system

Abstract

Provide a system. A login authentication means for authenticating a user; a user profile management means for managing profile information including user interests; A means for generating conversation data that uses generative AI to generate conversation content between users in real time; A user matching means for finding and matching with other users who share common interests based on the user's profile information; a real-time conversation management means for managing the content of conversations communicated in real time between users; a robot control command means for sending commands to the robot so that the robot provides guidance and services to users; A system including:

Description

[Technical Field]

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

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

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

[0004] In modern society, cafes and similar social spaces face challenges that make it difficult for users to communicate naturally and efficiently. Furthermore, users who meet for the first time often take time to find appropriate topics to talk about, and conversations often stall. Furthermore, insufficient information sharing about upcoming events often misses opportunities to stimulate users' latent interest and motivation to participate. Given these current circumstances, there is a need for systems that can promote communication between users, match users based on their interests, and provide real-time conversation generation functions using generative AI. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems with a system including a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, and a robot control command means. Specifically, the login authentication means first authenticates the user, and then the user profile management means manages profile information, including the user's interests and concerns. Based on this profile information, the user matching means automatically matches users with common interests and concerns. Furthermore, by combining the conversation data generation means and the real-time conversation management means, generative AI is utilized to generate and manage user conversations in real time. Finally, via the robot control command means, a robot in the cafe provides users with event information and recommended topics, providing a smoother and more fulfilling communication environment.

[0006] "Login authentication means" refers to a means that provides an authentication function for verifying the identity of a user when accessing a system.

[0007] "Profile management tools" are tools that provide the functionality to collect, manage, and store personal information such as a user's name, interests, and concerns.

[0008] "Means for generating conversation data" refers to a means for providing a function for generating conversation content between users in real time using generative AI.

[0009] "User matching means" refers to a means that provides a function for finding and matching other users who share common interests and concerns based on the user's profile information.

[0010] "Real-time conversation management means" refers to a means for managing the content of conversations communicated between users in real time and providing a function for ensuring smooth exchanges.

[0011] The "robot control command means" is a means for sending commands from the system to the robot, causing the robot to perform operations to provide guidance and services to users. [Brief explanation of the drawings]

[0012] [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 illustrating 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

[0013] 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.

[0014] First, the terms used in the following description will be explained.

[0015] 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).

[0016] 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.

[0017] 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.

[0018] 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.

[0019] 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."

[0020] [First embodiment]

[0021] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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."

[0033] The present invention is a system for promoting communication between users in social spaces such as cafes. A specific embodiment of this system and the processing of the program will be described below.

[0034] The system mainly consists of the following components:

[0035] Login authentication method

[0036] User profile management means

[0037] Conversation data generation method

[0038] User matching method

[0039] Real-time conversation management

[0040] Robot control command means

[0041] Login Process

[0042] The user operates a tablet device installed in the cafe and accesses the login page. The user enters the required information such as name and password and clicks the login button.

[0043] The terminal transmits the input user information to the server.

[0044] The server checks the received user information against a database, and if authentication is successful, generates an authentication token and returns it to the terminal.

[0045] The device stores the authentication token and proceeds to the next step.

[0046] Profile Management

[0047] After logging in, users access a page where they can add or update their profile information, including their interests.

[0048] The terminal transmits the entered profile information to the server.

[0049] The server stores the received profile information in a database and uses it to match users with other users.

[0050] User matching

[0051] The server searches for and extracts users who share common interests based on the profile information of the logged-in user, adds the users to a matching list, and sends it to the device.

[0052] The terminal receives the matching list and displays it to the user.

[0053] The user selects a person with whom he or she wants to start a chat from the displayed list and presses the chat start button.

[0054] Real-time conversation generation

[0055] The user enters a message on the chat screen and clicks the send button.

[0056] The terminal transmits the input message to the server.

[0057] The server receives the message, analyzes it, and sends a request to the generative AI.

[0058] The generative AI generates an appropriate response to the message and sends it back to the server.

[0059] The server receives the generated response, formats it appropriately, and sends it to the chat partner's device.

[0060] The device will display the received message in the chat window.

[0061] Robot Control

[0062] The user selects a specific action (e.g., requesting event information) from the tablet device and sends a command.

[0063] The terminal transmits the command content to the server.

[0064] The server receives the commands and sends control commands to the appropriate robots.

[0065] The robot receives commands and performs the specified action (e.g., reading out event information).

[0066] The robot reports the results of its operations to the server, and the server notifies the terminal of the results.

[0067] Specific examples

[0068] For example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the device notifies Person A and Person B, and they begin chatting with each other.

[0069] When Person A types "What recent movies do you recommend?" into the chat and sends it, the server uses generative AI to generate an appropriate response, which is displayed on Person B's device. Furthermore, if Person A requests information about events, the robot will provide information about events currently being held in the cafe.

[0070] In this way, customers can communicate efficiently and enjoyably within the cafe and receive guidance from the robot.

[0071] The processing flow will be explained below.

[0072] (Login process)

[0073] Step 1:

[0074] The user operates a tablet device installed in the cafe and accesses the login page.

[0075] Step 2:

[0076] The user enters login information such as name and password and clicks the login button.

[0077] Step 3:

[0078] The terminal sends the entered login information to the server.

[0079] Step 4:

[0080] The server receives the login information and checks it against the user information in its database.

[0081] Step 5:

[0082] If the server is successful in the authentication, it generates an authentication token and sends it to the terminal.

[0083] Step 6:

[0084] The device stores the received authentication token and displays a message to the user indicating that the login was successful.

[0085] (Profile Management)

[0086] Step 1:

[0087] After the user logs in, they access the profile settings page.

[0088] Step 2:

[0089] The user enters their profile information, such as interests, and clicks the save button.

[0090] Step 3:

[0091] The device transmits the entered profile information to the server.

[0092] Step 4:

[0093] The server stores the received profile information in a database.

[0094] (User matching)

[0095] Step 1:

[0096] The server searches for users with common interests based on each user's profile information.

[0097] Step 2:

[0098] The server extracts the relevant users and creates a matching list.

[0099] Step 3:

[0100] The server sends the matching list to each device.

[0101] Step 4:

[0102] The terminal displays the received matching list to the user.

[0103] Step 5:

[0104] The user selects a chat partner from the displayed list and presses the chat start button.

[0105] (Generating real-time conversations)

[0106] Step 1:

[0107] The user enters a message in the chat screen and clicks the send button.

[0108] Step 2:

[0109] The terminal sends the input message to the server.

[0110] Step 3:

[0111] The server analyzes the received message and sends a request to the generative AI.

[0112] Step 4:

[0113] The generative AI generates an appropriate response to the message and sends it back to the server.

[0114] Step 5:

[0115] The server receives the returned message, formats it, and sends it to the terminal.

[0116] Step 6:

[0117] Displays messages received by the device in the chat window.

[0118] (Robot Control)

[0119] Step 1:

[0120] The user selects a specific action (e.g., requesting event information) on the tablet device and clicks the send button.

[0121] Step 2:

[0122] The terminal sends the transmission content to the server.

[0123] Step 3:

[0124] The server sends the received request as a command to the appropriate robot.

[0125] Step 4:

[0126] The robot receives commands and performs the specified action (e.g., reading out information about an event).

[0127] Step 5:

[0128] The robot reports the results of its actions to the server.

[0129] Step 6:

[0130] The server checks the results of the operation and sends additional commands to the robot if necessary.

[0131] Step 7:

[0132] The terminal notifies the user that the robot's operation was successful.

[0133] These steps will make communication between customers in the cafe smooth and enjoyable.

[0134] Example 1

[0135] 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."

[0136] In modern society, it is often difficult for users to naturally interact with each other, especially in social spaces such as cafes. Furthermore, there is a lack of mechanisms for users with different interests to communicate efficiently. As a result, users tend to feel isolated, and social spaces are not fully utilized. Furthermore, there is a need for a mechanism that allows smooth real-time conversations and the sharing of information.

[0137] 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.

[0138] In this invention, the server includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a means for a user to select a specific action and send a command, a robot control command means for a robot to receive the command and execute the action, and a means for generating a response to an input message using a generative AI model. This allows users to be efficiently matched based on shared interests and concerns, and appropriate responses are generated in real time using the generative AI model, enabling smooth communication and information provision.

[0139] A "login authentication method" is a mechanism for verifying and authenticating the authentication information (e.g., name and password) entered by a user when accessing a system.

[0140] "User profile management means" means a mechanism by which a user can enter and update their interests and other profile information and store it in a database.

[0141] The "means for generating conversation data" is a mechanism for analyzing and processing messages and conversation content entered by users and generating conversation data.

[0142] "User matching means" is a system that searches for and extracts users with common interests and concerns based on user profile information, and matches them together.

[0143] The "real-time conversation management means" is a mechanism for sending and receiving messages between users in real time and managing conversations.

[0144] "Means for users to select specific actions and send commands" refers to a mechanism by which users select specific actions using a tablet device or the like and send commands to the system.

[0145] The "robot control command means" is a mechanism for transmitting commands received by the system to an appropriate robot, which then executes the operation.

[0146] "Means for generating a response to a message input by a generative AI model" refers to a mechanism that uses a generative AI model (e.g., GPT-3 (registered trademark)) to generate an appropriate response to a message input by a user.

[0147] This system is designed to promote communication between users in social settings such as cafes. The system mainly consists of a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a means for users to select specific actions and send commands, a robot control command means, and a means for generating replies to input messages using a generative AI model.

[0148] First, the user operates a tablet device installed in the cafe to access the login page. The user enters the required information, such as their name and password, and clicks the login button. The device sends the entered user information to the server. The server compares the received user information with its database, and if authentication is successful, generates an authentication token and sends it back to the device. The device saves the authentication token and proceeds to the next step.

[0149] After logging in, the user accesses the profile page and adds or updates profile information, including interests. The device sends the entered profile information to the server, which stores the received profile information in a database.

[0150] The server searches for and extracts users who share common interests based on the profile information of the logged-in user. The server adds the matching users to a matching list and sends it to the device. The device receives the matching list and displays it to the user. The user then selects the person they want to chat with from the displayed list and presses the start chat button.

[0151] The user enters a message on the chat screen and clicks the send button. The device sends the entered message to the server. The server receives the message, analyzes it, and sends a request to a generative AI (such as OpenAI's (registered trademark) GPT-3 model). The generative AI generates an appropriate response to the message and sends it back to the server. The server receives the generated response, formats it appropriately, and sends it to the device of the chat partner. The device displays the received message in the chat window.

[0152] The user can also select a specific action (e.g., requesting event information) from the tablet device and send a command. The device then sends the command to the server. The server receives the command and sends a control command to the appropriate robot. The robot then receives the command and performs the specified action (e.g., reading out event information). The robot then reports the results of its action to the server, which then notifies the device of the results.

[0153] As a concrete example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the device notifies Person A and Person B, and they begin chatting with each other.

[0154] When Person A types "What recent movies do you recommend?" into the chat and sends it, the server uses generative AI to generate an appropriate response, which is displayed on Person B's device. Furthermore, if Person A requests information about events, the robot will provide information about events currently being held in the cafe.

[0155] An example prompt is:

[0156] User Question:

[0157] "What recent movies would you recommend?"

[0158] AI response prompt:

[0159] "A recently released movie that has received particularly high praise is 'Movie Title'. This movie is 'Brief Movie Description'. You might enjoy it too."

[0160] In this way, customers can communicate efficiently and enjoyably within the cafe and receive guidance from the robot.

[0161] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0162] Step 1:

[0163] Users access the login page using a tablet device installed in the cafe.

[0164] Input: Login page on tablet device

[0165] Output: Login screen displayed

[0166] Specific operation: Tap the login icon on the device's home screen to display the login screen.

[0167] Step 2:

[0168] The user enters the required information such as name and password and clicks the login button.

[0169] Input: Name, Password

[0170] Output: Sending input information

[0171] Specific actions: Enter your name in the input field, then enter your password and tap the "Login" button.

[0172] Step 3:

[0173] The terminal transmits the input user information to the server.

[0174] Input: User name, password

[0175] Output: Request sent to server

[0176] Specific operation: When the login button is clicked, the device encrypts the data and sends it to the server using an HTTP POST request.

[0177] Step 4:

[0178] The server checks the received user information against a database, and if authentication is successful, generates an authentication token and returns it to the terminal.

[0179] Input: Username, Password

[0180] Output: Authentication token

[0181] Specific operation: The server queries the database, and if there is matching information, it generates a JWT (JSON Web Token) and sends it to the terminal.

[0182] Step 5:

[0183] The device stores the authentication token and proceeds to the next step.

[0184] Input: Authentication Token

[0185] Output: Authentication token saved

[0186] Specific operation: The received token is saved in local storage and prepared for the user's next operation.

[0187] Step 6:

[0188] After logging in, users access their profile page to add or update their profile information, including their interests.

[0189] Input: Interests, concerns

[0190] Output: Display of input information

[0191] Specific operation: Once you have logged in, a link to your profile page will appear; tap on it.

[0192] Step 7:

[0193] The terminal transmits the entered profile information to the server.

[0194] Input: Interests, concerns

[0195] Output: Request sent to server

[0196] Specific operation: Tap the submit button to send the information entered in the form to the server.

[0197] Step 8:

[0198] The server stores the received profile information in a database.

[0199] Input: Interests, concerns

[0200] Output: Save to database

[0201] Specific operation: The server inserts or updates the received data into the user profile table in the database.

[0202] Step 9:

[0203] The server searches for and extracts users who share common interests and concerns based on the profile information of the logged-in user.

[0204] Input: User profile information

[0205] Output: Matching list

[0206] What it does: The server filters other user profiles based on the user's areas of interest and generates a list of users with whom you have something in common.

[0207] Step 10:

[0208] The server sends the matching list to the terminal.

[0209] Input: Matching List

[0210] Output: Sending a request to the terminal

[0211] Specific operation: The generated list is sent to the terminal in JSON format.

[0212] Step 11:

[0213] The terminal receives the matching list and displays it to the user.

