to the server. The device then displays the search results from the server in capital font.

[1627] Sentiment Analysis Engine:

[1628] The device is equipped with an emotion analysis engine that analyzes emotions in real time from the user's facial expressions and tone of voice and sends the data to a server. For example, while the user is watching a video, the device's camera captures facial expressions in real time and sends the analysis data to a server. This analysis uses OpenCV and deep learning libraries (e.g., OpenFace).

[1629] User-Side Embodiment

[1630] Update your profile:

[1631] Users update their profile information and emotional information and send it to the server via their devices. For example, if a user adds "gardening" as a new hobby, the changes are sent to the server as an HTTP POST request, and the server updates the database.

[1632] Participate in community events:

[1633] Users can easily access local events through their devices and register to participate. Emotional data can also be used to select recommended events. For example, when a user selects an event they are interested in from the event list and presses the "Participate" button, the device sends the information to the server, which then stores the participation information in a database.

[1634] Prompt Sentence Examples

[1635] "Suggest new health articles or online fitness classes to users who have previously expressed positive feelings about health-related content."

[1636] This system allows the server, device, and user to work together to utilize user behavioral and emotional data, providing a personalized user experience and improving the quality of life for the elderly.

[1637] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1638] Program processing flow

[1639] Server Action:

[1640] Step 1:

[1641] The server receives user data sent from the device. The input includes user profile information and behavioral data. Specifically, the server receives an HTTP POST request and stores the data in temporary memory.

[1642] Step 2:

[1643] The server saves the received user data in a database. MySQL is used as the database. For data processing, the received data is converted into an INSERT statement and inserted into the database. As output, a status indicating successful saving is generated and returned to the terminal.

[1644] Step 3:

[1645] The server periodically retrieves user data from the database. The input includes user profile information and behavioral data stored in the database. It executes SELECT statements to retrieve data from the database and loads the retrieved data into memory.

[1646] Step 4:

[1647] The server inputs the acquired user data into the generative AI model and performs data analysis. Specifically, it runs the generative AI model using Python and TensorFlow. Data calculations involve clustering and pattern recognition of user behavior patterns and emotional data. The output is the analysis results.

[1648] Step 5:

[1649] The server generates recommended items based on the analysis results. The input includes the analysis results of the AI ​​model. The generated recommended items are cached in a database. The output is the cached recommended items.

[1650] Step 6:

[1651] The server retrieves local event information from an external data source. Specifically, it calls an external API (e.g., Eventbrite API) to retrieve local event information. The input includes the API request. The retrieved event information is parsed in JSON format and the necessary fields are extracted. The extracted event information is obtained as output.

[1652] Step 7:

[1653] The server saves the acquired event information in the database. Specifically, it creates an INSERT statement based on the extracted event information and inserts it into the database. As an output, it generates a status indicating that the save was successful.

[1654] Step 8:

[1655] The server recommends local events based on the user's location and emotion data. The input includes the user's location and emotion data. Based on this, the server searches for appropriate events and lists them as recommended items. The output is a list of related events.

[1656] Terminal handling:

[1657] Step 1:

[1658] The device accepts input from the user, including voice commands and touch gestures. Specific operations include capturing voice data for voice input and recognizing screen gestures for touch input.

[1659] Step 2:

[1660] The device processes the received user input and sends a request to the server. The input includes the user input data. Specifically, in the case of voice input, the device converts the voice to text using the Google Cloud Speech-to-Text API, generates an HTTP request, and sends it to the server. The output is a request to the server.

[1661] Step 3:

[1662] The terminal receives the response from the server. Specifically, it receives the HTTP response and analyzes its contents. The input includes the response data from the server. The output is the analyzed data.

[1663] Step 4:

[1664] The terminal displays the server's response to the user. Specific display operations include displaying text in uppercase font and outputting voice using speech synthesis. The output allows the user to confirm the information visually or audibly.

[1665] Step 5:

[1666] The device collects the user's facial expressions and voice tone in real time. Specifically, it captures facial expression data with a camera and records voice data with a microphone. The input includes the user's real-time facial expressions and voice data.

[1667] Step 6:

[1668] The device inputs the collected facial expression and voice data into an emotion analysis engine for analysis. Libraries such as OpenCV and OpenFace are used for the analysis. Data calculations involve facial expression recognition and voice tone analysis. The output is analyzed emotion data.

[1669] Step 7:

[1670] The device sends the emotion data obtained as a result of the analysis to the server. Specifically, it generates an HTTP POST request and sends it to the server. The input includes the analyzed emotion data. The output is the completion of the emotion data transfer to the server.

[1671] User Action:

[1672] Step 1:

[1673] A user enters or updates profile information, including new hobbies, location, etc. The user enters the data on the device's profile editing page.

[1674] Step 2:

[1675] The user sends profile information to the server through the device. After checking the input data, the user presses the send button to generate an HTTP POST request, which the device then sends to the server. As an output, a send request to the server is generated.

[1676] Step 3:

[1677] The user operates the device to browse the local event list. Specifically, the user opens the event list page on the device and selects an event they are interested in. The input includes the user's selection data.

[1678] Step 4:

[1679] A user registers to participate in an event. After selecting an event, the user presses the "Participate" button to generate a request to send information about the selected event to the server. The output is a participation request sent to the server.

[1680] Step 5:

[1681] The user waits for a response from the server confirming their participation in the event. Specifically, the user receives the response from the server using the notification function on the device. The input includes the response data from the server. The output is a notification confirming their participation.

[1682] (Application example 2)

[1683] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1684] Conventional social networking platforms for seniors have difficulty providing personalized services that fully reflect users' emotions and preferences. Furthermore, conventional technologies are insufficient when it comes to providing a user interface that is easy for seniors to use and recommending local event information. In particular, there is a demand for technology that can analyze seniors' emotions and recommend the most appropriate content and events based on that analysis.

[1685] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1686] In this invention, the server includes means for collecting and storing user data, means for applying a generative AI model to the collected user data and analyzing it, means for recommending content, friend candidates, and events based on the analysis results, means for operating an emotion engine that analyzes emotions from the user's facial expressions and tone of voice in real time, and means for transmitting emotion data to the server, thereby enabling the provision of personalized services based on the user's emotional state.

[1687] A "communication platform for the elderly" is an online system aimed primarily at elderly people for the purpose of mutual interaction.

[1688] "User data" refers to various information about an individual, including a user's profile information, behavioral data, emotional data, and the like.

[1689] A "generative AI model" is an artificial intelligence algorithm used to analyze user behavioral and emotional data.

[1690] "Means for analysis" refers to the function of applying a generative AI model to collected user data and performing analysis.

[1691] "Content" includes information or entertainment elements such as articles, videos, images, etc. provided to users.

[1692] "Friend candidates" refer to other users with whom the user may potentially build new friendships.

[1693] "Event" means any gathering or activity, held online or offline, in which users can participate.

[1694] The "Emotion Engine" is a system that analyzes emotions in real time from a user's facial expressions and tone of voice.

[1695] "Emotion data" is information about the user's emotional state obtained by the emotion engine.

[1696] "Server" means the primary computer system that collects, stores, and analyzes user data and uses the generative AI model.

[1697] "External Data Sources" refers to information sources outside the Platform that provide information such as local event information.

[1698] "Location information" is data indicating the user's current location and movement information.