[0214] Input: Matching List

[0215] Output: Display list

[0216] Specific operation: When the list is received, it is reflected in the display UI and displayed in a format that is easy for the user to see.

[0217] Step 12:

[0218] The user selects a person with whom he or she wants to start a chat from the displayed list and presses the chat start button.

[0219] Input: List item

[0220] Output: Chat start request

[0221] What it does: Tap on the user's name in the list and click the "Start Chat" button.

[0222] Step 13:

[0223] The user enters a message on the chat screen and clicks the send button.

[0224] Input: Message text

[0225] Output: Message send request

[0226] Specific actions: Enter a message in the text box and press the "Send" button.

[0227] Step 14:

[0228] The terminal transmits the input message to the server.

[0229] Input: Message text

[0230] Output: Request sent to server

[0231] Specific operation: The message text is sent to the server using an HTTP POST request.

[0232] Step 15:

[0233] The server receives the message, analyzes it, and sends a request to the generative AI.

[0234] Input: Message text

[0235] Output: Send prompt to AI

[0236] Specific operation: Analyze the message content and generate and send an appropriate prompt to a generative AI (e.g., GPT-3).

[0237] Step 16:

[0238] The generative AI generates an appropriate response to the message and sends it back to the server.

[0239] Input: prompt

[0240] Output: The generated response

[0241] How it works: The AI ​​model generates a response based on the prompt, and the response is received by the server.

[0242] Step 17:

[0243] The server receives the generated response, formats it appropriately, and sends it to the chat partner's device.

[0244] Input: Generated response

[0245] Output: Sending a request to the terminal

[0246] Specific operation: The response is formatted as JSON and sent to the chat participant's device.

[0247] Step 18:

[0248] The device will display the received message in the chat window.

[0249] Input: Generated response

[0250] Output: Display message

[0251] Specific behavior: When a message is received, it is displayed in the UI and can be confirmed by the user.

[0252] Step 19:

[0253] The user selects a specific action from the tablet device and sends a command.

[0254] Input: Action selection

[0255] Output: Command transmission request

[0256] Specific actions: Select "Event Information" from the menu and press the send button.

[0257] Step 20:

[0258] The terminal transmits the command content to the server.

[0259] Input: Action command

[0260] Output: Request sent to server

[0261] Specific Operation: An HTTP request is used to send the selected command information to the server.

[0262] Step 21:

[0263] The server receives the commands and sends control commands to the appropriate robots.

[0264] Input: Command information

[0265] Output: Sending control commands to the robot

[0266] Specific operation: Analyzes the command content and sends the command to the necessary robot.

[0267] Step 22:

[0268] The robot receives commands and performs the specified actions.

[0269] Input: Control command

[0270] Output: Action execution

[0271] Specific Action: The robot moves to the designated area and performs the programmed action.

[0272] Step 23:

[0273] The robot reports the results of its operations to the server, and the server notifies the terminal of the results.

[0274] Input: Operation result

[0275] Output: Result notification

[0276] Specific operation: An operation completion report is sent to the server, and the server sends a notification to the user's terminal.

[0277] (Application example 1)

[0278] 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."

[0279] In social spaces such as cafes, there is a need for an efficient system to promote communication between users and to automate information about events and services within the cafe.In addition, there is a need for a system that can generate conversations between users in real time using smartphones and act as a mobile guide.

[0280] 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.

[0281] In this invention, the server includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a mobile control command means, and a mobile information terminal application execution means. This allows users to be easily matched based on their shared interests and concerns, enables real-time conversations using generative AI, and automates information about events and services in the cafe via a smartphone application.

[0282] The "login authentication means" is a means for a user to input authentication information required to access the system and verify the user's identity.

[0283] "User profile management means" means a means for entering and updating a user's interests and other personal information and storing it in a database.

[0284] The "means for generating conversation data" is a means for generating the content of conversation necessary to promote communication between users.

[0285] "User matching means" refers to a means for searching for and matching users who share common interests.

[0286] "Real-time conversation management means" refers to a means for managing and supporting conversations between users in real time.

[0287] The "mobile object control command means" is a means for controlling and instructing the operation of a mobile object (such as a robot) for purposes such as event announcements and service provision.

[0288] "Mobile information terminal application execution means" refers to means for executing applications that run on mobile information terminals such as smartphones and tablets.

[0289] A "generative AI model" is an artificial intelligence model that generates appropriate responses and information based on input text and data.

[0290] A "prompt sentence" is an input sentence to a generative AI model, and is an instruction sentence that enables the AI ​​to generate an appropriate response.

[0291] MODE FOR CARRYING OUT THE INVENTION

[0292] The present invention is a system for promoting communication between users in social spaces such as cafes and providing information about events and services available within the cafe. Specific embodiments of this system are described below.

[0293] Login Authentication

[0294] Users log in using a tablet device installed in the cafe or their own smartphone. The user information entered through the login authentication means is sent to the server, which then collates it with a database for authentication. If authentication is successful, an authentication token is returned to the device.

[0295] Profile Management

[0296] After logging in, users can add or update their profile information, including their interests. The device sends the entered profile information to the server, which stores it in a database. The stored data is then used to match users with other users.

[0297] User matching

[0298] The server searches for and extracts other users who share common interests based on the profile information of the logged-in user. Matching users are added to a matching list, which is sent to the device. The user then selects the person they want to chat with from the displayed list and presses the Start Chat button.

[0299] Real-time conversation generation

[0300] The user enters a message on the chat screen and clicks the send button. The device sends the message to the server, which then uses the generative AI model to generate an appropriate reply. The generated reply is sent from the server to the chat partner's device and displayed in the chat window.

[0301] Event Information

[0302] Users can request information about events taking place in the cafe via a tablet or smartphone. This command is sent to the server, which then uses the mobile control command means to instruct the robot based on the command, and the robot then performs the specified action, such as reading out information about the event. The results of the robot's actions are reported to the server, which then notifies the terminal of the results.

[0303] Hardware and software used

[0304] Hardware: Tablets, smartphones, robots, servers

[0305] Software: User profile management software, generative AI models (e.g., GPT-3), authentication systems, matching algorithms, real-time chat software

[0306] Specific examples

[0307] For example, Person A and Person B visit a cafe and log in from their respective smartphones. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the devices notify Person A and Person B, and they begin chatting with each other. When Person A types and sends "What movies do you recommend these days?" in the chat, the server uses a generative AI model to generate an appropriate response, which is displayed on Person B's device. Furthermore, if Person A requests information about events, the robot will provide information about events currently being held in the cafe.

[0308] Prompt Sentence Examples

[0309] Simply launch the SmartCafe Connect app, log in, and update your interest profile. Then, check your match list and start chatting with other users who share your interests. If you request event information, a robot in the cafe will guide you to the event.

[0310] Login name: User name

[0311] Password:Password

[0312] Interests: Music, movies

[0313] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0314] Step 1:

[0315] Login Authentication

[0316] The user accesses the login page using a tablet device installed in the cafe or their own smartphone and enters their name and password. The device sends this input information to the server. The server compares the received user information with a database, and if authentication is successful, it generates an authentication token and sends it back to the device. The device saves the authentication token and moves the user to the next step.

[0317] Input: User name, password

[0318] Output: Authentication token

[0319] Step 2:

[0320] Profile Management

[0321] After logging in, users access a page where they can enter and update their profile information, including their interests. The device sends the entered profile information to the server, which stores this information in a database and uses it to match users with other users.

[0322] Input: User profile information (interests, concerns)

[0323] Output: Profile information stored in a database

[0324] Step 3:

[0325] User matching

[0326] The server searches for other users who share common interests based on the logged-in user's profile information and adds those users to a matching list. This matching list is sent to the user's device, which then displays it to the user. The user selects the person they want to chat with from the displayed list and presses the start chat button.

[0327] Input: Profile information stored in the database

[0328] Output: Matching list

[0329] Step 4:

[0330] Real-time conversation generation

[0331] The user enters a message on the chat screen and clicks the send button. The device sends the entered message to the server, which analyzes the message and sends a request to the generative AI model. The generative AI model generates an appropriate response to the message and sends it back to the server. The server receives the generated response and sends it to the device of the chat partner. The device displays the received message in the chat window.

[0332] Input: User's message

[0333] Output: The response from the generative AI model

[0334] Step 5:

[0335] Event Information

[0336] A user requests a specific action, such as an event announcement, via a tablet or smartphone. The device sends this command to the server. The server receives the command and sends a control command to the robot using the mobile object control command means. The robot receives the command and performs the specified action (e.g., reading out an event announcement). The robot reports the results of its action to the server, which then notifies the device of the result.

[0337] Input: User's event information request

[0338] Output: Event information by robot

[0339] Specific behavior:

[0340] Server: User authentication, storing information in a database, matching, requests to the generative AI model, sending vehicle control commands

[0341] Device: Sending user input, storing authentication tokens, displaying match lists, sending and receiving chat messages

[0342] Users: Log in, enter profile information, use chat, and send event invitation requests

[0343] Robot: Event guide execution 34,,

[0344] 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.

[0345] The present invention is a system for promoting communication between users in social spaces such as cafes. The system includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a robot control command means, and an emotion engine.

[0346] Specific embodiments of the system and program processing will be described below.

[0347] Login Process

[0348] The user operates a tablet device installed in the cafe and accesses the login page. The user enters the required information such as name and password and clicks the login button.

[0349] The terminal transmits the input user information to the server.

[0350] The server checks the received user information against a database, and if authentication is successful, generates an authentication token and returns it to the terminal.

[0351] The terminal stores the authentication token and displays a successful login to the user.

[0352] Profile Management

[0353] After logging in, users access a page where they can add or update their profile information, including their interests.

[0354] The terminal transmits the entered profile information to the server.

[0355] The server stores the received profile information in a database and uses it to match users with other users.

[0356] User matching

[0357] Based on the profile information mentioned above, the server searches and extracts users with common interests and creates a matching list.

[0358] The server sends the matching list to each terminal.

[0359] The terminal receives the matching list and displays it to the user.

[0360] The user selects the desired partner from the displayed list and presses the chat start button.

[0361] Real-time conversation generation

[0362] The user enters a message on the chat screen and clicks the send button.

[0363] The terminal transmits the input message to the server.

[0364] The server receives the message and sends a request to the generative AI.

[0365] The generative AI generates an appropriate response to the message and sends it back to the server.

[0366] The server receives the returned message, formats it, and sends it to the terminal.

[0367] The device will display the received message in the chat window.

[0368] Emotion engine integration

[0369] When a user inputs a message on the chat screen, the terminal transmits the input content to the server.

[0370] The server sends the received message to the emotion engine to analyze the user's emotions.

[0371] The emotion engine sends the analysis results back to the server, and the generative AI adjusts the content and style of the response based on those results.

[0372] The server sends the tailored response to the device, which displays it in the chat window.

[0373] As a concrete example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the device notifies Person A and Person B, and they begin chatting.

[0374] When Person A types in and sends "What recent movie do you recommend?", the server sends the message to the generative AI and emotion engine, and the emotion engine detects Person A's feelings of excitement and anticipation. Based on the results, the generative AI generates a response such as "The recent movie I recommend is 'Inception.' It's an amazing movie!" and displays it on Person B's device. In this way, the conversation between Person A and Person B becomes richer and more natural with the intervention of the emotion engine.

[0375] Robot Control

[0376] The user selects and sends a specific action (e.g., requesting event information) from the tablet device.

[0377] The terminal transmits the transmission contents to the server.

[0378] The server sends the request as a control command to the appropriate robot.

[0379] The robot receives commands and performs the specified action (e.g., reading out event information).

[0380] The robot reports the results of its operations to the server, and the server notifies the terminal of the results.

[0381] In this way, by implementing the system of the present invention, communication between users in a cafe becomes smooth and enjoyable, and the introduction of an emotion engine enables even deeper communication.

[0382] The processing flow will be explained below.

[0383] (Login process)

[0384] Step 1:

[0385] The user operates a tablet device installed in the cafe and accesses the login page.

[0386] Step 2:

[0387] The user enters login information such as name and password and clicks the login button.

[0388] Step 3:

[0389] The terminal sends the entered login information to the server.

[0390] Step 4:

[0391] The server receives the login information and checks it against the user information in its database.

[0392] Step 5:

[0393] If the server is successful in the authentication, it generates an authentication token and sends it to the terminal.

[0394] Step 6:

[0395] The terminal stores the received authentication token and displays a successful login to the user.

[0396] (Profile Management)

[0397] Step 1:

[0398] After the user logs in, they access the profile settings page.

[0399] Step 2:

[0400] The user enters their profile information, such as interests, and clicks the save button.

[0401] Step 3:

[0402] The device transmits the entered profile information to the server.

[0403] Step 4:

[0404] The server stores the received profile information in a database.

[0405] (User matching)

[0406] Step 1:

[0407] The server searches for users with common interests based on each user's profile information.

[0408] Step 2:

[0409] The server extracts the relevant users and creates a matching list.

[0410] Step 3:

[0411] The server sends the matching list to each device.

[0412] Step 4:

[0413] The terminal displays the received matching list to the user.

[0414] Step 5:

[0415] The user selects a chat partner from the displayed list and presses the chat start button.

[0416] (Generating real-time conversations)

[0417] Step 1:

[0418] The user enters a message in the chat screen and clicks the send button.

[0419] Step 2:

[0420] The terminal sends the input message to the server.

[0421] Step 3:

[0422] The server analyzes the received message and sends a request to the generative AI.

[0423] Step 4:

[0424] The generative AI generates an appropriate response to the message and sends it back to the server.

[0425] Step 5:

[0426] The server receives the returned message, formats it, and sends it to the terminal.

[0427] Step 6:

[0428] Displays messages received by the device in the chat window.

[0429] (Emotion engine integration)

[0430] Step 1:

[0431] The user enters a message in the chat screen and clicks the send button.

[0432] Step 2:

[0433] The terminal sends the input message to the server.

[0434] Step 3:

[0435] The server sends the received message to the emotion engine.

[0436] Step 4:

[0437] An emotion engine analyzes the message and identifies the user's emotion.

[0438] Step 5:

[0439] The emotion engine sends the analysis results back to the server.

[0440] Step 6:

[0441] The server requests the generative AI to generate a message based on the results of the emotion engine.

[0442] Step 7:

[0443] The generative AI generates an appropriate response based on the emotion and sends it back to the server.

[0444] Step 8:

[0445] The server receives the returned message, formats it, and sends it to the terminal.

[0446] Step 9:

[0447] Displays messages received by the device in the chat window.

[0448] (Robot Control)

[0449] Step 1:

[0450] The user selects a specific action (e.g., requesting event information) on the tablet device and clicks the send button.

[0451] Step 2:

[0452] The terminal sends the transmission content to the server.

[0453] Step 3:

[0454] The server sends the received request as a command to the appropriate robot.

[0455] Step 4:

[0456] The robot receives commands and performs the specified action (e.g., reading out information about an event).

[0457] Step 5:

[0458] The robot reports the results of its actions to the server.

[0459] Step 6:

[0460] The server checks the results of the operation and sends additional commands to the robot if necessary.

[0461] Step 7:

[0462] The terminal notifies the user that the robot's operation was successful.

[0463] These specific processing steps make communication between users in the cafe smooth and enjoyable, and the intervention of the emotion engine enables deeper communication.

[0464] Example 2

[0465] 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."

[0466] In existing social forums, communication between users is not smooth, and support for creating new interactions is insufficient. In particular, it is difficult to generate natural conversations in real time and respond with consideration for emotions. Furthermore, it is difficult to appropriately match users based on their interests, making it difficult to promote interactions with people who share their interests.

[0467] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0468] In this invention, the server includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a sentiment analysis means using a sentiment analysis engine, an AI model response generation means based on the sentiment analysis engine, and a robot control command means. This enables natural conversation between users, realizes responses that take emotions into consideration, and promotes effective matching based on common interests.

[0469] A "login authentication means" is a means for verifying the identity of a user when the user accesses a system.

[0470] "User profile management means" refers to a means by which a user can register and update their own interests and other information in the system.

[0471] The "means for generating conversation data" is a means for generating information necessary for conversation between users.

[0472] "User matching means" refers to a means for finding and matching users who share common interests based on user profile information.

[0473] "Real-time conversation management means" means means for controlling and managing a conversation in real time so that the conversation progresses continuously and fluently.

[0474] The "emotion analysis means using an emotion analysis engine" is a means for analyzing the user's emotions from the input message and outputting the results.

[0475] "A generative AI model response generation means based on an emotion analysis engine" is a means for generating an appropriate response based on the output of an emotion analysis engine.

[0476] The "robot control command means" is a means for sending specific commands to the robot and controlling its operation.

[0477] The present invention is a system for promoting communication between users in social settings such as cafes. The system includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a sentiment analysis means using a sentiment analysis engine, a generative AI model response generation means based on the sentiment analysis engine, and a robot control command means.

[0478] During the login process, the user operates a tablet device installed in the cafe to access the login page. After entering the required information such as their name and password, the user clicks the login button. The device sends the entered user information to the server, which then compares the received user information with its database. If authentication is successful, the server generates an authentication token and returns it to the device. The device saves the authentication token and displays a message to the user indicating that login was successful.

[0479] Next, after logging in, the user accesses a page to add or update profile information, including interests. The device sends the entered profile information to the server, which stores the received profile information in a database and uses it to match users with other users.

[0480] During the matching process, the server searches for and extracts users with common interests based on profile information in the database, and creates a matching list. The server then sends the matching list to each device, which receives it and displays it to the user. The user then selects the desired partner from the displayed list and presses the button to start chatting.

[0481] In real-time conversation generation, a user enters a message on the chat screen and clicks the send button. The device sends the entered message to the server, which receives the message and sends a request to the generative AI. The generative AI generates an appropriate response to the message and sends it back to the server. The server receives the returned message, formats it, and sends it to the device, which then displays the received message in the chat window.

[0482] The system also integrates a sentiment analysis engine. When a user types a message on the chat screen, the device sends the input to the server, which then sends the received message to the sentiment analysis engine, which analyzes the user's emotions. The sentiment analysis engine then sends the analysis results back to the server, and the generative AI adjusts the content and style of the reply based on the results. The server then sends the adjusted reply to the device, where it is displayed in the chat window.

[0483] As a concrete example, user A and user B visit a cafe and each log in. User A likes music, and user B likes movies. After logging in, their profile information is updated, and the server matches them based on their shared interest in "entertainment." Once matching is complete, the devices notify users A and B, and a chat begins. When user A types and sends the question, "What's a recent movie you recommend?", the server sends the message to the generative AI and the emotion analysis engine, and the emotion analysis engine detects user A's emotions of excitement and anticipation. Based on the results, the generative AI generates a response such as, "The recent movie I recommend is 'Inception.' It's an amazing movie!" and displays it on user B's device. In this way, the conversation between user A and user B becomes richer and more natural with the intervention of the emotion analysis engine.

[0484] It also controls robots. When a user selects and sends a specific action (e.g., requesting event information) from a tablet device, the device sends the request to the server. The server then sends the request as a control command to the appropriate robot, which then receives the command and performs the specified action (e.g., reading out event information). The robot then reports the results of its action to the server, which then notifies the device of the results.

[0485] Examples of prompts for generative AI models include:

[0486] "A user asks, 'What are some recent movie recommendations?' Generate an appropriate response."

[0487] "Based on the results of the sentiment analysis engine, generate responses that reflect the user's feelings of excitement and anticipation."

[0488] In this way, by implementing the system of the present invention, communication between users in the cafe becomes smooth and enjoyable, and the introduction of an emotion analysis engine enables even deeper communication.

[0489] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0490] Specific explanation of program processing

[0491] Step 1:

[0492] Login Process

[0493] Input: User information such as name and password

[0494] process:

[0495] 1. The user operates a tablet device in the cafe, enters their name and password, and clicks the login button.

[0496] 2. The terminal sends the entered user information to the server.

[0497] 3. The server checks the received user information against the information in its database.

[0498] 4. If the authentication is successful, the server generates an authentication token and returns it to the terminal.

[0499] 5. The device stores the authentication token and displays a successful login to the user.

[0500] Output: Authentication token and login result displayed

[0501] Specific examples of behavior:

[0502] The user enters "Yamada Taro" and "password123," and the device sends this information to the server. The server checks it against the database, and if it matches, it returns an authentication token called token12345, and the device displays "Login successful."

[0503] Step 2:

[0504] Profile Management

[0505] Input: Profile information such as interests

[0506] process:

[0507] 1. After logging in, the user visits the profile management page and enters or updates new information.

[0508] 2. The device sends the entered profile information to the server.

[0509] 3. The server stores the received profile information in a database and uses it for future matching.

[0510] Output: Updated profile information saved to database

[0511] Specific examples of behavior:

[0512] Users add interests such as "music, movies, reading" to their profile, and the device sends this information to the server, which stores it in a database.

[0513] Step 3:

[0514] User matching

[0515] Input: Profile information in the database

[0516] process:

[0517] 1. The server searches the profile information in the database and extracts users with common interests.

[0518] 2. The server generates a matching list based on the extraction results and sends it to each device.

[0519] 3. The device receives the matching list and displays it to the user.

[0520] 4. The user selects the desired partner and presses the chat start button.

[0521] Output: Match list and information displayed to the user

[0522] Specific examples of behavior:

[0523] The server matches user A and user B based on the common interests of "music and movies," and the device displays "A and B have been matched."

[0524] Step 4:

[0525] Real-time conversation generation

[0526] Input: The message entered by the user

[0527] process:

[0528] 1. The user enters a message in the chat screen and clicks the send button.

[0529] 2. The terminal sends the entered message to the server.

[0530] 3. The server sends the received message as a request to the generative AI model.

[0531] 4. The generative AI model generates an appropriate response to the message and sends it back to the server.

[0532] 5. The server formats the returned message and sends it to the terminal.

[0533] 6. The device will display the received message in the chat window.

[0534] Output: The generated reply message

[0535] Specific examples of behavior:

[0536] The user types "What are some recent recommended movies?", the device sends the message to the server, and the server sends the prompt "User asks about recent recommended movies" to the generative AI model. The generative AI model replies "The recent recommended movie is 'Inception'", which is displayed on the device via the server.

[0537] Step 5:

[0538] Sentiment analysis engine integration

[0539] Input: The message entered by the user

[0540] process:

[0541] 1. When a user enters a message on the chat screen, the device sends the content to the server.

[0542] 2. The server sends the received message to the sentiment analysis engine.

[0543] 3. The sentiment analysis engine analyzes the input message and detects the user's emotions.

[0544] 4. The sentiment analysis engine sends the analysis results back to the server, and the server sends a prompt based on the analysis results to the generative AI model.

[0545] 5. The generative AI model generates a tailored response based on the sentiment analysis results and sends it back to the server.

[0546] 6. The server sends this adjusted response to the device, which displays it in the chat window.

[0547] Output: Tailored response message based on sentiment analysis results

[0548] Specific examples of behavior:

[0549] A user excitedly types, "What's the best recent movie?" The sentiment analysis engine detects this excitement, and the generative AI model adjusts and responds, "The best recent movie is 'Inception.' It's an amazing movie!"

[0550] Step 6:

[0551] Robot Control

[0552] Input: User action selection (e.g., event information request)

[0553] process:

[0554] 1. The user selects and submits a specific action (e.g., requesting event information) on a tablet device.

[0555] 2. The device sends the selection to the server.

[0556] 3. The server sends the request as a control command to the appropriate robot.

[0557] 4. The robot receives the control command and performs the specified action (e.g., reading out an event announcement).

[0558] 5. The robot reports the results of its operation to the server, and the server notifies the terminal of the results.

[0559] Output: Robot operation results and notification

[0560] Specific examples of behavior:

[0561] When the user selects "I want to hear about the next event," the device sends a request to the server, and the server sends a command to the robot to "read out the event information." The robot reads out the information, reports to the server that "the event information has been read out," and notifies the device.

[0562] (Application example 2)

[0563] 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."

[0564] In today's social settings, it is difficult to foster communication between users and realize natural and rich conversations. Conventional systems lack the ability to match users based on their interests and generate appropriate conversations based on their emotions, presenting technical challenges for achieving deeper communication. Furthermore, to efficiently operate these functions in physical stores, it is necessary to integrate multiple technologies and improve the user experience.

[0565] 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.

[0566] In this invention, the server includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a robot control command means, an emotion analysis means, and an application means including chat conversations with users. This makes it possible to realize natural and rich communication by matching users with other users who share common interests based on their profile information and generating and adjusting conversation content that takes emotions into consideration using an emotion analysis engine.

[0567] The "login authentication means" is an authentication process used by a user to access the system, and involves inputting authentication information such as a user name and password to perform authentication.

[0568] "User profile management means" refers to a function for adding, updating, and managing profile information such as a user's interests.

[0569] "Means for generating conversational data" is a function that uses generative AI to generate appropriate responses based on messages entered by users.

[0570] "User matching means" is a function that searches for and extracts other users who share common interests based on the user's profile information, and creates a matching list.

[0571] "Real-time conversation management means" is a function that manages the sending and receiving of messages on the chat screen in real time, ensuring that conversations progress smoothly.

[0572] The "robot control command means" is a function that sends control commands to the robots in the cafe to cause them to perform specific actions, and manages the robots' operations.

[0573] The "emotion analysis means" is a function that analyzes messages entered by users and adjusts the content of conversations by detecting their emotions.

[0574] "Application means including chat conversations with users" refers to an application that is installed on a smartphone or tablet device and provides matching and chat functions between users.

[0575] The present invention is a system for promoting communication between users in social spaces such as cafes. The system includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a robot control command means, an emotion analysis means, and an application means including a chat conversation with a user.

[0576] Login authentication method

[0577] The user accesses the login page using a tablet device or smartphone installed in the cafe and enters their name and password to log in. The device sends the entered user information to the server, which then performs authentication and returns an authentication token if successful.

[0578] Profile Management Methods

[0579] After logging in, the user accesses a page for adding or updating profile information, including interests, and enters the profile information. The device sends the entered information to the server, which stores it in a database.

[0580] User matching method

[0581] The server searches for and extracts users with common interests based on the saved profile information, creates a matching list, and sends the matching list to each device, which then displays the list to the user.

[0582] Real-time conversation management

[0583] When a user enters and sends a message on the chat screen, the device sends the message to the server, which then sends the message to the generative AI model, which generates an appropriate response. The response is then adjusted by the sentiment analysis means and sent back to the device via the server.

[0584] Robot control command means

[0585] When a user sends a specific action (e.g., a request for event information), the device sends the request to the server, which then sends the request as a control command to the appropriate robot, which then performs the specified action.

[0586] Emotion analysis means

[0587] The sentiment analyzer analyzes messages entered by users to detect their emotions, and the server sends the results to a generative AI model to adjust the content and style of the reply, making the conversation more natural and rich.

[0588] Application means including chat conversations with users

[0589] Chat conversations are conducted through an application installed on smartphones and tablets, which provides comprehensive profile entry, matching, and chat functions.

[0590] Specific examples

[0591] For example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the device notifies Person A and Person B, and the chat begins.

[0592] When Person A types in "What recent movie would you recommend?" and submits it, the server uses emotion analysis to detect Person A's feelings of excitement and anticipation, and based on the results, the generative AI model generates a response saying, "The recent movie I recommend is 'Inception.' It's an absolutely amazing film!" and displays it on Person B's device.

[0593] Prompt Sentence Examples

[0594] What recent movies do you recommend?

[0595] What recent music albums do you recommend?

[0596] What's today's recommended cafe menu?

[0597] This will make communication between users in the cafe smooth and enjoyable, and the introduction of an emotion engine will enable even deeper communication.

[0598] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0599] Step 1:

[0600] The user accesses the login page using a tablet or smartphone installed in the cafe and logs in by entering their username and password. The device sends the entered authentication information to the server, which checks it against a database. If authentication is successful, the server issues an authentication token and returns it to the device. The authentication token is then displayed to the user.