[1699] An "intuitive user interface" is a graphical or audio-based interface designed to be easy for users to operate.

[1700] "Recommendation" refers to the activity of suggesting specific content, potential friends, events, etc. to the user based on the analysis results.

[1701] "Real-time" refers to immediate processing and feedback without delay.

[1702] This system is designed to provide a communication platform for the elderly and recommend personalized services by analyzing users' emotional data. The system operates in cooperation with the server, terminals, and users.

[1703] Server-side implementation

[1704] User Data Collection and Storage:

[1705] The server collects user profile information, behavioral data, and emotional data and stores them in a database. Specifically, the profile information and behavioral history entered by the user into the device, as well as the emotional data analyzed by the emotion engine, are sent to the server and stored there.

[1706] Data analysis and recommendations:

[1707] The server applies generative AI models to the collected data to analyze the user's behavioral patterns and emotional data. Based on the analysis results, the server can recommend content, friend suggestions, and local events that are most suitable for the user. For example, if a user prefers health-related content, the server can recommend new health articles and online fitness classes.

[1708] Retrieving information from external data sources:

[1709] The server retrieves necessary data from external data sources to obtain local event and community information and stores it in a database, which enables recommendations of local events based on the user's location and emotion data.

[1710] Terminal side embodiment

[1711] User Interface (UI):

[1712] The device offers an intuitive UI that seniors can easily operate, including voice control, large font, and touch control. For example, if a user uses the voice command "Find friends," the device recognizes the command and launches the friend search function.

[1713] Emotion Engine Operation:

[1714] The device has an emotion engine built in that analyzes the user's facial expressions and tone of voice to generate emotion data. This data is sent to a server in real time. For example, while the user is watching a video, the camera analyzes the user's facial expressions and sends the emotion data to the server.

[1715] User-Side Embodiment

[1716] Update your profile:

[1717] A user can update his / her profile information and emotional data and send it to the server through the terminal, for example, by adding a new hobby to his / her profile and sending the emotional data related to that hobby to the server.

[1718] Participate in the event:

[1719] Users can easily access local events through their devices and register to participate. Related events are recommended using emotion data, making it easier for users to participate in events that interest them. For example, a user who is interested in handicrafts will be recommended information about handicraft workshops being held in their area and can register to participate in those events.

[1720] Hardware and Software Use

[1721] Hardware:

[1722] Server: The main server for running the database and AI models

[1723] Camera: Analyzes the user's facial expressions

[1724] Microphone: Analyzes the user's voice tone

[1725] Smartphones and head-mounted displays (HMDs)

[1726] software:

[1727] Python, TensorFlow, OpenCV: Implementing a sentiment analysis engine and AI model

[1728] API server: Acquires and stores user data, receives emotion data

[1729] User Interface: UI that supports voice recognition and touch operation

[1730] Examples and prompts

[1731] example:

[1732] Example: When a user uses a virtual community assistant in an app installed on their smartphone, the camera analyzes the user's facial expressions and recommends products and events that the user is interested in in real time.

[1733] Prompt for the generative AI model:

[1734] "Analyze the reactions of users to products they are looking at while shopping and recommend other products related to the products that showed positive emotions."

[1735] In this way, the system can improve the quality of life for the elderly and provide more personalized services.

[1736] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1737] Step 1:

[1738] Entering and saving user data (terminal and server)

[1739] Users input their profile information and behavioral data through their devices. The devices then send this data to the server, which then stores it in a database. For example, a user might add a new hobby. The information entered includes profile information, behavioral history, and emotional data, and all of this data is managed centrally by the server.

[1740] Step 2:

[1741] Acquiring emotion data (device)

[1742] The device uses an emotion engine to obtain emotion data in real time from the user's facial expressions and voice tone. The emotion engine uses a camera and microphone to analyze the user's emotions and generate the results as data. The input in this step is the user's facial expressions and voice tone, and the output is the analyzed emotion data.

[1743] Step 3:

[1744] Sending emotional data (device and server)

[1745] The device transmits the acquired emotional data to a server in real time. The server receives this data and stores it in a database along with the user profile and behavioral data. Continuous acquisition of emotional data enables more precise analysis. The input is emotional data, and the output is transmission to the server and storage in the database.

[1746] Step 4:

[1747] Data analysis and information recommendation (server)

[1748] The server applies a generative AI model to the collected user data, analyzing behavioral patterns and emotional data. The analysis results in data that can be used to recommend content, friend candidates, and local events that are best suited to the user. The input for this step is the stored data, and the output is a recommendation list. Specifically, new health articles and online fitness classes will be recommended to users who prefer health-related content.

[1749] Step 5:

[1750] Obtaining information from external data sources (server)

[1751] The server retrieves the necessary data from external data sources to obtain local event and community information. The retrieved data is stored in a database and becomes the basis for recommendations based on the user's location and emotion data. The input is external data, and the output is stored in the database.

[1752] Step 6:

[1753] User Interface (Terminal)

[1754] The device provides an intuitive user interface designed for seniors. Users can easily operate it using voice commands, touch operations, and capital fonts. For example, if you use the voice command "Find friends," the device recognizes the command and activates the friend search function. In this step, the input is a voice command or touch operation, and the output is the activation of the corresponding function.

[1755] Step 7:

[1756] Event and content recommendations (device)

[1757] The content and events desired by the user are displayed on the device. Based on the recommendation list sent from the server, the most suitable content and event information for the user is displayed. The input is the recommendation data from the server, and the output is the display on the user interface. Specifically, for a user who prefers health-related information, related new articles and events are displayed.

[1758] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1759] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1760] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1761] [Fourth embodiment]

[1762] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1763] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1764] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1765] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1766] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1767] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1768] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1769] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1770] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1771] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1772] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1773] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1774] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1775] The present invention relates to a social networking platform for seniors, and provides a means for collecting and storing user data, a means for analyzing the data by applying an AI model, a means for recommending content, friend candidates, and events based on the analysis results, and a means for acquiring and storing local event information and community information. A specific embodiment of this system is described below.

[1776] Server-side implementation

[1777] 1. User Data Collection and Storage:

[1778] Overview: The server collects profile information, behavioral data, and health information of elderly users and stores it in a database.

[1779] Example: When user A enters his / her hobbies and location on the profile page, this information is sent from the device to the server and stored in the server's database.

[1780] 2. Data analysis and recommendations:

[1781] Overview: The server applies an AI model to the collected data to analyze it, and based on the results, recommends the most suitable content, friend candidates, and events to the user.

[1782] Example: If User B has frequently viewed health-related content in the past, the server can analyze their behavioral patterns and recommend new health articles or online fitness classes.

[1783] 3. Acquisition and provision of local event information:

[1784] Overview: The server obtains local event and community information from external data sources, stores it in a database, and recommends related events based on the user's location information.

[1785] Example: If user C lives in a particular area, information about craft workshops for seniors held in that area is retrieved from an external data source and recommended to user C.

[1786] Terminal side embodiment

[1787] 1. User Interface (UI):

[1788] Overview: The device provides an intuitive UI that is easy for seniors to operate, and includes features such as voice control and uppercase fonts.

[1789] Example: If user D uses a voice command to say "Find friends," the device will recognize the voice command, launch the friend search function, and display the search results in capital letters.

[1790] User-Side Embodiment

[1791] 1. Update your profile:

[1792] Overview: Users update their profile information and send that data to a server via their device.