[0601] Input: Username, Password

[0602] Data processing: Database matching of authentication information

[0603] Output: Authentication token

[0604] Step 2:

[0605] After logging in, users enter and update their profile information, including their interests. The device sends the entered profile information to the server, which stores it in a database.

[0606] Input: Profile information (interests, etc.)

[0607] Data processing: Profile information stored in a database

[0608] Output: Profile information update results

[0609] Step 3:

[0610] The server searches for and extracts users with common interests based on the saved profile information, creating a matching list. The server then sends the matching list to each device, which then displays it to the user.

[0611] Input: Profile information stored in the database

[0612] Data processing: Creating a matching list based on common interests

[0613] Output: Matching list

[0614] Step 4:

[0615] When a user enters a message on the chat screen and presses the send button, the device sends the message to the server. The server sends the message to a generative AI model, which generates an appropriate response. The generated response is then sent to a sentiment analysis means, where it is adjusted based on the user's emotions. The adjusted response is then sent back to the device via the server and displayed in the chat window.

[0616] Input: Chat message

[0617] Data processing: Response generation using generative AI models, adjustments using sentiment analysis methods

[0618] Output: Adjusted response

[0619] Step 5:

[0620] When a user requests a robot in a cafe to perform a specific action (e.g., an event announcement), the terminal sends the request to the server. The server then sends the request as a control command to the appropriate robot, which then executes the specified action. The robot then reports the results of its action to the server, which then notifies the terminal of the results.

[0621] Input: Request to the robot (e.g., event information)

[0622] Data processing: generating and transmitting robot control commands

[0623] Output: Robot movement results

[0624] For example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches them based on their shared interest in "entertainment," sending a notification to their device. User A then types, "What's a recommended recent movie?" The server's sentiment analysis engine analyzes this message, and the generative AI model generates a response: "The recommended recent movie is 'Inception.' It's an amazing movie!", which is displayed on Person B's device.

[0625] The above are the specific processing steps performed by this system.

[0626] 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.

[0627] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0628] 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.

[0629] [Second embodiment]

[0630] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0631] 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.

[0632] 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).

[0633] 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.

[0634] 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.

[0635] 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).

[0636] 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.

[0637] 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.

[0638] 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.

[0639] 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.

[0640] 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.

[0641] 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."

[0642] The present invention is a system for promoting communication between users in social spaces such as cafes. A specific embodiment of this system and the processing of the program will be described below.

[0643] The system mainly consists of the following components:

[0644] Login authentication method

[0645] User profile management means

[0646] Conversation data generation method

[0647] User matching method

[0648] Real-time conversation management

[0649] Robot control command means

[0650] Login Process

[0651] The user operates a tablet device installed in the cafe and accesses the login page. The user enters the required information such as name and password and clicks the login button.

[0652] The terminal transmits the input user information to the server.

[0653] The server checks the received user information against a database, and if authentication is successful, generates an authentication token and returns it to the terminal.

[0654] The device stores the authentication token and proceeds to the next step.

[0655] Profile Management

[0656] After logging in, users access a page where they can add or update their profile information, including their interests.

[0657] The terminal transmits the entered profile information to the server.

[0658] The server stores the received profile information in a database and uses it to match users with other users.

[0659] User matching

[0660] The server searches for and extracts users who share common interests based on the profile information of the logged-in user, adds the users to a matching list, and sends it to the device.

[0661] The terminal receives the matching list and displays it to the user.

[0662] The user selects a person with whom he or she wants to start a chat from the displayed list and presses the chat start button.

[0663] Real-time conversation generation

[0664] The user enters a message on the chat screen and clicks the send button.

[0665] The terminal transmits the input message to the server.

[0666] The server receives the message, analyzes it, and sends a request to the generative AI.

[0667] The generative AI generates an appropriate response to the message and sends it back to the server.

[0668] The server receives the generated response, formats it appropriately, and sends it to the chat partner's device.

[0669] The device will display the received message in the chat window.

[0670] Robot Control

[0671] The user selects a specific action (e.g., requesting event information) from the tablet device and sends a command.

[0672] The terminal transmits the command content to the server.

[0673] The server receives the commands and sends control commands to the appropriate robots.

[0674] The robot receives commands and performs the specified action (e.g., reading out event information).

[0675] The robot reports the results of its operations to the server, and the server notifies the terminal of the results.

[0676] Specific examples

[0677] For example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the device notifies Person A and Person B, and they begin chatting with each other.

[0678] When Person A types "What recent movies do you recommend?" into the chat and sends it, the server uses generative AI to generate an appropriate response, which is displayed on Person B's device. Furthermore, if Person A requests information about events, the robot will provide information about events currently being held in the cafe.

[0679] In this way, customers can communicate efficiently and enjoyably within the cafe and receive guidance from the robot.

[0680] The processing flow will be explained below.

[0681] (Login process)

[0682] Step 1:

[0683] The user operates a tablet device installed in the cafe and accesses the login page.

[0684] Step 2:

[0685] The user enters login information such as name and password and clicks the login button.

[0686] Step 3:

[0687] The terminal sends the entered login information to the server.

[0688] Step 4:

[0689] The server receives the login information and checks it against the user information in its database.

[0690] Step 5:

[0691] If the server is successful in the authentication, it generates an authentication token and sends it to the terminal.

[0692] Step 6:

[0693] The device stores the received authentication token and displays a message to the user indicating that the login was successful.

[0694] (Profile Management)

[0695] Step 1:

[0696] After the user logs in, they access the profile settings page.

[0697] Step 2:

[0698] The user enters their profile information, such as interests, and clicks the save button.

[0699] Step 3:

[0700] The device transmits the entered profile information to the server.

[0701] Step 4:

[0702] The server stores the received profile information in a database.

[0703] (User matching)

[0704] Step 1:

[0705] The server searches for users with common interests based on each user's profile information.

[0706] Step 2:

[0707] The server extracts the relevant users and creates a matching list.

[0708] Step 3:

[0709] The server sends the matching list to each device.

[0710] Step 4:

[0711] The terminal displays the received matching list to the user.

[0712] Step 5:

[0713] The user selects a chat partner from the displayed list and presses the chat start button.

[0714] (Generating real-time conversations)

[0715] Step 1:

[0716] The user enters a message in the chat screen and clicks the send button.

[0717] Step 2:

[0718] The terminal sends the input message to the server.

[0719] Step 3:

[0720] The server analyzes the received message and sends a request to the generative AI.

[0721] Step 4:

[0722] The generative AI generates an appropriate response to the message and sends it back to the server.

[0723] Step 5:

[0724] The server receives the returned message, formats it, and sends it to the terminal.

[0725] Step 6:

[0726] Displays messages received by the device in the chat window.

[0727] (Robot Control)

[0728] Step 1:

[0729] The user selects a specific action (e.g., requesting event information) on the tablet device and clicks the send button.

[0730] Step 2:

[0731] The terminal sends the transmission content to the server.

[0732] Step 3:

[0733] The server sends the received request as a command to the appropriate robot.

[0734] Step 4:

[0735] The robot receives commands and performs the specified action (e.g., reading out information about an event).

[0736] Step 5:

[0737] The robot reports the results of its actions to the server.

[0738] Step 6:

[0739] The server checks the results of the operation and sends additional commands to the robot if necessary.

[0740] Step 7:

[0741] The terminal notifies the user that the robot's operation was successful.

[0742] These steps will make communication between customers in the cafe smooth and enjoyable.

[0743] Example 1

[0744] 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."

[0745] In modern society, it is often difficult for users to naturally interact with each other, especially in social spaces such as cafes. Furthermore, there is a lack of mechanisms for users with different interests to communicate efficiently. As a result, users tend to feel isolated, and social spaces are not fully utilized. Furthermore, there is a need for a mechanism that allows smooth real-time conversations and the sharing of information.

[0746] 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.

[0747] In this invention, the server includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a means for a user to select a specific action and send a command, a robot control command means for a robot to receive the command and execute the action, and a means for generating a response to an input message using a generative AI model. This allows users to be efficiently matched based on shared interests and concerns, and appropriate responses are generated in real time using the generative AI model, enabling smooth communication and information provision.

[0748] A "login authentication method" is a mechanism for verifying and authenticating the authentication information (e.g., name and password) entered by a user when accessing a system.

[0749] "User profile management means" means a mechanism by which a user can enter and update their interests and other profile information and store it in a database.

[0750] The "means for generating conversation data" is a mechanism for analyzing and processing messages and conversation content entered by users and generating conversation data.

[0751] "User matching means" is a system that searches for and extracts users with common interests and concerns based on user profile information, and matches them together.

[0752] The "real-time conversation management means" is a mechanism for sending and receiving messages between users in real time and managing conversations.

[0753] "Means for users to select specific actions and send commands" refers to a mechanism by which users select specific actions using a tablet device or the like and send commands to the system.

[0754] The "robot control command means" is a mechanism for transmitting commands received by the system to an appropriate robot, which then executes the operation.

[0755] "Means for generating a response to a message input by a generative AI model" refers to a mechanism that uses a generative AI model (e.g., GPT-3) to generate an appropriate response to a message input by a user.

[0756] This system is designed to promote communication between users in social settings such as cafes. The system mainly consists of a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a means for users to select specific actions and send commands, a robot control command means, and a means for generating replies to input messages using a generative AI model.

[0757] First, the user operates a tablet device installed in the cafe to access the login page. The user enters the required information, such as their name and password, and clicks the login button. The device sends the entered user information to the server. The server compares the received user information with its database, and if authentication is successful, generates an authentication token and sends it back to the device. The device saves the authentication token and proceeds to the next step.

[0758] After logging in, the user accesses the profile page and adds or updates profile information, including interests. The device sends the entered profile information to the server, which stores the received profile information in a database.

[0759] The server searches for and extracts users who share common interests based on the profile information of the logged-in user. The server adds the matching users to a matching list and sends it to the device. The device receives the matching list and displays it to the user. The user then selects the person they want to chat with from the displayed list and presses the start chat button.

[0760] The user enters a message on the chat screen and clicks the send button. The device sends the entered message to the server. The server receives the message, analyzes it, and sends a request to a generative AI (such as OpenAI's GPT-3 model). The generative AI generates an appropriate response to the message and sends it back to the server. The server receives the generated response, formats it appropriately, and sends it to the device of the chat partner. The device displays the received message in the chat window.

[0761] The user can also select a specific action (e.g., requesting event information) from the tablet device and send a command. The device then sends the command to the server. The server receives the command and sends a control command to the appropriate robot. The robot then receives the command and performs the specified action (e.g., reading out event information). The robot then reports the results of its action to the server, which then notifies the device of the results.

[0762] As a concrete example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the device notifies Person A and Person B, and they begin chatting with each other.

[0763] When Person A types "What recent movies do you recommend?" into the chat and sends it, the server uses generative AI to generate an appropriate response, which is displayed on Person B's device. Furthermore, if Person A requests information about events, the robot will provide information about events currently being held in the cafe.

[0764] An example prompt is:

[0765] User Question:

[0766] "What recent movies would you recommend?"

[0767] AI response prompt:

[0768] "A recently released movie that has received particularly high praise is 'Movie Title'. This movie is 'Brief Movie Description'. You might enjoy it too."

[0769] In this way, customers can communicate efficiently and enjoyably within the cafe and receive guidance from the robot.

[0770] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0771] Step 1:

[0772] Users access the login page using a tablet device installed in the cafe.

[0773] Input: Login page on tablet device

[0774] Output: Login screen displayed

[0775] Specific operation: Tap the login icon on the device's home screen to display the login screen.

[0776] Step 2:

[0777] The user enters the required information such as name and password and clicks the login button.

[0778] Input: Name, Password

[0779] Output: Sending input information

[0780] Specific actions: Enter your name in the input field, then enter your password and tap the "Login" button.

[0781] Step 3:

[0782] The terminal transmits the input user information to the server.

[0783] Input: User name, password

[0784] Output: Request sent to server

[0785] Specific operation: When the login button is clicked, the device encrypts the data and sends it to the server using an HTTP POST request.

[0786] Step 4:

[0787] The server checks the received user information against a database, and if authentication is successful, generates an authentication token and returns it to the terminal.

[0788] Input: Username, Password

[0789] Output: Authentication token

[0790] Specific operation: The server queries the database, and if there is matching information, it generates a JWT (JSON Web Token) and sends it to the terminal.

[0791] Step 5:

[0792] The device stores the authentication token and proceeds to the next step.

[0793] Input: Authentication Token

[0794] Output: Authentication token saved

[0795] Specific operation: The received token is saved in local storage and prepared for the user's next operation.

[0796] Step 6:

[0797] After logging in, users access their profile page to add or update their profile information, including their interests.

[0798] Input: Interests, concerns

[0799] Output: Display of input information

[0800] Specific operation: Once you have logged in, a link to your profile page will appear; tap on it.

[0801] Step 7:

[0802] The terminal transmits the entered profile information to the server.

[0803] Input: Interests, concerns

[0804] Output: Request sent to server

[0805] Specific operation: Tap the submit button to send the information entered in the form to the server.

[0806] Step 8:

[0807] The server stores the received profile information in a database.

[0808] Input: Interests, concerns

[0809] Output: Save to database

[0810] Specific operation: The server inserts or updates the received data into the user profile table in the database.

[0811] Step 9:

[0812] The server searches for and extracts users who share common interests and concerns based on the profile information of the logged-in user.

[0813] Input: User profile information

[0814] Output: Matching list

[0815] What it does: The server filters other user profiles based on the user's areas of interest and generates a list of users with whom you have something in common.

[0816] Step 10:

[0817] The server sends the matching list to the terminal.

[0818] Input: Matching List

[0819] Output: Sending a request to the terminal

[0820] Specific operation: The generated list is sent to the terminal in JSON format.

[0821] Step 11:

[0822] The terminal receives the matching list and displays it to the user.

[0823] Input: Matching List

[0824] Output: Display list

[0825] Specific operation: When the list is received, it is reflected in the display UI and displayed in a format that is easy for the user to see.

[0826] Step 12:

[0827] The user selects a person with whom he or she wants to start a chat from the displayed list and presses the chat start button.

[0828] Input: List item

[0829] Output: Chat start request

[0830] What it does: Tap on the user's name in the list and click the "Start Chat" button.

[0831] Step 13:

[0832] The user enters a message on the chat screen and clicks the send button.

[0833] Input: Message text

[0834] Output: Message send request

[0835] Specific actions: Enter a message in the text box and press the "Send" button.

[0836] Step 14:

[0837] The terminal transmits the input message to the server.

[0838] Input: Message text

[0839] Output: Request sent to server

[0840] Specific operation: The message text is sent to the server using an HTTP POST request.

[0841] Step 15:

[0842] The server receives the message, analyzes it, and sends a request to the generative AI.

[0843] Input: Message text

[0844] Output: Send prompt to AI

[0845] Specific operation: Analyze the message content and generate and send an appropriate prompt to a generative AI (e.g., GPT-3).

[0846] Step 16:

[0847] The generative AI generates an appropriate response to the message and sends it back to the server.

[0848] Input: prompt

[0849] Output: The generated response

[0850] How it works: The AI ​​model generates a response based on the prompt, and the response is received by the server.

[0851] Step 17:

[0852] The server receives the generated response, formats it appropriately, and sends it to the chat partner's device.

[0853] Input: Generated response

[0854] Output: Sending a request to the terminal

[0855] Specific operation: The response is formatted as JSON and sent to the chat participant's device.

[0856] Step 18:

[0857] The device will display the received message in the chat window.

[0858] Input: Generated response

[0859] Output: Display message

[0860] Specific behavior: When a message is received, it is displayed in the UI and can be confirmed by the user.

[0861] Step 19:

[0862] The user selects a specific action from the tablet device and sends a command.

[0863] Input: Action selection

[0864] Output: Command transmission request

[0865] Specific actions: Select "Event Information" from the menu and press the send button.

[0866] Step 20:

[0867] The terminal transmits the command content to the server.

[0868] Input: Action command

[0869] Output: Request sent to server

[0870] Specific Operation: An HTTP request is used to send the selected command information to the server.

[0871] Step 21:

[0872] The server receives the commands and sends control commands to the appropriate robots.

[0873] Input: Command information

[0874] Output: Sending control commands to the robot

[0875] Specific operation: Analyzes the command content and sends the command to the necessary robot.

[0876] Step 22:

[0877] The robot receives commands and performs the specified actions.

[0878] Input: Control command

[0879] Output: Action execution

[0880] Specific Action: The robot moves to the designated area and performs the programmed action.

[0881] Step 23:

[0882] The robot reports the results of its operations to the server, and the server notifies the terminal of the results.

[0883] Input: Operation result

[0884] Output: Result notification

[0885] Specific operation: An operation completion report is sent to the server, and the server sends a notification to the user's terminal.

[0886] (Application example 1)

[0887] 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."

[0888] In social spaces such as cafes, there is a need for an efficient system to promote communication between users and to automate information about events and services within the cafe.In addition, there is a need for a system that can generate conversations between users in real time using smartphones and act as a mobile guide.

[0889] 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.

[0890] In this invention, the server includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a mobile control command means, and a mobile information terminal application execution means. This allows users to be easily matched based on their shared interests and concerns, enables real-time conversations using generative AI, and automates information about events and services in the cafe via a smartphone application.

[0891] The "login authentication means" is a means for a user to input authentication information required to access the system and verify the user's identity.

[0892] "User profile management means" means a means for entering and updating a user's interests and other personal information and storing it in a database.

[0893] The "means for generating conversation data" is a means for generating the content of conversation necessary to promote communication between users.

[0894] "User matching means" refers to a means for searching for and matching users who share common interests.

[0895] "Real-time conversation management means" refers to a means for managing and supporting conversations between users in real time.

[0896] The "mobile object control command means" is a means for controlling and instructing the operation of a mobile object (such as a robot) for purposes such as event announcements and service provision.

[0897] "Mobile information terminal application execution means" refers to means for executing applications that run on mobile information terminals such as smartphones and tablets.

[0898] A "generative AI model" is an artificial intelligence model that generates appropriate responses and information based on input text and data.

[0899] A "prompt sentence" is an input sentence to a generative AI model, and is an instruction sentence that enables the AI ​​to generate an appropriate response.

[0900] MODE FOR CARRYING OUT THE INVENTION

[0901] The present invention is a system for promoting communication between users in social spaces such as cafes and providing information about events and services available within the cafe. Specific embodiments of this system are described below.

[0902] Login Authentication

[0903] Users log in using a tablet device installed in the cafe or their own smartphone. The user information entered through the login authentication means is sent to the server, which then collates it with a database for authentication. If authentication is successful, an authentication token is returned to the device.

[0904] Profile Management

[0905] After logging in, users can add or update their profile information, including their interests. The device sends the entered profile information to the server, which stores it in a database. The stored data is then used to match users with other users.

[0906] User matching

[0907] The server searches for and extracts other users who share common interests based on the profile information of the logged-in user. Matching users are added to a matching list, which is sent to the device. The user then selects the person they want to chat with from the displayed list and presses the Start Chat button.

[0908] Real-time conversation generation

[0909] The user enters a message on the chat screen and clicks the send button. The device sends the message to the server, which then uses the generative AI model to generate an appropriate reply. The generated reply is sent from the server to the chat partner's device and displayed in the chat window.

[0910] Event Information

[0911] Users can request information about events taking place in the cafe via a tablet or smartphone. This command is sent to the server, which then uses the mobile control command means to instruct the robot based on the command, and the robot then performs the specified action, such as reading out information about the event. The results of the robot's actions are reported to the server, which then notifies the terminal of the results.

[0912] Hardware and software used

[0913] Hardware: Tablets, smartphones, robots, servers

[0914] Software: User profile management software, generative AI models (e.g., GPT-3), authentication systems, matching algorithms, real-time chat software

[0915] Specific examples

[0916] For example, Person A and Person B visit a cafe and log in from their respective smartphones. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the devices notify Person A and Person B, and they begin chatting with each other. When Person A types and sends "What movies do you recommend these days?" in the chat, the server uses a generative AI model to generate an appropriate response, which is displayed on Person B's device. Furthermore, if Person A requests information about events, the robot will provide information about events currently being held in the cafe.

[0917] Prompt Sentence Examples

[0918] Simply launch the SmartCafe Connect app, log in, and update your interest profile. Then, check your match list and start chatting with other users who share your interests. If you request event information, a robot in the cafe will guide you to the event.

[0919] Login name: User name

[0920] Password:Password

[0921] Interests: Music, movies

[0922] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0923] Step 1:

[0924] Login Authentication

[0925] The user accesses the login page using a tablet device installed in the cafe or their own smartphone and enters their name and password. The device sends this input information to the server. The server compares the received user information with a database, and if authentication is successful, it generates an authentication token and sends it back to the device. The device saves the authentication token and moves the user to the next step.

[0926] Input: User name, password

[0927] Output: Authentication token

[0928] Step 2:

[0929] Profile Management

[0930] After logging in, users access a page where they can enter and update their profile information, including their interests. The device sends the entered profile information to the server, which stores this information in a database and uses it to match users with other users.

[0931] Input: User profile information (interests, concerns)

[0932] Output: Profile information stored in a database

[0933] Step 3:

[0934] User matching

[0935] The server searches for other users who share common interests based on the logged-in user's profile information and adds those users to a matching list. This matching list is sent to the user's device, which then displays it to the user. The user selects the person they want to chat with from the displayed list and presses the start chat button.

[0936] Input: Profile information stored in the database

[0937] Output: Matching list

[0938] Step 4:

[0939] Real-time conversation generation

[0940] The user enters a message on the chat screen and clicks the send button. The device sends the entered message to the server, which analyzes the message and sends a request to the generative AI model. The generative AI model generates an appropriate response to the message and sends it back to the server. The server receives the generated response and sends it to the device of the chat partner. The device displays the received message in the chat window.

[0941] Input: User's message

[0942] Output: The response from the generative AI model

[0943] Step 5:

[0944] Event Information

[0945] A user requests a specific action, such as an event announcement, via a tablet or smartphone. The device sends this command to the server. The server receives the command and sends a control command to the robot using the mobile object control command means. The robot receives the command and performs the specified action (e.g., reading out an event announcement). The robot reports the results of its action to the server, which then notifies the device of the result.

[0946] Input: User's event information request

[0947] Output: Event information by robot

[0948] Specific behavior:

[0949] Server: User authentication, storing information in a database, matching, requests to the generative AI model, sending vehicle control commands

[0950] Device: Sending user input, storing authentication tokens, displaying match lists, sending and receiving chat messages

[0951] Users: Log in, enter profile information, use chat, and send event invitation requests

[0952] Robot: Event guide execution 34,,

[0953] 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.

[0954] The present invention is a system for promoting communication between users in social spaces such as cafes. The system includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a robot control command means, and an emotion engine.

[0955] Specific embodiments of the system and program processing will be described below.

[0956] Login Process

[0957] The user operates a tablet device installed in the cafe and accesses the login page. The user enters the required information such as name and password and clicks the login button.

[0958] The terminal transmits the input user information to the server.

[0959] The server checks the received user information against a database, and if authentication is successful, generates an authentication token and returns it to the terminal.

[0960] The terminal stores the authentication token and displays a successful login to the user.

[0961] Profile Management

[0962] After logging in, users access a page where they can add or update their profile information, including their interests.

[0963] The terminal transmits the entered profile information to the server.

[0964] The server stores the received profile information in a database and uses it to match users with other users.

[0965] User matching

[0966] Based on the profile information mentioned above, the server searches and extracts users with common interests and creates a matching list.

[0967] The server sends the matching list to each terminal.

[0968] The terminal receives the matching list and displays it to the user.

[0969] The user selects the desired partner from the displayed list and presses the chat start button.

[0970] Real-time conversation generation

[0971] The user enters a message on the chat screen and clicks the send button.

[0972] The terminal transmits the input message to the server.

[0973] The server receives the message and sends a request to the generative AI.

[0974] The generative AI generates an appropriate response to the message and sends it back to the server.

[0975] The server receives the returned message, formats it, and sends it to the terminal.

[0976] The device will display the received message in the chat window.

[0977] Emotion engine integration

[0978] When a user inputs a message on the chat screen, the terminal transmits the input content to the server.

[0979] The server sends the received message to the emotion engine to analyze the user's emotions.

[0980] The emotion engine sends the analysis results back to the server, and the generative AI adjusts the content and style of the response based on those results.

[0981] The server sends the tailored response to the device, which displays it in the chat window.

[0982] As a concrete example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the device notifies Person A and Person B, and they begin chatting.

[0983] When Person A types in and sends "What recent movie do you recommend?", the server sends the message to the generative AI and emotion engine, and the emotion engine detects Person A's feelings of excitement and anticipation. Based on the results, the generative AI generates a response such as "The recent movie I recommend is 'Inception.' It's an amazing movie!" and displays it on Person B's device. In this way, the conversation between Person A and Person B becomes richer and more natural with the intervention of the emotion engine.

[0984] Robot Control

[0985] The user selects and sends a specific action (e.g., requesting event information) from the tablet device.

[0986] The terminal transmits the transmission contents to the server.

[0987] The server sends the request as a control command to the appropriate robot.

[0988] The robot receives commands and performs the specified action (e.g., reading out event information).

[0989] The robot reports the results of its operations to the server, and the server notifies the terminal of the results.

[0990] In this way, by implementing the system of the present invention, communication between users in a cafe becomes smooth and enjoyable, and the introduction of an emotion engine enables even deeper communication.

[0991] The processing flow will be explained below.

[0992] (Login process)

[0993] Step 1:

[0994] The user operates a tablet device installed in the cafe and accesses the login page.

[0995] Step 2:

[0996] The user enters login information such as name and password and clicks the login button.

[0997] Step 3:

[0998] The terminal sends the entered login information to the server.

[0999] Step 4:

[1000] The server receives the login information and checks it against the user information in its database.

[1001] Step 5:

[1002] If the server is successful in the authentication, it generates an authentication token and sends it to the terminal.

[1003] Step 6:

[1004] The terminal stores the received authentication token and displays a successful login to the user.

[1005] (Profile Management)

[1006] Step 1:

[1007] After the user logs in, they access the profile settings page.

[1008] Step 2:

[1009] The user enters their profile information, such as interests, and clicks the save button.

[1010] Step 3:

[1011] The device transmits the entered profile information to the server.

[1012] Step 4:

[1013] The server stores the received profile information in a database.

[1014] (User matching)

[1015] Step 1:

[1016] The server searches for users with common interests based on each user's profile information.

[1017] Step 2:

[1018] The server extracts the relevant users and creates a matching list.

[1019] Step 3:

[1020] The server sends the matching list to each device.

[1021] Step 4:

[1022] The terminal displays the received matching list to the user.

[1023] Step 5:

[1024] The user selects a chat partner from the displayed list and presses the chat start button.

[1025] (Generating real-time conversations)

[1026] Step 1:

[1027] The user enters a message in the chat screen and clicks the send button.

[1028] Step 2:

[1029] The terminal sends the input message to the server.

[1030] Step 3:

[1031] The server analyzes the received message and sends a request to the generative AI.

[1032] Step 4:

[1033] The generative AI generates an appropriate response to the message and sends it back to the server.

[1034] Step 5:

[1035] The server receives the returned message, formats it, and sends it to the terminal.

[1036] Step 6:

[1037] Displays messages received by the device in the chat window.

[1038] (Emotion engine integration)

[1039] Step 1:

[1040] The user enters a message in the chat screen and clicks the send button.

[1041] Step 2:

[1042] The terminal sends the input message to the server.

[1043] Step 3:

[1044] The server sends the received message to the emotion engine.

[1045] Step 4:

[1046] An emotion engine analyzes the message and identifies the user's emotion.