[1793] Example: User E adds "gardening" as a new hobby. This information is immediately sent to the server and saved.

[1794] 2. Participate in community events:

[1795] Overview: Users can easily access and register for local events through their devices.

[1796] Example: User F selects an event he or she is interested in from a list of local events displayed within the platform and presses the "Participate" button. The request to participate is sent to the server, and the event participation is completed.

[1797] In this way, the present invention effectively promotes social interaction, health management, and community participation for the elderly through collaboration between servers, terminals, and users, thereby resolving the problems of traditional social networking platforms and improving the quality of life for the elderly.

[1798] The processing flow will be explained below.

[1799] User Data Collection and Storage Process Steps

[1800] Step 1:

[1801] The user enters profile information.

[1802] User: Enters their hobbies, location, health information, etc. on their profile page.

[1803] Example: User A enters "gardening" as a hobby.

[1804] Step 2:

[1805] The entered data is sent to the server.

[1806] Terminal: Sends input information to the server in real time.

[1807] Example: The terminal sends user A's hobby information to the server as a data packet.

[1808] Step 3:

[1809] Save the data to a database.

[1810] Server: Validates the received data and stores it in the database.

[1811] Example: The server adds the hobby "gardening" to User A's profile.

[1812] Data analysis and recommendation processing steps

[1813] Step 1:

[1814] Periodically read the stored data.

[1815] Server: Periodically reads user data from the database.

[1816] Example: The server reads user A's behavior data once a day.

[1817] Step 2:

[1818] Apply AI models to analyze the data.

[1819] Server: Analyzes the stored data using AI models to analyze user trends.

[1820] Example: The server analyzes which genre of content User A has frequently viewed in the past month.

[1821] Step 3:

[1822] Generate recommendations based on the analysis results.

[1823] Server: Based on the analysis results, it generates the most suitable content, friend suggestions, and events for the user.

[1824] Example: The server recommends to user A new articles about "gardening" and other users with the same hobby.

[1825] Step 4:

[1826] Prepare the recommendations in the form of a notice.

[1827] Server: Formats the recommendation information and prepares it to be sent to the device as a notification message.

[1828] Example: A server creates a notification that says "Join an online group for gardening enthusiasts."

[1829] Processing steps for obtaining and providing local event information

[1830] Step 1:

[1831] Retrieve local event information from an external data source.

[1832] Server: Collects local event information from external APIs and databases.

[1833] Example: The server retrieves the events calendar from the API of a local cultural center.

[1834] Step 2:

[1835] Save the retrieved data in the database.

[1836] Server: Validates the acquired event information and stores it in an internal database.

[1837] Example: The server stores the obtained information about the craft workshop in a database.

[1838] Step 3:

[1839] Recommend events based on the user's location.

[1840] Server: Obtains the user's location and recommends relevant events.

[1841] Example: User B is notified of a craft workshop near where he currently lives.

[1842] User interface provision and operation processing steps

[1843] Step 1:

[1844] The user logs in and sees the main dashboard.

[1845] Terminal: Receives login information, authenticates the user, and displays the main dashboard.

[1846] Example: When User C logs in, the dashboard displays recent notifications and recommended content.

[1847] Step 2:

[1848] Accepts interaction from the user.

[1849] Device: Accepts actions such as button presses, swipes, and voice commands.

[1850] Example: User D enters the voice command "Find friends."

[1851] Step 3:

[1852] Send the request to the server.

[1853] Terminal: Sends appropriate requests to the server based on user actions.

[1854] Example: The device analyzes user D's voice command and sends a friend search request to the server.

[1855] Step 4:

[1856] Displays the response from the server.

[1857] Terminal: Receives the response from the server and displays it to the user.

[1858] Example: The device displays the search results from the server on the screen and provides new friend candidates to User D.

[1859] In this way, the platform of the present invention provides a high-level user experience through cooperation between users, terminals, and servers.

[1860] Example 1

[1861] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1862] When seniors use social networking platforms, they face challenges such as difficulty in operation, social isolation, and digital divides. Furthermore, it is difficult to efficiently recommend content, friend candidates, and local event information specifically for seniors. Therefore, there is a need to provide a platform that seniors can easily operate and that allows them to receive appropriate information and content.

[1863] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1864] In this invention, the server includes means for collecting and storing user data, means for applying a machine learning model to the collected user data and analyzing it, means for recommending content, friend candidates, and events based on the analysis results, means for acquiring and storing local event information and community information from external data sources, a terminal for providing a user interface, means for a user to update their own profile information and send the updated information to the server via the terminal, means for providing a user interface that the user can easily operate using voice commands and uppercase fonts, means for transmitting data collected by the terminal and user-input data to the server, means for displaying responses from the server to the user, means for recommending related local events based on the user's location information, and means for accepting and transmitting requests to participate in local events to the server. This allows elderly people to easily operate the device and receive information and content that meets their individual needs.

[1865] "User Data" refers to information about an individual user, such as the elderly user's profile information, behavioral data, and health information.

[1866] A "machine learning model" refers to an artificial intelligence algorithm that analyzes data and makes predictions or classifications based on the results.

[1867] "Content" refers to any information or material provided on the Platform, including articles, videos, and event information.

[1868] "Friend Suggestions" refers to other users on the social networking platform who are recommended to you based on your interests and behavioral data.

[1869] "Event" means a local or online gathering or activity that users can participate in.

[1870] "External data sources" refers to sources for obtaining data from outside the platform, such as information providers or APIs outside the platform.

[1871] "User interface" refers to the screens and operating means that allow users to interact with the system, and includes those that are particularly easy for seniors to use.

[1872] "Terminal" refers to the device through which a user accesses the platform, such as a smartphone or tablet.

[1873] "Voice command" refers to a voice input method in which a user gives instructions to a system using voice.

[1874] "Server" refers to a remote computer system that stores data, analyzes data, generates recommendations, etc.

[1875] "Location information" is information that indicates the user's geographical location and is used to recommend related local events.

[1876] "Local Events" refers to events such as workshops and gatherings that take place in a specific geographic area.

[1877] A "participation request" refers to a request by a user to indicate their intention to participate in a particular event and to convey that information to the system.

[1878] "Storage" refers to the act of keeping collected data or information in a database or storage.

[1879] The present invention relates to a social networking platform for seniors, and includes means for collecting and storing user data, means for analyzing the data by applying a machine learning model, means for recommending content, friend candidates, and events based on the analysis results, means for acquiring and storing local event information and community information from external data sources, a terminal for providing a user interface, and means for providing a user interface that can be easily operated by users using voice commands and uppercase fonts. Specific embodiments are described below.

[1880] Server-side implementation

[1881] The server performs the following process.

[1882] 1. Collection and storage of user data

[1883] Hardware: Servers, data servers (e.g. Dell PowerEdge)

[1884] Software: Database management system (e.g., MySQL), collection program (e.g., written in Python)

[1885] The server collects the user's profile information, behavioral data, and health information and stores them in a database. For example, when a user enters their hobbies and location on the profile page, this information is sent from the device to the server and stored in the server's database.

[1886] 2. Data analysis and recommendation

[1887] Hardware: Server, GPU (e.g. NVIDIA Tesla)

[1888] Software: Machine learning libraries (e.g., TensorFlow), data analysis programs (e.g., written in Python)

[1889] The server applies machine learning models to the collected data and analyzes it, and based on the results, recommends the most suitable content, friend candidates, and events to the user. For example, if a user has frequently viewed health-related content in the past, the server can analyze their behavioral patterns and recommend new health articles or online fitness classes.