[1047] Step 5:

[1048] The emotion engine sends the analysis results back to the server.

[1049] Step 6:

[1050] The server requests the generative AI to generate a message based on the results of the emotion engine.

[1051] Step 7:

[1052] The generative AI generates an appropriate response based on the emotion and sends it back to the server.

[1053] Step 8:

[1054] The server receives the returned message, formats it, and sends it to the terminal.

[1055] Step 9:

[1056] Displays messages received by the device in the chat window.

[1057] (Robot Control)

[1058] Step 1:

[1059] The user selects a specific action (e.g., requesting event information) on the tablet device and clicks the send button.

[1060] Step 2:

[1061] The terminal sends the transmission content to the server.

[1062] Step 3:

[1063] The server sends the received request as a command to the appropriate robot.

[1064] Step 4:

[1065] The robot receives commands and performs the specified action (e.g., reading out information about an event).

[1066] Step 5:

[1067] The robot reports the results of its actions to the server.

[1068] Step 6:

[1069] The server checks the results of the operation and sends additional commands to the robot if necessary.

[1070] Step 7:

[1071] The terminal notifies the user that the robot's operation was successful.

[1072] These specific processing steps make communication between users in the cafe smooth and enjoyable, and the intervention of the emotion engine enables deeper communication.

[1073] Example 2

[1074] 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."

[1075] In existing social forums, communication between users is not smooth, and support for creating new interactions is insufficient. In particular, it is difficult to generate natural conversations in real time and respond with consideration for emotions. Furthermore, it is difficult to appropriately match users based on their interests, making it difficult to promote interactions with people who share their interests.

[1076] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1077] In this invention, the server includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a sentiment analysis means using a sentiment analysis engine, an AI model response generation means based on the sentiment analysis engine, and a robot control command means. This enables natural conversation between users, realizes responses that take emotions into consideration, and promotes effective matching based on common interests.

[1078] A "login authentication means" is a means for verifying the identity of a user when the user accesses a system.

[1079] "User profile management means" refers to a means by which a user can register and update their own interests and other information in the system.

[1080] The "means for generating conversation data" is a means for generating information necessary for conversation between users.

[1081] "User matching means" refers to a means for finding and matching users who share common interests based on user profile information.

[1082] "Real-time conversation management means" means means for controlling and managing a conversation in real time so that the conversation progresses continuously and fluently.

[1083] The "emotion analysis means using an emotion analysis engine" is a means for analyzing the user's emotions from the input message and outputting the results.

[1084] "A generative AI model response generation means based on an emotion analysis engine" is a means for generating an appropriate response based on the output of an emotion analysis engine.

[1085] The "robot control command means" is a means for sending specific commands to the robot and controlling its operation.

[1086] The present invention is a system for promoting communication between users in social settings such as cafes. The system includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a sentiment analysis means using a sentiment analysis engine, a generative AI model response generation means based on the sentiment analysis engine, and a robot control command means.

[1087] During the login process, the user operates a tablet device installed in the cafe to access the login page. After entering the required information such as their name and password, the user clicks the login button. The device sends the entered user information to the server, which then compares the received user information with its database. If authentication is successful, the server generates an authentication token and returns it to the device. The device saves the authentication token and displays a message to the user indicating that login was successful.

[1088] Next, after logging in, the user accesses a page to add or update profile information, including interests. The device sends the entered profile information to the server, which stores the received profile information in a database and uses it to match users with other users.

[1089] During the matching process, the server searches for and extracts users with common interests based on profile information in the database, and creates a matching list. The server then sends the matching list to each device, which receives it and displays it to the user. The user then selects the desired partner from the displayed list and presses the button to start chatting.

[1090] In real-time conversation generation, a user enters a message on the chat screen and clicks the send button. The device sends the entered message to the server, which receives the message and sends a request to the generative AI. The generative AI generates an appropriate response to the message and sends it back to the server. The server receives the returned message, formats it, and sends it to the device, which then displays the received message in the chat window.

[1091] The system also integrates a sentiment analysis engine. When a user types a message on the chat screen, the device sends the input to the server, which then sends the received message to the sentiment analysis engine, which analyzes the user's emotions. The sentiment analysis engine then sends the analysis results back to the server, and the generative AI adjusts the content and style of the reply based on the results. The server then sends the adjusted reply to the device, where it is displayed in the chat window.

[1092] As a concrete example, user A and user B visit a cafe and each log in. User A likes music, and user B likes movies. After logging in, their profile information is updated, and the server matches them based on their shared interest in "entertainment." Once matching is complete, the devices notify users A and B, and a chat begins. When user A types and sends the question, "What's a recent movie you recommend?", the server sends the message to the generative AI and the emotion analysis engine, and the emotion analysis engine detects user A's emotions of excitement and anticipation. Based on the results, the generative AI generates a response such as, "The recent movie I recommend is 'Inception.' It's an amazing movie!" and displays it on user B's device. In this way, the conversation between user A and user B becomes richer and more natural with the intervention of the emotion analysis engine.

[1093] It also controls robots. When a user selects and sends a specific action (e.g., requesting event information) from a tablet device, the device sends the request to the server. The server then sends the request as a control command to the appropriate robot, which then receives the command and performs the specified action (e.g., reading out event information). The robot then reports the results of its action to the server, which then notifies the device of the results.

[1094] Examples of prompts for generative AI models include:

[1095] "A user asks, 'What are some recent movie recommendations?' Generate an appropriate response."

[1096] "Based on the results of the sentiment analysis engine, generate responses that reflect the user's feelings of excitement and anticipation."

[1097] In this way, by implementing the system of the present invention, communication between users in the cafe becomes smooth and enjoyable, and the introduction of an emotion analysis engine enables even deeper communication.

[1098] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1099] Specific explanation of program processing

[1100] Step 1:

[1101] Login Process

[1102] Input: User information such as name and password

[1103] process:

[1104] 1. The user operates a tablet device in the cafe, enters their name and password, and clicks the login button.

[1105] 2. The terminal sends the entered user information to the server.

[1106] 3. The server checks the received user information against the information in its database.

[1107] 4. If the authentication is successful, the server generates an authentication token and returns it to the terminal.

[1108] 5. The device stores the authentication token and displays a successful login to the user.

[1109] Output: Authentication token and login result displayed

[1110] Specific examples of behavior:

[1111] The user enters "Yamada Taro" and "password123," and the device sends this information to the server. The server checks it against the database, and if it matches, it returns an authentication token called token12345, and the device displays "Login successful."

[1112] Step 2:

[1113] Profile Management

[1114] Input: Profile information such as interests

[1115] process:

[1116] 1. After logging in, the user visits the profile management page and enters or updates new information.

[1117] 2. The device sends the entered profile information to the server.

[1118] 3. The server stores the received profile information in a database and uses it for future matching.

[1119] Output: Updated profile information saved to database

[1120] Specific examples of behavior:

[1121] Users add interests such as "music, movies, reading" to their profile, and the device sends this information to the server, which stores it in a database.

[1122] Step 3:

[1123] User matching

[1124] Input: Profile information in the database

[1125] process:

[1126] 1. The server searches the profile information in the database and extracts users with common interests.

[1127] 2. The server generates a matching list based on the extraction results and sends it to each device.

[1128] 3. The device receives the matching list and displays it to the user.

[1129] 4. The user selects the desired partner and presses the chat start button.

[1130] Output: Match list and information displayed to the user

[1131] Specific examples of behavior:

[1132] The server matches user A and user B based on the common interests of "music and movies," and the device displays "A and B have been matched."

[1133] Step 4:

[1134] Real-time conversation generation

[1135] Input: The message entered by the user

[1136] process:

[1137] 1. The user enters a message in the chat screen and clicks the send button.

[1138] 2. The terminal sends the entered message to the server.

[1139] 3. The server sends the received message as a request to the generative AI model.

[1140] 4. The generative AI model generates an appropriate response to the message and sends it back to the server.

[1141] 5. The server formats the returned message and sends it to the terminal.

[1142] 6. The device will display the received message in the chat window.

[1143] Output: The generated reply message

[1144] Specific examples of behavior:

[1145] The user types "What are some recent recommended movies?", the device sends the message to the server, and the server sends the prompt "User asks about recent recommended movies" to the generative AI model. The generative AI model replies "The recent recommended movie is 'Inception'", which is displayed on the device via the server.

[1146] Step 5:

[1147] Sentiment analysis engine integration

[1148] Input: The message entered by the user

[1149] process:

[1150] 1. When a user enters a message on the chat screen, the device sends the content to the server.

[1151] 2. The server sends the received message to the sentiment analysis engine.

[1152] 3. The sentiment analysis engine analyzes the input message and detects the user's emotions.

[1153] 4. The sentiment analysis engine sends the analysis results back to the server, and the server sends a prompt based on the analysis results to the generative AI model.

[1154] 5. The generative AI model generates a tailored response based on the sentiment analysis results and sends it back to the server.

[1155] 6. The server sends this adjusted response to the device, which displays it in the chat window.

[1156] Output: Tailored response message based on sentiment analysis results

[1157] Specific examples of behavior:

[1158] A user excitedly types, "What's the best recent movie?" The sentiment analysis engine detects this excitement, and the generative AI model adjusts and responds, "The best recent movie is 'Inception.' It's an amazing movie!"

[1159] Step 6:

[1160] Robot Control

[1161] Input: User action selection (e.g., event information request)

[1162] process:

[1163] 1. The user selects and submits a specific action (e.g., requesting event information) on a tablet device.

[1164] 2. The device sends the selection to the server.

[1165] 3. The server sends the request as a control command to the appropriate robot.

[1166] 4. The robot receives the control command and performs the specified action (e.g., reading out an event announcement).

[1167] 5. The robot reports the results of its operation to the server, and the server notifies the terminal of the results.

[1168] Output: Robot operation results and notification

[1169] Specific examples of behavior:

[1170] When the user selects "I want to hear about the next event," the device sends a request to the server, and the server sends a command to the robot to "read out the event information." The robot reads out the information, reports to the server that "the event information has been read out," and notifies the device.

[1171] (Application example 2)

[1172] 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."

[1173] In today's social settings, it is difficult to foster communication between users and realize natural and rich conversations. Conventional systems lack the ability to match users based on their interests and generate appropriate conversations based on their emotions, presenting technical challenges for achieving deeper communication. Furthermore, to efficiently operate these functions in physical stores, it is necessary to integrate multiple technologies and improve the user experience.

[1174] 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.

[1175] In this invention, the server includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a robot control command means, an emotion analysis means, and an application means including chat conversations with users. This makes it possible to realize natural and rich communication by matching users with other users who share common interests based on their profile information and generating and adjusting conversation content that takes emotions into consideration using an emotion analysis engine.

[1176] The "login authentication means" is an authentication process used by a user to access the system, and involves inputting authentication information such as a user name and password to perform authentication.

[1177] "User profile management means" refers to a function for adding, updating, and managing profile information such as a user's interests.

[1178] "Means for generating conversational data" is a function that uses generative AI to generate appropriate responses based on messages entered by users.

[1179] "User matching means" is a function that searches for and extracts other users who share common interests based on the user's profile information, and creates a matching list.

[1180] "Real-time conversation management means" is a function that manages the sending and receiving of messages on the chat screen in real time, ensuring that conversations progress smoothly.

[1181] The "robot control command means" is a function that sends control commands to the robots in the cafe to cause them to perform specific actions, and manages the robots' operations.

[1182] The "emotion analysis means" is a function that analyzes messages entered by users and adjusts the content of conversations by detecting their emotions.

[1183] "Application means including chat conversations with users" refers to an application that is installed on a smartphone or tablet device and provides matching and chat functions between users.

[1184] The present invention is a system for promoting communication between users in social spaces such as cafes. The system includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a robot control command means, an emotion analysis means, and an application means including a chat conversation with a user.

[1185] Login authentication method

[1186] The user accesses the login page using a tablet device or smartphone installed in the cafe and enters their name and password to log in. The device sends the entered user information to the server, which then performs authentication and returns an authentication token if successful.

[1187] Profile Management Methods

[1188] After logging in, the user accesses a page for adding or updating profile information, including interests, and enters the profile information. The device sends the entered information to the server, which stores it in a database.

[1189] User matching method

[1190] The server searches for and extracts users with common interests based on the saved profile information, creates a matching list, and sends the matching list to each device, which then displays the list to the user.

[1191] Real-time conversation management

[1192] When a user enters and sends a message on the chat screen, the device sends the message to the server, which then sends the message to the generative AI model, which generates an appropriate response. The response is then adjusted by the sentiment analysis means and sent back to the device via the server.

[1193] Robot control command means

[1194] When a user sends a specific action (e.g., a request for event information), the device sends the request to the server, which then sends the request as a control command to the appropriate robot, which then performs the specified action.

[1195] Emotion analysis means

[1196] The sentiment analyzer analyzes messages entered by users to detect their emotions, and the server sends the results to a generative AI model to adjust the content and style of the reply, making the conversation more natural and rich.

[1197] Application means including chat conversations with users

[1198] Chat conversations are conducted through an application installed on smartphones and tablets, which provides comprehensive profile entry, matching, and chat functions.

[1199] Specific examples

[1200] For example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the device notifies Person A and Person B, and the chat begins.

[1201] When Person A types in "What recent movie would you recommend?" and submits it, the server uses emotion analysis to detect Person A's feelings of excitement and anticipation, and based on the results, the generative AI model generates a response saying, "The recent movie I recommend is 'Inception.' It's an absolutely amazing film!" and displays it on Person B's device.

[1202] Prompt Sentence Examples

[1203] What recent movies do you recommend?

[1204] What recent music albums do you recommend?

[1205] What's today's recommended cafe menu?

[1206] This will make communication between users in the cafe smooth and enjoyable, and the introduction of an emotion engine will enable even deeper communication.

[1207] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1208] Step 1:

[1209] The user accesses the login page using a tablet or smartphone installed in the cafe and logs in by entering their username and password. The device sends the entered authentication information to the server, which checks it against a database. If authentication is successful, the server issues an authentication token and returns it to the device. The authentication token is then displayed to the user.

[1210] Input: Username, Password

[1211] Data processing: Database matching of authentication information

[1212] Output: Authentication token

[1213] Step 2:

[1214] After logging in, users enter and update their profile information, including their interests. The device sends the entered profile information to the server, which stores it in a database.

[1215] Input: Profile information (interests, etc.)

[1216] Data processing: Profile information stored in a database

[1217] Output: Profile information update results

[1218] Step 3:

[1219] The server searches for and extracts users with common interests based on the saved profile information, creating a matching list. The server then sends the matching list to each device, which then displays it to the user.

[1220] Input: Profile information stored in the database

[1221] Data processing: Creating a matching list based on common interests

[1222] Output: Matching list

[1223] Step 4:

[1224] When a user enters a message on the chat screen and presses the send button, the device sends the message to the server. The server sends the message to a generative AI model, which generates an appropriate response. The generated response is then sent to a sentiment analysis means, where it is adjusted based on the user's emotions. The adjusted response is then sent back to the device via the server and displayed in the chat window.

[1225] Input: Chat message

[1226] Data processing: Response generation using generative AI models, adjustments using sentiment analysis methods

[1227] Output: Adjusted response

[1228] Step 5:

[1229] When a user requests a robot in a cafe to perform a specific action (e.g., an event announcement), the terminal sends the request to the server. The server then sends the request as a control command to the appropriate robot, which then executes the specified action. The robot then reports the results of its action to the server, which then notifies the terminal of the results.

[1230] Input: Request to the robot (e.g., event information)

[1231] Data processing: generating and transmitting robot control commands

[1232] Output: Robot movement results

[1233] For example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches them based on their shared interest in "entertainment," sending a notification to their device. User A then types, "What's a recommended recent movie?" The server's sentiment analysis engine analyzes this message, and the generative AI model generates a response: "The recommended recent movie is 'Inception.' It's an amazing movie!", which is displayed on Person B's device.

[1234] The above are the specific processing steps performed by this system.

[1235] 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.

[1236] 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.

[1237] 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.

[1238] [Third embodiment]

[1239] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1240] 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.

[1241] 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).

[1242] 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.

[1243] 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.

[1244] 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).

[1245] 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.

[1246] 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.

[1247] 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.

[1248] 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.

[1249] 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.

[1250] 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."

[1251] The present invention is a system for promoting communication between users in social spaces such as cafes. A specific embodiment of this system and the processing of the program will be described below.

[1252] The system mainly consists of the following components:

[1253] Login authentication method

[1254] User profile management means

[1255] Conversation data generation method

[1256] User matching method

[1257] Real-time conversation management

[1258] Robot control command means

[1259] Login Process

[1260] The user operates a tablet device installed in the cafe and accesses the login page. The user enters the required information such as name and password and clicks the login button.

[1261] The terminal transmits the input user information to the server.

[1262] The server checks the received user information against a database, and if authentication is successful, generates an authentication token and returns it to the terminal.

[1263] The device stores the authentication token and proceeds to the next step.

[1264] Profile Management

[1265] After logging in, users access a page where they can add or update their profile information, including their interests.

[1266] The terminal transmits the entered profile information to the server.

[1267] The server stores the received profile information in a database and uses it to match users with other users.

[1268] User matching

[1269] The server searches for and extracts users who share common interests based on the profile information of the logged-in user, adds the users to a matching list, and sends it to the device.

[1270] The terminal receives the matching list and displays it to the user.

[1271] The user selects a person with whom he or she wants to start a chat from the displayed list and presses the chat start button.

[1272] Real-time conversation generation

[1273] The user enters a message on the chat screen and clicks the send button.

[1274] The terminal transmits the input message to the server.

[1275] The server receives the message, analyzes it, and sends a request to the generative AI.

[1276] The generative AI generates an appropriate response to the message and sends it back to the server.

[1277] The server receives the generated response, formats it appropriately, and sends it to the chat partner's device.

[1278] The device will display the received message in the chat window.

[1279] Robot Control

[1280] The user selects a specific action (e.g., requesting event information) from the tablet device and sends a command.

[1281] The terminal transmits the command content to the server.

[1282] The server receives the commands and sends control commands to the appropriate robots.

[1283] The robot receives commands and performs the specified action (e.g., reading out event information).

[1284] The robot reports the results of its operations to the server, and the server notifies the terminal of the results.

[1285] Specific examples

[1286] For example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the device notifies Person A and Person B, and they begin chatting with each other.

[1287] When Person A types "What recent movies do you recommend?" into the chat and sends it, the server uses generative AI to generate an appropriate response, which is displayed on Person B's device. Furthermore, if Person A requests information about events, the robot will provide information about events currently being held in the cafe.

[1288] In this way, customers can communicate efficiently and enjoyably within the cafe and receive guidance from the robot.

[1289] The processing flow will be explained below.

[1290] (Login process)

[1291] Step 1:

[1292] The user operates a tablet device installed in the cafe and accesses the login page.

[1293] Step 2:

[1294] The user enters login information such as name and password and clicks the login button.

[1295] Step 3:

[1296] The terminal sends the entered login information to the server.

[1297] Step 4:

[1298] The server receives the login information and checks it against the user information in its database.

[1299] Step 5:

[1300] If the server is successful in the authentication, it generates an authentication token and sends it to the terminal.

[1301] Step 6:

[1302] The device stores the received authentication token and displays a message to the user indicating that the login was successful.

[1303] (Profile Management)

[1304] Step 1:

[1305] After the user logs in, they access the profile settings page.

[1306] Step 2:

[1307] The user enters their profile information, such as interests, and clicks the save button.

[1308] Step 3:

[1309] The device transmits the entered profile information to the server.

[1310] Step 4:

[1311] The server stores the received profile information in a database.

[1312] (User matching)

[1313] Step 1:

[1314] The server searches for users with common interests based on each user's profile information.

[1315] Step 2:

[1316] The server extracts the relevant users and creates a matching list.

[1317] Step 3:

[1318] The server sends the matching list to each device.

[1319] Step 4:

[1320] The terminal displays the received matching list to the user.

[1321] Step 5:

[1322] The user selects a chat partner from the displayed list and presses the chat start button.

[1323] (Generating real-time conversations)

[1324] Step 1:

[1325] The user enters a message in the chat screen and clicks the send button.

[1326] Step 2:

[1327] The terminal sends the input message to the server.

[1328] Step 3:

[1329] The server analyzes the received message and sends a request to the generative AI.

[1330] Step 4:

[1331] The generative AI generates an appropriate response to the message and sends it back to the server.

[1332] Step 5:

[1333] The server receives the returned message, formats it, and sends it to the terminal.

[1334] Step 6:

[1335] Displays messages received by the device in the chat window.

[1336] (Robot Control)

[1337] Step 1:

[1338] The user selects a specific action (e.g., requesting event information) on the tablet device and clicks the send button.

[1339] Step 2:

[1340] The terminal sends the transmission content to the server.

[1341] Step 3:

[1342] The server sends the received request as a command to the appropriate robot.

[1343] Step 4:

[1344] The robot receives commands and performs the specified action (e.g., reading out information about an event).

[1345] Step 5:

[1346] The robot reports the results of its actions to the server.

[1347] Step 6:

[1348] The server checks the results of the operation and sends additional commands to the robot if necessary.

[1349] Step 7:

[1350] The terminal notifies the user that the robot's operation was successful.

[1351] These steps will make communication between customers in the cafe smooth and enjoyable.

[1352] Example 1

[1353] 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."

[1354] In modern society, it is often difficult for users to naturally interact with each other, especially in social spaces such as cafes. Furthermore, there is a lack of mechanisms for users with different interests to communicate efficiently. As a result, users tend to feel isolated, and social spaces are not fully utilized. Furthermore, there is a need for a mechanism that allows smooth real-time conversations and the sharing of information.

[1355] 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.

[1356] In this invention, the server includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a means for a user to select a specific action and send a command, a robot control command means for a robot to receive the command and execute the action, and a means for generating a response to an input message using a generative AI model. This allows users to be efficiently matched based on shared interests and concerns, and appropriate responses are generated in real time using the generative AI model, enabling smooth communication and information provision.

[1357] A "login authentication method" is a mechanism for verifying and authenticating the authentication information (e.g., name and password) entered by a user when accessing a system.

[1358] "User profile management means" means a mechanism by which a user can enter and update their interests and other profile information and store it in a database.

[1359] The "means for generating conversation data" is a mechanism for analyzing and processing messages and conversation content entered by users and generating conversation data.

[1360] "User matching means" is a system that searches for and extracts users with common interests and concerns based on user profile information, and matches them together.

[1361] The "real-time conversation management means" is a mechanism for sending and receiving messages between users in real time and managing conversations.

[1362] "Means for users to select specific actions and send commands" refers to a mechanism by which users select specific actions using a tablet device or the like and send commands to the system.

[1363] The "robot control command means" is a mechanism for transmitting commands received by the system to an appropriate robot, which then executes the operation.

[1364] "Means for generating a response to a message input by a generative AI model" refers to a mechanism that uses a generative AI model (e.g., GPT-3) to generate an appropriate response to a message input by a user.

[1365] This system is designed to promote communication between users in social settings such as cafes. The system mainly consists of a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a means for users to select specific actions and send commands, a robot control command means, and a means for generating replies to input messages using a generative AI model.

[1366] First, the user operates a tablet device installed in the cafe to access the login page. The user enters the required information, such as their name and password, and clicks the login button. The device sends the entered user information to the server. The server compares the received user information with its database, and if authentication is successful, generates an authentication token and sends it back to the device. The device saves the authentication token and proceeds to the next step.

[1367] After logging in, the user accesses the profile page and adds or updates profile information, including interests. The device sends the entered profile information to the server, which stores the received profile information in a database.

[1368] The server searches for and extracts users who share common interests based on the profile information of the logged-in user. The server adds the matching users to a matching list and sends it to the device. The device receives the matching list and displays it to the user. The user then selects the person they want to chat with from the displayed list and presses the start chat button.

[1369] The user enters a message on the chat screen and clicks the send button. The device sends the entered message to the server. The server receives the message, analyzes it, and sends a request to a generative AI (such as OpenAI's GPT-3 model). The generative AI generates an appropriate response to the message and sends it back to the server. The server receives the generated response, formats it appropriately, and sends it to the device of the chat partner. The device displays the received message in the chat window.

[1370] The user can also select a specific action (e.g., requesting event information) from the tablet device and send a command. The device then sends the command to the server. The server receives the command and sends a control command to the appropriate robot. The robot then receives the command and performs the specified action (e.g., reading out event information). The robot then reports the results of its action to the server, which then notifies the device of the results.

[1371] As a concrete example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the device notifies Person A and Person B, and they begin chatting with each other.

[1372] When Person A types "What recent movies do you recommend?" into the chat and sends it, the server uses generative AI to generate an appropriate response, which is displayed on Person B's device. Furthermore, if Person A requests information about events, the robot will provide information about events currently being held in the cafe.

[1373] An example prompt is:

[1374] User Question:

[1375] "What recent movies would you recommend?"

[1376] AI response prompt:

[1377] "A recently released movie that has received particularly high praise is 'Movie Title'. This movie is 'Brief Movie Description'. You might enjoy it too."

[1378] In this way, customers can communicate efficiently and enjoyably within the cafe and receive guidance from the robot.

[1379] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1380] Step 1:

[1381] Users access the login page using a tablet device installed in the cafe.

[1382] Input: Login page on tablet device

[1383] Output: Login screen displayed

[1384] Specific operation: Tap the login icon on the device's home screen to display the login screen.

[1385] Step 2:

[1386] The user enters the required information such as name and password and clicks the login button.

[1387] Input: Name, Password

[1388] Output: Sending input information

[1389] Specific actions: Enter your name in the input field, then enter your password and tap the "Login" button.

[1390] Step 3:

[1391] The terminal transmits the input user information to the server.

[1392] Input: User name, password

[1393] Output: Request sent to server

[1394] Specific operation: When the login button is clicked, the device encrypts the data and sends it to the server using an HTTP POST request.

[1395] Step 4:

[1396] The server checks the received user information against a database, and if authentication is successful, generates an authentication token and returns it to the terminal.

[1397] Input: Username, Password

[1398] Output: Authentication token

[1399] Specific operation: The server queries the database, and if there is matching information, it generates a JWT (JSON Web Token) and sends it to the terminal.

[1400] Step 5:

[1401] The device stores the authentication token and proceeds to the next step.

[1402] Input: Authentication Token

[1403] Output: Authentication token saved

[1404] Specific operation: The received token is saved in local storage and prepared for the user's next operation.

[1405] Step 6:

[1406] After logging in, users access their profile page to add or update their profile information, including their interests.

[1407] Input: Interests, concerns

[1408] Output: Display of input information

[1409] Specific operation: Once you have logged in, a link to your profile page will appear; tap on it.

[1410] Step 7:

[1411] The terminal transmits the entered profile information to the server.

[1412] Input: Interests, concerns

[1413] Output: Request sent to server

[1414] Specific operation: Tap the submit button to send the information entered in the form to the server.

[1415] Step 8:

[1416] The server stores the received profile information in a database.

[1417] Input: Interests, concerns

[1418] Output: Save to database

[1419] Specific operation: The server inserts or updates the received data into the user profile table in the database.

[1420] Step 9:

[1421] The server searches for and extracts users who share common interests and concerns based on the profile information of the logged-in user.

[1422] Input: User profile information

[1423] Output: Matching list

[1424] What it does: The server filters other user profiles based on the user's areas of interest and generates a list of users with whom you have something in common.

[1425] Step 10:

[1426] The server sends the matching list to the terminal.

[1427] Input: Matching List

[1428] Output: Sending a request to the terminal

[1429] Specific operation: The generated list is sent to the terminal in JSON format.

[1430] Step 11:

[1431] The terminal receives the matching list and displays it to the user.

[1432] Input: Matching List

[1433] Output: Display list

[1434] Specific operation: When the list is received, it is reflected in the display UI and displayed in a format that is easy for the user to see.