[1890] 3. Acquisition and provision of local event information

[1891] Hardware: Server

[1892] Software: External API client (e.g. written in Python), database management system (e.g. MySQL)

[1893] The server obtains local event and community information from external data sources, stores it in a database, and recommends related events based on the user's location information. For example, if a user lives in a specific area, the server obtains information about handicraft workshops for seniors held in that area from an external data source and recommends them to the user.

[1894] Terminal side embodiment

[1895] The terminal performs the following processing.

[1896] 1. User Interface (UI)

[1897] Hardware: Tablets, smartphones (e.g. iPad)

[1898] Software: UI frameworks (e.g., Flutter), speech recognition systems (e.g., Google Speech-to-Text)

[1899] The device provides an intuitive UI that is easy for seniors to operate. For example, if a user uses a voice command to say "Find friends," the device recognizes the voice command and activates the friend search function. The device also displays search results in capital letters.

[1900] User-Side Embodiment

[1901] The user performs the following process.

[1902] 1. Update your profile

[1903] Users update their profile information and send the data to the server via their devices. For example, a user adds "gardening" as a new hobby. This information is immediately sent to the server and stored.

[1904] 2. Participate in community events

[1905] Users can easily access local events through their devices and register to participate. For example, users select an event they are interested in from a list of local events displayed within the platform and press the "Participate" button. Their participation request is then sent to the server, completing their participation in the event.

[1906] Example of a generative AI model prompt

[1907] Update Profile function description prompt:

[1908] Please explain the profile update function of a social networking platform for seniors. Please provide a detailed description of the specific processes that are performed from the perspectives of the server, device, and user, including both hardware and software. Include specific examples.

[1909] Event participation function description generation prompt:

[1910] Please explain the event participation function of a social networking platform for seniors. Please provide a detailed description of the specific processes that are performed from the perspectives of the server, device, and user, including both hardware and software. Include specific examples.

[1911] In this way, the entire system functions with the server, terminals, and users working together to promote social interaction, health management, and community participation among the elderly.

[1912] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1913] Step 1:

[1914] User enters profile information

[1915] Input: A user accesses a profile page on their device and enters personal information such as hobbies and location.

[1916] Specific operation: The user enters "Hobby: Gardening" and "Location: Tokyo" and presses the "Save" button.

[1917] Data processing and calculation: None

[1918] Output: Input data (hobbies, location)

[1919] Step 2:

[1920] The device sends the data to the server

[1921] Input: Profile information entered by the user

[1922] Specific behavior: The device generates the following JSON data and sends it to the server: {"hobby": "gardening", "location": "Tokyo"}

[1923] Data processing and calculation: Convert data into JSON format.

[1924] Output: JSON data sent to the server

[1925] Step 3:

[1926] The server saves the data to a database

[1927] Input: JSON data sent from the terminal

[1928] What happens: The server executes the following SQL query: INSERT INTO users (hobby, location) VALUES ('Gardening', 'Tokyo')

[1929] Data processing and calculation: Convert JSON data into SQL statements and save them in the database.

[1930] Output: User information stored in the database

[1931] Step 4:

[1932] The server analyzes the user data

[1933] Input: User information stored in the database

[1934] What it does: The server runs a Python script to analyze user behavior data using a machine learning model (e.g., TensorFlow).

[1935] Data processing and computation: Data analysis using machine learning models.

[1936] Output: Analysis results (user interests, behavioral patterns)

[1937] Step 5:

[1938] The server generates recommended content

[1939] Input: Analysis results

[1940] What it does: The server lists content, potential friends, and events based on the user's interests.

[1941] Data processing and calculation: The analysis results are compared with the information in the database to create the optimal recommendation list.

[1942] Output: Recommendation list

[1943] Step 6:

[1944] The server sends the recommendation list to the device.

[1945] Input: Recommendation list

[1946] What happens: The server generates the following JSON data and sends it to the device: {"recommendations": ["health-related articles", "online fitness classes"]}

[1947] Data processing and calculation: Convert the recommendation list into JSON format.

[1948] Output: JSON data sent to the device

[1949] Step 7:

[1950] The device displays the UI

[1951] Input: Profile information, recommendation list

[1952] What it does: The device displays information on the main menu screen with large icons and fonts.

[1953] Data processing and calculation: None

[1954] Output: The UI that the user sees

[1955] Step 8:

[1956] The device recognizes your voice commands

[1957] Input: User's voice command

[1958] What it does: When a user says "Find friends," the device uses a voice recognition system (e.g., Google Speech-to-Text) to interpret the voice command.

[1959] Data processing and computation: Converting voice data into text.

[1960] Output: Text representation of voice commands

[1961] Step 9:

[1962] Your device will display the search results.

[1963] Input: Text form of voice command

[1964] What it does: Your device will display a list of potential "Find Friends" search results in capital letters.

[1965] Data processing and calculation: None

[1966] Output: Search results displayed in the UI

[1967] Step 10:

[1968] User views the event list

[1969] Input: Recommendation list

[1970] What happens: The user opens the Events section.

[1971] Data processing and calculation: None

[1972] Output: Event list

[1973] Step 11:

[1974] User chooses to attend the event

[1975] Input: Event list

[1976] Specific actions: The user selects "Craft Workshop" and presses the "Participate" button.

[1977] Data processing and calculation: None

[1978] Output: Join request

[1979] Step 12:

[1980] The device sends a join request to the server

[1981] Input: Join request

[1982] Specific operation: The device generates the following JSON data and sends it to the server: {"event": "Craft Workshop", "user": "F"}

[1983] Data processing and calculation: Convert the join request into JSON format.

[1984] Output: JSON data sent to the server

[1985] In this way, the entire system functions with the server, terminals, and users working together to promote social interaction, health management, and community participation among the elderly.

[1986] (Application example 1)

[1987] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1988] It has been difficult to effectively recommend content, friend candidates, and events that users are interested in on social networking platforms for seniors, as well as provide information about local food events. A user interface that is visually easy to operate is also required. To solve these challenges, a system is needed to support the dietary habits of seniors and promote social interaction.

[1989] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1990] In this invention, the server includes means for collecting and storing user data, means for applying an AI model to the collected user data and analyzing it, means for recommending content, friend candidates, and events based on the analysis results, means for recommending food items and delivery options, means for acquiring local food event information from an external data source, and means for storing the acquired food event information. This makes it possible to accurately recommend not only content, friend candidates, and events that interest elderly people, but also food items and local food events that interest them.

[1991] "User Data" refers to any data relating to a user, such as a user's profile information, behavioral data, and preference information.

[1992] "Means for storage" refers to a mechanism for storing collected user data in a database.

[1993] An "AI model" is a collection of algorithms that use artificial intelligence to analyze data and make predictions.

[1994] "Means of analysis" refers to the process of applying an AI model to collected user data to analyze and evaluate that data.

[1995] The "means for recommending content, friend candidates, and events" is a function for presenting content, friend candidates, and events that are suitable for the user based on the analysis results.

[1996] The "means for recommending food items and delivery options" is a function for presenting appropriate food items and delivery services to a user based on the user's preference data.

[1997] An "external data source" is a mechanism for collecting information from data providers outside the system.

[1998] "Local food event information" is information about food-related events held in a specific region.

[1999] An "intuitive user interface" is an easy-to-understand screen designed to allow users to operate it easily.

[2000] "Visual display means" refers to a mechanism for outputting information on the screen in a form that is easy for the user to understand.

[2001] "Server" means a centralized management system used to manage user data, perform analysis, and store results.

[2002] This invention realizes a system that provides a wide range of recommendations, including food items and food events, on a social networking platform for seniors.

[2003] Server-side implementation

[2004] 1. Collection and storage of user data

[2005] Overview: The server collects user profile information, behavioral data, and preference information and stores it in a database.

[2006] Software used: Database management system (DBMS)

[2007] Example: When a user enters their hobbies and location on their profile page, this information is sent to the server and automatically stored in a database.

[2008] 2. Data analysis and recommendation

[2009] Overview: The server applies an AI model to the collected data to analyze it, and based on the results, recommends the most suitable content, friend candidates, food items, and food events to the user.

[2010] Software used: Generative AI model algorithms, machine learning libraries (e.g., TensorFlow, PyTorch)

[2011] Example: If a user has frequently viewed "pizza" related content in the past, the server can analyze their behavioral patterns and recommend new pizza-related delivery options or local pizza festivals.

[2012] 3. Acquisition and provision of information on local food events

[2013] Overview: The server obtains local food event information from external data sources, stores it in a database, and recommends relevant events based on the user's location information.

[2014] Software used: External API (e.g., event information API)

[2015] Example: If the user lives in "Yokohama City", information about pizza festivals held in the area is retrieved from an external data source and recommended to the user.

[2016] Terminal side embodiment

[2017] 1. Intuitive User Interface (UI)

[2018] Overview: The device provides an intuitive UI that is easy for seniors to operate, and includes features such as voice control and uppercase fonts.

[2019] Hardware used: smartphone, head-mounted display (HMD)

[2020] Example: If a user uses a voice command to say, "Tell me what pizzas are best," the device recognizes the voice command and displays related food items and events in a large font.

[2021] 2. Visual display of local food event information

[2022] Overview: Visually displays recommendation information and event information from the server.

[2023] Software used: GUI library (e.g. React Native, Flutter)

[2024] Example: A list of local food events is displayed, and users can select an event that interests them and view more information.

[2025] User-Side Embodiment

[2026] 1. Update your profile

[2027] Overview: A user updates his or her profile information and sends the data to a server via the device.

[2028] Example: When a user adds a new hobby to their profile, "making pizza," this information is immediately sent to the server and stored.

[2029] 2. Participating in food events

[2030] Overview: Users use their devices to access local food events and register to participate.

[2031] Example: A user selects an event of interest from a list of local food events displayed within the platform and presses the "Attend" button.

[2032] These efforts will help promote eating habits and social interactions among the elderly and increase the convenience of the platform.

[2033] Example prompt sentence:

[2034] If a user enters "I like Twice Cooked Pork" in their profile, the server will recommend "food items and related events related to Twice Cooked Pork."

[2035] For example, if the user sets the location information as "Yokohama City," information about the Twice Cooked Pork Festival will be provided.

[2036] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2037] Step 1:

[2038] The server collects and stores user data

[2039] Input: Users input profile information and preference information

[2040] Processing: The server receives this information and stores it in a database. Specifically, it analyzes the data sent from the smartphone or head-mounted display (HMD) and stores it in the database in an appropriate format.

[2041] Output: User information stored in the database

[2042] Step 2:

[2043] The server applies an AI model to the collected data and analyzes it.

[2044] Input: User data stored in the database

[2045] Processing: The server analyzes the data using machine learning libraries (e.g., TensorFlow, PyTorch) to understand user preferences and behavioral patterns. An AI model analyzes the data and identifies recommendations.

[2046] Output: Analysis results, list of recommended targets

[2047] Step 3:

[2048] The server uses the analysis to recommend content, friend suggestions, events, food items, and delivery options.

[2049] Input: Analysis results, list of recommended targets

[2050] Processing: The server categorizes recommendations into categories and selects the most suitable content, friend suggestions, events, food items, and delivery options for the user, using a generative AI model algorithm.

[2051] Output: Recommended content for the user, friend suggestions, events, food items, and delivery options

[2052] Step 4:

[2053] The server retrieves local food event information from an external data source.

[2054] Input: User's location

[2055] Processing: The server uses an external API (e.g., an event information API) to obtain local food event information based on the user's location. Specifically, the server sends an API request and temporarily stores the obtained data.

[2056] Output: Local food event information

[2057] Step 5:

[2058] The server stores the food event information it has obtained.

[2059] Input: Retrieved local food event information

[2060] Processing: The server formats the food event information and stores it in a database, allowing for fast responses to user requests.

[2061] Output: Food event information stored in the database

[2062] Step 6:

[2063] The device accepts input from the user through the user interface (UI) and sends a request to the server.

[2064] Input: Voice commands and touch input from the user

[2065] Processing: The device receives the user's input, converts it into an appropriate format, and sends a request to the server. Specifically, it uses voice recognition technology to convert voice commands into text data.

[2066] Output: Request data to the server

[2067] Step 7:

[2068] The terminal displays the response from the server to the user.

[2069] Input: Response data from the server

[2070] Processing: The device visually displays the response data received from the server, specifically by displaying the information in large font on the smartphone or HMD screen so that the user can easily understand it.

[2071] Output: Information displayed to the user

[2072] Step 8:

[2073] The device visually displays information about local food events.

[2074] Input: Local food event information obtained from the server

[2075] Processing: The device displays food event information in a visually easy-to-understand format, such as a list or card format, allowing the user to view the details.

[2076] Output: Visual display of local food event information

[2077] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2078] The present invention relates to a system for providing more personalized services on a social networking platform for seniors by combining the collection and storage of user data, data analysis using AI models, recommendations of content, friend candidates, and events, as well as an emotion engine that recognizes user emotions. Specific embodiments of this system are described below.

[2079] Server-side implementation

[2080] 1. User Data Collection and Storage:

[2081] Overview: The server collects profile information, behavioral data, and emotional information of elderly users and stores them in a database.

[2082] Example: User A enters his / her hobbies and location on a profile page, and the information is sent from the device to the server and stored in the server's database. In addition, the user's emotional reactions while watching a video are also recorded as emotional data.

[2083] 2. Data analysis and recommendations:

[2084] Overview: The server applies AI models to the collected data, analyzes the user's behavioral patterns and emotional data, and based on the results, recommends the most suitable content, friend candidates, and events to the user.

[2085] Example: If User B has frequently viewed health-related content in the past and the emotion engine detects a positive reaction to it, the server can recommend new health articles or online fitness classes.

[2086] 3. Acquisition and provision of local event information:

[2087] Overview: The server obtains local event and community information from external data sources, stores it in a database, and recommends related events based on the user's location and emotion data.

[2088] Example: If user C is interested in crafts and has positive feelings about that interest, the server will recommend information about craft workshops taking place in the area.

[2089] Terminal side embodiment

[2090] 1. User Interface (UI):

[2091] Overview: The device provides an intuitive UI that is easy for seniors to operate, including features such as voice control and uppercase fonts.

[2092] Example: If user D uses a voice command to say "Find friends," the device will recognize the voice command, launch the friend search function, and display the search results in capital letters.

[2093] 2. Emotion Engine Operation:

[2094] Overview: The device is equipped with an emotion engine that analyzes the user's emotions in real time from their facial expressions and tone of voice, and sends the data to a server.

[2095] Example: While user E is watching a video, the device analyzes the user's facial expressions with a camera and transmits emotional data to the server in real time.

[2096] User-Side Embodiment

[2097] 1. Update your profile:

[2098] Overview: Users update their profile information and emotional information and send it to the server via their device.

[2099] Example: User F adds "gardening" as a new hobby, and emotion data about the hobby is also sent to the server.

[2100] 2. Participate in community events:

[2101] Summary: Users can easily access local events through their devices and select recommended events using emotional data when registering to attend.

[2102] Example: User G selects an event of interest from a list of local events displayed within the platform, and presses the "Participate" button based on the emotional data for that event.

[2103] In this way, by combining the emotion engine, the system of the present invention provides a more personalized user experience and improves the quality of life for the elderly. The server, terminal, and user work together to provide optimal services tailored to the user's emotional state.

[2104] The processing flow will be explained below.

[2105] User Data Collection and Storage Process Steps

[2106] Step 1:

[2107] The user enters profile information.

[2108] User: Enter their hobbies, location, health information, etc. on their profile page.

[2109] Example: User A enters "gardening" as a hobby.

[2110] Step 2:

[2111] The entered data is sent to the server.

[2112] Terminal: Sends input information to the server in real time.

[2113] Example: The terminal sends user A's hobby information to the server as a data packet.

[2114] Step 3:

[2115] Save the data to a database.

[2116] Server: Validates the received data and stores it in the database.

[2117] Example: The server adds the hobby "gardening" to User A's profile.

[2118] Processing steps for collecting and storing emotion data

[2119] Step 1:

[2120] Start your emotion engine.

[2121] Device: Activate the emotion engine when watching videos or browsing content.

[2122] Example: When a user starts watching a fitness video, the device's emotion engine is activated.

[2123] Step 2:

[2124] Emotion data is analyzed and sent to the server.

[2125] Device: Analyzes the user's facial expressions and tone of voice in real time and sends the results to the server.

[2126] Example: If a user smiles while watching a video, send that positive emotion data to the server.

[2127] Step 3:

[2128] Emotion data is stored in a database.

[2129] Server: Validates the received emotion data and stores it in a database.

[2130] Example: The server integrates user emotion data into User A's profile.

[2131] Data analysis and recommendation processing steps

[2132] Step 1:

[2133] Periodically read the stored data.

[2134] Server: Periodically reads user data and emotion data from the database.

[2135] Example: The server reads user A's behavioral and emotional data every day.

[2136] Step 2:

[2137] Apply AI models to analyze the data.

[2138] Server: Analyzes the stored data using AI models to analyze user trends.

[2139] Example: The server analyzes which genres of content User A has frequently viewed in the past month and which content he has responded positively to.

[2140] Step 3:

[2141] Generate recommendations based on the analysis results.

[2142] Server: Based on the analysis results, it generates the most suitable content, friend suggestions, and events for the user.

[2143] Example: The server recommends to user A new articles about "gardening" and other users with the same hobby.

[2144] Step 4:

[2145] Prepare the recommendations in the form of a notice.

[2146] Server: Formats the recommendation information and prepares it to be sent to the device as a notification message.

[2147] Example: A server creates a notification that says "Join an online group for gardening enthusiasts."

[2148] Processing steps for obtaining and providing local event information

[2149] Step 1:

[2150] Retrieve local event information from an external data source.

[2151] Server: Collects local event information from external APIs and databases.

[2152] Example: The server retrieves the events calendar from the API of a local cultural center.

[2153] Step 2:

[2154] Save the retrieved data in the database.

[2155] Server: Validates the acquired event information and stores it in an internal database.

[2156] Example: The server stores the obtained information about the craft workshop in a database.

[2157] Step 3:

[2158] Recommend events based on user location and emotion data.

[2159] Server: Obtains user location and emotion data and recommends relevant events.

[2160] Example: Notify user B of a craft workshop near where they currently live. If the user has a strong interest in crafts, the event will be recommended even more strongly.

[2161] User interface provision and operation processing steps

[2162] Step 1:

[2163] The user logs in and sees the main dashboard.

[2164] Terminal: Receives login information, authenticates the user, and displays the main dashboard.

[2165] Example: When User C logs in, the dashboard displays recent notifications and recommended content.

[2166] Step 2:

[2167] Accepts interaction from the user.

[2168] Device: Accepts actions such as button presses, swipes, and voice commands.

[2169] Example: User D enters the voice command "Find friends."

[2170] Step 3:

[2171] Send the request to the server.

[2172] Terminal: Sends appropriate requests to the server based on user actions.

[2173] Example: The device analyzes user D's voice command and sends a friend search request to the server.

[2174] Step 4:

[2175] Displays the response from the server.

[2176] Terminal: Receives the response from the server and displays it to the user.

[2177] Example: The device displays the search results from the server on the screen and provides new friend candidates to User D.

[2178] In this way, the platform of the present invention provides a high-level user experience that includes emotional data by linking the terminal, server, and user.

[2179] Example 2

[2180] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2181] Current social networking platforms for seniors lack personalized services, making it difficult for them to find content, friends, and events that suit them. Another issue is that few services utilize emotional data, making it difficult to provide appropriate recommendations that match current emotions.

[2182] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for collecting and storing user data, a means for applying a generative AI model to the collected user data and analyzing it, a means for recommending content, friend candidates, and events based on the analysis results, a means for collecting and storing user emotion data, and a means including an emotion analysis engine for performing analysis based on the emotion data. This makes it possible to provide personalized services by utilizing the user's behavioral data and emotion data.

[2183] "User Data" refers to a user's profile information, behavioral data, location information, and any other data related to the use of the Platform.

[2184] A "generative AI model" is a model that uses machine learning algorithms to analyze data and generate new information and predictions based on the learning results.

[2185] An "emotion analysis engine" refers to software or hardware functionality that analyzes emotional data from a user's facial expressions, voice, etc. in real time.

[2186] "Content" refers to articles, videos, music, images, and any other information provided to users.

[2187] "Friend candidates" refers to data for recommending other users who may be of interest or related to the user.

[2188] "Event" refers to a workshop, seminar, sporting event, or other gathering held in the community.

[2189] An "intuitive user interface" refers to a simple and easy-to-understand screen layout and operating procedures designed to be easy for seniors to operate.

[2190] "Voice operation" refers to a function that allows the user to perform various operations on the system using voice commands.

[2191] "Capital font" refers to a font that is displayed in a larger-than-normal character size to improve legibility.

[2192] "External data sources" refers to online services or APIs that provide various data that can be accessed from outside the system.

[2193] "Location information" refers to geographic data that indicates a user's current location.

[2194] MODE FOR CARRYING OUT THE INVENTION

[2195] The present invention relates to a system for providing more personalized services on a social networking platform for seniors by combining the collection and storage of user data, data analysis using a generative AI model, recommendations of content, friend candidates, and events, as well as a sentiment analysis engine that recognizes user emotions. Specific embodiments of this system are described below.

[2196] Server-side implementation

[2197] User Data Collection and Storage:

[2198] The server obtains the profile information, behavioral data, and emotional information of the elderly user and stores this information in a database. For example, when a user enters their hobbies or location on the profile page, the device sends this information to the server as an HTTP POST request. The server then saves the received data in a database (e.g., MySQL) using an INSERT statement. If the saving process is successful, the server returns a status indicating that the save was successful to the device.

[2199] Data analysis and recommendations:

[2200] The server applies a generative AI model to the collected data and analyzes the user's behavioral patterns and emotional data. Based on the results, it recommends optimal content, friend candidates, and events to the user. For example, the server periodically retrieves user data from the database using a SELECT statement and transfers that data to the AI ​​analysis server. This analysis is performed using Python and TensorFlow. Based on the analysis results, recommended items are generated and cached in the database. These recommendations are displayed the next time the user logs in.

[2201] Acquiring and providing local event information:

[2202] The server retrieves local event information from external data sources and recommends relevant events to users based on location and emotion data. For example, the server periodically calls an external API (e.g., Eventbrite API) to retrieve local event information, extracts the necessary information, and stores it in a database. When a user logs in, the server picks up and recommends events held in the surrounding area.

[2203] Terminal side embodiment

[2204] User Interface (UI):

[2205] The device provides an intuitive UI that seniors can easily operate, including features such as voice control and capital font. For example, when a user says the voice command "Find friends," the device converts the speech to text using the Google Cloud Speech-to-Text API, creates a search query based on that text, and sends it to the server. The device then displays the search results from the server in capital font.

[2206] Sentiment Analysis Engine:

[2207] The device is equipped with an emotion analysis engine that analyzes emotions in real time from the user's facial expressions and tone of voice and sends the data to a server. For example, while the user is watching a video, the device's camera captures facial expressions in real time and sends the analysis data to a server. This analysis uses OpenCV and deep learning libraries (e.g., OpenFace).

[2208] User-Side Embodiment

[2209] Update your profile:

[2210] Users update their profile information and emotional information and send it to the server via their devices. For example, if a user adds "gardening" as a new hobby, the changes are sent to the server as an HTTP POST request, and the server updates the database.

[2211] Participate in community events:

[2212] Users can easily access local events through their devices and register to participate. Emotional data can also be used to select recommended events. For example, when a user selects an event they are interested in from the event list and presses the "Participate" button, the device sends the information to the server, which then stores the participation information in a database.

[2213] Prompt Sentence Examples

[2214] "Suggest new health articles or online fitness classes to users who have previously expressed positive feelings about health-related content."

[2215] This system allows the server, device, and user to work together to utilize user behavioral and emotional data, providing a personalized user experience and improving the quality of life for the elderly.

[2216] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2217] Program processing flow

[2218] Server Action:

[2219] Step 1:

[2220] The server receives user data sent from the device. The input includes user profile information and behavioral data. Specifically, the server receives an HTTP POST request and stores the data in temporary memory.

[2221] Step 2:

[2222] The server saves the received user data in a database. MySQL is used as the database. For data processing, the received data is converted into an INSERT statement and inserted into the database. As output, a status indicating successful saving is generated and returned to the terminal.

[2223] Step 3:

[2224] The server periodically retrieves user data from the database. The input includes user profile information and behavioral data stored in the database. It executes SELECT statements to retrieve data from the database and loads the retrieved data into memory.

[2225] Step 4:

[2226] The server inputs the acquired user data into the generative AI model and performs data analysis. Specifically, it runs the generative AI model using Python and TensorFlow. Data calculations involve clustering and pattern recognition of user behavior patterns and emotional data. The output is the analysis results.

[2227] Step 5:

[2228] The server generates recommended items based on the analysis results. The input includes the analysis results of the AI ​​model. The generated recommended items are cached in a database. The output is the cached recommended items.

[2229] Step 6:

[2230] The server retrieves local event information from an external data source. Specifically, it calls an external API (e.g., Eventbrite API) to retrieve local event information. The input includes the API request. The retrieved event information is parsed in JSON format and the necessary fields are extracted. The extracted event information is obtained as output.

[2231] Step 7:

[2232] The server saves the acquired event information in the database. Specifically, it creates an INSERT statement based on the extracted event information and inserts it into the database. As an output, it generates a status indicating that the save was successful.

[2233] Step 8:

[2234] The server recommends local events based on the user's location and emotion data. The input includes the user's location and emotion data. Based on this, the server searches for appropriate events and lists them as recommended items. The output is a list of related events.

[2235] Terminal handling:

[2236] Step 1:

[2237] The device accepts input from the user, including voice commands and touch gestures. Specific operations include capturing voice data for voice input and recognizing screen gestures for touch input.

[2238] Step 2:

[2239] The device processes the received user input and sends a request to the server. The input includes the user input data. Specifically, in the case of voice input, the device converts the voice to text using the Google Cloud Speech-to-Text API, generates an HTTP request, and sends it to the server. The output is a request to the server.

[2240] Step 3:

[2241] The terminal receives the response from the server. Specifically, it receives the HTTP response and analyzes its contents. The input includes the response data from the server. The output is the analyzed data.

[2242] Step 4:

[2243] The terminal displays the server's response to the user. Specific display operations include displaying text in uppercase font and outputting voice using speech synthesis. The output allows the user to confirm the information visually or audibly.

[2244] Step 5:

[2245] The device collects the user's facial expressions and voice tone in real time. Specifically, it captures facial expression data with a camera and records voice data with a microphone. The input includes the user's real-time facial expressions and voice data.

[2246] Step 6:

[2247] The device inputs the collected facial expression and voice data into an emotion analysis engine for analysis. Libraries such as OpenCV and OpenFace are used for the analysis. Data calculations involve facial expression recognition and voice tone analysis. The output is analyzed emotion data.

[2248] Step 7:

[2249] The device sends the emotion data obtained as a result of the analysis to the server. Specifically, it generates an HTTP POST request and sends it to the server. The input includes the analyzed emotion data. The output is the completion of the emotion data transfer to the server.

[2250] User Action:

[2251] Step 1:

[2252] A user enters or updates profile information, including new hobbies, location, etc. The user enters the data on the device's profile editing page.

[2253] Step 2:

[2254] The user sends profile information to the server through the device. After checking the input data, the user presses the send button to generate an HTTP POST request, which the device then sends to the server. As an output, a send request to the server is generated.

[2255] Step 3:

[2256] The user operates the device to browse the local event list. Specifically, the user opens the event list page on the device and selects an event they are interested in. The input includes the user's selection data.

[2257] Step 4:

[2258] A user registers to participate in an event. After selecting an event, the user presses the "Participate" button to generate a request to send information about the selected event to the server. The output is a participation request sent to the server.

[2259] Step 5:

[2260] The user waits for a response from the server confirming their participation in the event. Specifically, the user receives the response from the server using the notification function on the device. The input includes the response data from the server. The output is a notification confirming their participation.

[2261] (Application example 2)

[2262] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2263] Conventional social networking platforms for seniors have difficulty providing personalized services that fully reflect users' emotions and preferences. Furthermore, conventional technologies are insufficient when it comes to providing a user interface that is easy for seniors to use and recommending local event information. In particular, there is a demand for technology that can analyze seniors' emotions and recommend the most appropriate content and events based on that analysis.

[2264] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2265] In this invention, the server includes means for collecting and storing user data, means for applying a generative AI model to the collected user data and analyzing it, means for recommending content, friend candidates, and events based on the analysis results, means for operating an emotion engine that analyzes emotions from the user's facial expressions and tone of voice in real time, and means for transmitting emotion data to the server, thereby enabling the provision of personalized services based on the user's emotional state.

[2266] A "communication platform for the elderly" is an online system aimed primarily at elderly people for the purpose of mutual interaction.

[2267] "User data" refers to various information about an individual, including a user's profile information, behavioral data, emotional data, and the like.

[2268] A "generative AI model" is an artificial intelligence algorithm used to analyze user behavioral and emotional data.

[2269] "Means for analysis" refers to the function of applying a generative AI model to collected user data and performing analysis.

[2270] "Content" includes information or entertainment elements such as articles, videos, images, etc. provided to users.

[2271] "Friend candidates" refer to other users with whom the user may potentially build new friendships.

[2272] "Event" means any gathering or activity, held online or offline, in which users can participate.

[2273] The "Emotion Engine" is a system that analyzes emotions in real time from a user's facial expressions and tone of voice.

[2274] "Emotion data" is information about the user's emotional state obtained by the emotion engine.

[2275] "Server" means the primary computer system that collects, stores, and analyzes user data and uses the generative AI model.

[2276] "External Data Sources" refers to information sources outside the Platform that provide information such as local event information.

[2277] "Location information" is data indicating the user's current location and movement information.

[2278] An "intuitive user interface" is a graphical or audio-based interface designed to be easy for users to operate.

[2279] "Recommendation" refers to the activity of suggesting specific content, potential friends, events, etc. to the user based on the analysis results.

[2280] "Real-time" refers to immediate processing and feedback without delay.

[2281] This system is designed to provide a communication platform for the elderly and recommend personalized services by analyzing users' emotional data. The system operates in cooperation with the server, terminals, and users.

[2282] Server-side implementation

[2283] User Data Collection and Storage:

[2284] The server collects user profile information, behavioral data, and emotional data and stores them in a database. Specifically, the profile information and behavioral history entered by the user into the device, as well as the emotional data analyzed by the emotion engine, are sent to the server and stored there.

[2285] Data analysis and recommendations:

[2286] The server applies generative AI models to the collected data to analyze the user's behavioral patterns and emotional data. Based on the analysis results, the server can recommend content, friend suggestions, and local events that are most suitable for the user. For example, if a user prefers health-related content, the server can recommend new health articles and online fitness classes.

[2287] Retrieving information from external data sources:

[2288] The server retrieves necessary data from external data sources to obtain local event and community information and stores it in a database, which enables recommendations of local events based on the user's location and emotion data.

[2289] Terminal side embodiment

[2290] User Interface (UI):

[2291] The device offers an intuitive UI that seniors can easily operate, including voice control, large font, and touch control. For example, if a user uses the voice command "Find friends," the device recognizes the command and launches the friend search function.

[2292] Emotion Engine Operation:

[2293] The device has an emotion engine built in that analyzes the user's facial expressions and tone of voice to generate emotion data. This data is sent to a server in real time. For example, while the user is watching a video, the camera analyzes the user's facial expressions and sends the emotion data to the server.

[2294] User-Side Embodiment

[2295] Update your profile:

[2296] A user can update his / her profile information and emotional data and send it to the server through the terminal, for example, by adding a new hobby to his / her profile and sending the emotional data related to that hobby to the server.

[2297] Participate in the event:

[2298] Users can easily access local events through their devices and register to participate. Related events are recommended using emotion data, making it easier for users to participate in events that interest them. For example, a user who is interested in handicrafts will be recommended information about handicraft workshops being held in their area and can register to participate in those events.

[2299] Hardware and Software Use

[2300] Hardware:

[2301] Server: The main server for running the database and AI models

[2302] Camera: Analyzes the user's facial expressions

[2303] Microphone: Analyzes the user's voice tone

[2304] Smartphones and head-mounted displays (HMDs)

[2305] software:

[2306] Python, TensorFlow, OpenCV: Implementing a sentiment analysis engine and AI model

[2307] API server: Acquires and stores user data, receives emotion data

[2308] User Interface: UI that supports voice recognition and touch operation

[2309] Examples and prompts

[2310] example:

[2311] Example: When a user uses a virtual community assistant in an app installed on their smartphone, the camera analyzes the user's facial expressions and recommends products and events that the user is interested in in real time.

[2312] Prompt for the generative AI model:

[2313] "Analyze the reactions of users to products they are looking at while shopping and recommend other products related to the products that showed positive emotions."

[2314] In this way, the system can improve the quality of life for the elderly and provide more personalized services.

[2315] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2316] Step 1:

[2317] Entering and saving user data (terminal and server)

[2318] Users input their profile information and behavioral data through their devices. The devices then send this data to the server, which then stores it in a database. For example, a user might add a new hobby. The information entered includes profile information, behavioral history, and emotional data, and all of this data is managed centrally by the server.

[2319] Step 2:

[2320] Acquiring emotion data (device)

[2321] The device uses an emotion engine to obtain emotion data in real time from the user's facial expressions and voice tone. The emotion engine uses a camera and microphone to analyze the user's emotions and generate the results as data. The input in this step is the user's facial expressions and voice tone, and the output is the analyzed emotion data.

[2322] Step 3:

[2323] Sending emotional data (device and server)

[2324] The device transmits the acquired emotional data to a server in real time. The server receives this data and stores it in a database along with the user profile and behavioral data. Continuous acquisition of emotional data enables more precise analysis. The input is emotional data, and the output is transmission to the server and storage in the database.

[2325] Step 4:

[2326] Data analysis and information recommendation (server)

[2327] The server applies a generative AI model to the collected user data, analyzing behavioral patterns and emotional data. The analysis results in data that can be used to recommend content, friend candidates, and local events that are best suited to the user. The input for this step is the stored data, and the output is a recommendation list. Specifically, new health articles and online fitness classes will be recommended to users who prefer health-related content.

[2328] Step 5:

[2329] Obtaining information from external data sources (server)

[2330] The server retrieves the necessary data from external data sources to obtain local event and community information. The retrieved data is stored in a database and becomes the basis for recommendations based on the user's location and emotion data. The input is external data, and the output is stored in the database.

[2331] Step 6:

[2332] User Interface (Terminal)

[2333] The device provides an intuitive user interface designed for seniors. Users can easily operate it using voice commands, touch operations, and capital fonts. For example, if you use the voice command "Find friends," the device recognizes the command and activates the friend search function. In this step, the input is a voice command or touch operation, and the output is the activation of the corresponding function.

[2334] Step 7:

[2335] Event and content recommendations (device)

[2336] The content and events desired by the user are displayed on the device. Based on the recommendation list sent from the server, the most suitable content and event information for the user is displayed. The input is the recommendation data from the server, and the output is the display on the user interface. Specifically, for a user who prefers health-related information, related new articles and events are displayed.

[2337] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2338] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2339] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2340] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2341] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept o...

Claims

1. On a social networking platform for seniors, means for collecting and storing user data; A means for applying an AI model to the collected user data and analyzing it; A means to recommend content, friend candidates, and events based on the analysis results, A system including:

2. A means of retrieving and storing local event and community information from external data sources; means for recommending relevant local events based on the user's location information; The system of claim 1 , comprising:

3. A means for providing an intuitive user interface that is easy for users to operate; means for accepting input from a user and sending requests to a server; means for displaying to the user a response from the server to the request; The system of claim 1 , comprising:

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