[1435] Step 12:

[1436] The user selects a person with whom he or she wants to start a chat from the displayed list and presses the chat start button.

[1437] Input: List item

[1438] Output: Chat start request

[1439] What it does: Tap on the user's name in the list and click the "Start Chat" button.

[1440] Step 13:

[1441] The user enters a message on the chat screen and clicks the send button.

[1442] Input: Message text

[1443] Output: Message send request

[1444] Specific actions: Enter a message in the text box and press the "Send" button.

[1445] Step 14:

[1446] The terminal transmits the input message to the server.

[1447] Input: Message text

[1448] Output: Request sent to server

[1449] Specific operation: The message text is sent to the server using an HTTP POST request.

[1450] Step 15:

[1451] The server receives the message, analyzes it, and sends a request to the generative AI.

[1452] Input: Message text

[1453] Output: Send prompt to AI

[1454] Specific operation: Analyze the message content and generate and send an appropriate prompt to a generative AI (e.g., GPT-3).

[1455] Step 16:

[1456] The generative AI generates an appropriate response to the message and sends it back to the server.

[1457] Input: prompt

[1458] Output: The generated response

[1459] How it works: The AI ​​model generates a response based on the prompt, and the response is received by the server.

[1460] Step 17:

[1461] The server receives the generated response, formats it appropriately, and sends it to the chat partner's device.

[1462] Input: Generated response

[1463] Output: Sending a request to the terminal

[1464] Specific operation: The response is formatted as JSON and sent to the chat participant's device.

[1465] Step 18:

[1466] The device will display the received message in the chat window.

[1467] Input: Generated response

[1468] Output: Display message

[1469] Specific behavior: When a message is received, it is displayed in the UI and can be confirmed by the user.

[1470] Step 19:

[1471] The user selects a specific action from the tablet device and sends a command.

[1472] Input: Action selection

[1473] Output: Command transmission request

[1474] Specific actions: Select "Event Information" from the menu and press the send button.

[1475] Step 20:

[1476] The terminal transmits the command content to the server.

[1477] Input: Action command

[1478] Output: Request sent to server

[1479] Specific Operation: An HTTP request is used to send the selected command information to the server.

[1480] Step 21:

[1481] The server receives the commands and sends control commands to the appropriate robots.

[1482] Input: Command information

[1483] Output: Sending control commands to the robot

[1484] Specific operation: Analyzes the command content and sends the command to the necessary robot.

[1485] Step 22:

[1486] The robot receives commands and performs the specified actions.

[1487] Input: Control command

[1488] Output: Action execution

[1489] Specific Action: The robot moves to the designated area and performs the programmed action.

[1490] Step 23:

[1491] The robot reports the results of its operations to the server, and the server notifies the terminal of the results.

[1492] Input: Operation result

[1493] Output: Result notification

[1494] Specific operation: An operation completion report is sent to the server, and the server sends a notification to the user's terminal.

[1495] (Application example 1)

[1496] 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."

[1497] In social spaces such as cafes, there is a need for an efficient system to promote communication between users and to automate information about events and services within the cafe.In addition, there is a need for a system that can generate conversations between users in real time using smartphones and act as a mobile guide.

[1498] 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.

[1499] In this invention, the server includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a mobile control command means, and a mobile information terminal application execution means. This allows users to be easily matched based on their shared interests and concerns, enables real-time conversations using generative AI, and automates information about events and services in the cafe via a smartphone application.

[1500] The "login authentication means" is a means for a user to input authentication information required to access the system and verify the user's identity.

[1501] "User profile management means" means a means for entering and updating a user's interests and other personal information and storing it in a database.

[1502] The "means for generating conversation data" is a means for generating the content of conversation necessary to promote communication between users.

[1503] "User matching means" refers to a means for searching for and matching users who share common interests.

[1504] "Real-time conversation management means" refers to a means for managing and supporting conversations between users in real time.

[1505] The "mobile object control command means" is a means for controlling and instructing the operation of a mobile object (such as a robot) for purposes such as event announcements and service provision.

[1506] "Mobile information terminal application execution means" refers to means for executing applications that run on mobile information terminals such as smartphones and tablets.

[1507] A "generative AI model" is an artificial intelligence model that generates appropriate responses and information based on input text and data.

[1508] A "prompt sentence" is an input sentence to a generative AI model, and is an instruction sentence that enables the AI ​​to generate an appropriate response.

[1509] MODE FOR CARRYING OUT THE INVENTION

[1510] The present invention is a system for promoting communication between users in social spaces such as cafes and providing information about events and services available within the cafe. Specific embodiments of this system are described below.

[1511] Login Authentication

[1512] Users log in using a tablet device installed in the cafe or their own smartphone. The user information entered through the login authentication means is sent to the server, which then collates it with a database for authentication. If authentication is successful, an authentication token is returned to the device.

[1513] Profile Management

[1514] After logging in, users can add or update their profile information, including their interests. The device sends the entered profile information to the server, which stores it in a database. The stored data is then used to match users with other users.

[1515] User matching

[1516] The server searches for and extracts other users who share common interests based on the profile information of the logged-in user. Matching users are added to a matching list, which is sent to the device. The user then selects the person they want to chat with from the displayed list and presses the Start Chat button.

[1517] Real-time conversation generation

[1518] The user enters a message on the chat screen and clicks the send button. The device sends the message to the server, which then uses the generative AI model to generate an appropriate reply. The generated reply is sent from the server to the chat partner's device and displayed in the chat window.

[1519] Event Information

[1520] Users can request information about events taking place in the cafe via a tablet or smartphone. This command is sent to the server, which then uses the mobile control command means to instruct the robot based on the command, and the robot then performs the specified action, such as reading out information about the event. The results of the robot's actions are reported to the server, which then notifies the terminal of the results.

[1521] Hardware and software used

[1522] Hardware: Tablets, smartphones, robots, servers

[1523] Software: User profile management software, generative AI models (e.g., GPT-3), authentication systems, matching algorithms, real-time chat software

[1524] Specific examples

[1525] For example, Person A and Person B visit a cafe and log in from their respective smartphones. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the devices notify Person A and Person B, and they begin chatting with each other. When Person A types and sends "What movies do you recommend these days?" in the chat, the server uses a generative AI model to generate an appropriate response, which is displayed on Person B's device. Furthermore, if Person A requests information about events, the robot will provide information about events currently being held in the cafe.

[1526] Prompt Sentence Examples

[1527] Simply launch the SmartCafe Connect app, log in, and update your interest profile. Then, check your match list and start chatting with other users who share your interests. If you request event information, a robot in the cafe will guide you to the event.

[1528] Login name: User name

[1529] Password:Password

[1530] Interests: Music, movies

[1531] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1532] Step 1:

[1533] Login Authentication

[1534] The user accesses the login page using a tablet device installed in the cafe or their own smartphone and enters their name and password. The device sends this input information to the server. The server compares the received user information with a database, and if authentication is successful, it generates an authentication token and sends it back to the device. The device saves the authentication token and moves the user to the next step.

[1535] Input: User name, password

[1536] Output: Authentication token

[1537] Step 2:

[1538] Profile Management

[1539] After logging in, users access a page where they can enter and update their profile information, including their interests. The device sends the entered profile information to the server, which stores this information in a database and uses it to match users with other users.

[1540] Input: User profile information (interests, concerns)

[1541] Output: Profile information stored in a database

[1542] Step 3:

[1543] User matching

[1544] The server searches for other users who share common interests based on the logged-in user's profile information and adds those users to a matching list. This matching list is sent to the user's device, which then displays it to the user. The user selects the person they want to chat with from the displayed list and presses the start chat button.

[1545] Input: Profile information stored in the database

[1546] Output: Matching list

[1547] Step 4:

[1548] Real-time conversation generation

[1549] The user enters a message on the chat screen and clicks the send button. The device sends the entered message to the server, which analyzes the message and sends a request to the generative AI model. The generative AI model generates an appropriate response to the message and sends it back to the server. The server receives the generated response and sends it to the device of the chat partner. The device displays the received message in the chat window.

[1550] Input: User's message

[1551] Output: The response from the generative AI model

[1552] Step 5:

[1553] Event Information

[1554] A user requests a specific action, such as an event announcement, via a tablet or smartphone. The device sends this command to the server. The server receives the command and sends a control command to the robot using the mobile object control command means. The robot receives the command and performs the specified action (e.g., reading out an event announcement). The robot reports the results of its action to the server, which then notifies the device of the result.

[1555] Input: User's event information request

[1556] Output: Event information by robot

[1557] Specific behavior:

[1558] Server: User authentication, storing information in a database, matching, requests to the generative AI model, sending vehicle control commands

[1559] Device: Sending user input, storing authentication tokens, displaying match lists, sending and receiving chat messages

[1560] Users: Log in, enter profile information, use chat, and send event invitation requests

[1561] Robot: Event guide execution 34,,

[1562] 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.

[1563] The present invention is a system for promoting communication between users in social spaces such as cafes. The system includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a robot control command means, and an emotion engine.

[1564] Specific embodiments of the system and program processing will be described below.

[1565] Login Process

[1566] The user operates a tablet device installed in the cafe and accesses the login page. The user enters the required information such as name and password and clicks the login button.

[1567] The terminal transmits the input user information to the server.

[1568] The server checks the received user information against a database, and if authentication is successful, generates an authentication token and returns it to the terminal.

[1569] The terminal stores the authentication token and displays a successful login to the user.

[1570] Profile Management

[1571] After logging in, users access a page where they can add or update their profile information, including their interests.

[1572] The terminal transmits the entered profile information to the server.

[1573] The server stores the received profile information in a database and uses it to match users with other users.

[1574] User matching

[1575] Based on the profile information mentioned above, the server searches and extracts users with common interests and creates a matching list.

[1576] The server sends the matching list to each terminal.

[1577] The terminal receives the matching list and displays it to the user.

[1578] The user selects the desired partner from the displayed list and presses the chat start button.

[1579] Real-time conversation generation

[1580] The user enters a message on the chat screen and clicks the send button.

[1581] The terminal transmits the input message to the server.

[1582] The server receives the message and sends a request to the generative AI.

[1583] The generative AI generates an appropriate response to the message and sends it back to the server.

[1584] The server receives the returned message, formats it, and sends it to the terminal.

[1585] The device will display the received message in the chat window.

[1586] Emotion engine integration

[1587] When a user inputs a message on the chat screen, the terminal transmits the input content to the server.

[1588] The server sends the received message to the emotion engine to analyze the user's emotions.

[1589] The emotion engine sends the analysis results back to the server, and the generative AI adjusts the content and style of the response based on those results.

[1590] The server sends the tailored response to the device, which displays it in the chat window.

[1591] As a concrete example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the device notifies Person A and Person B, and they begin chatting.

[1592] When Person A types in and sends "What recent movie do you recommend?", the server sends the message to the generative AI and emotion engine, and the emotion engine detects Person A's feelings of excitement and anticipation. Based on the results, the generative AI generates a response such as "The recent movie I recommend is 'Inception.' It's an amazing movie!" and displays it on Person B's device. In this way, the conversation between Person A and Person B becomes richer and more natural with the intervention of the emotion engine.

[1593] Robot Control

[1594] The user selects and sends a specific action (e.g., requesting event information) from the tablet device.

[1595] The terminal transmits the transmission contents to the server.

[1596] The server sends the request as a control command to the appropriate robot.

[1597] The robot receives commands and performs the specified action (e.g., reading out event information).

[1598] The robot reports the results of its operations to the server, and the server notifies the terminal of the results.

[1599] In this way, by implementing the system of the present invention, communication between users in a cafe becomes smooth and enjoyable, and the introduction of an emotion engine enables even deeper communication.

[1600] The processing flow will be explained below.

[1601] (Login process)

[1602] Step 1:

[1603] The user operates a tablet device installed in the cafe and accesses the login page.

[1604] Step 2:

[1605] The user enters login information such as name and password and clicks the login button.

[1606] Step 3:

[1607] The terminal sends the entered login information to the server.

[1608] Step 4:

[1609] The server receives the login information and checks it against the user information in its database.

[1610] Step 5:

[1611] If the server is successful in the authentication, it generates an authentication token and sends it to the terminal.

[1612] Step 6:

[1613] The terminal stores the received authentication token and displays a successful login to the user.

[1614] (Profile Management)

[1615] Step 1:

[1616] After the user logs in, they access the profile settings page.

[1617] Step 2:

[1618] The user enters their profile information, such as interests, and clicks the save button.

[1619] Step 3:

[1620] The device transmits the entered profile information to the server.

[1621] Step 4:

[1622] The server stores the received profile information in a database.

[1623] (User matching)

[1624] Step 1:

[1625] The server searches for users with common interests based on each user's profile information.

[1626] Step 2:

[1627] The server extracts the relevant users and creates a matching list.

[1628] Step 3:

[1629] The server sends the matching list to each device.

[1630] Step 4:

[1631] The terminal displays the received matching list to the user.

[1632] Step 5:

[1633] The user selects a chat partner from the displayed list and presses the chat start button.

[1634] (Generating real-time conversations)

[1635] Step 1:

[1636] The user enters a message in the chat screen and clicks the send button.

[1637] Step 2:

[1638] The terminal sends the input message to the server.

[1639] Step 3:

[1640] The server analyzes the received message and sends a request to the generative AI.

[1641] Step 4:

[1642] The generative AI generates an appropriate response to the message and sends it back to the server.

[1643] Step 5:

[1644] The server receives the returned message, formats it, and sends it to the terminal.

[1645] Step 6:

[1646] Displays messages received by the device in the chat window.

[1647] (Emotion engine integration)

[1648] Step 1:

[1649] The user enters a message in the chat screen and clicks the send button.

[1650] Step 2:

[1651] The terminal sends the input message to the server.

[1652] Step 3:

[1653] The server sends the received message to the emotion engine.

[1654] Step 4:

[1655] An emotion engine analyzes the message and identifies the user's emotion.

[1656] Step 5:

[1657] The emotion engine sends the analysis results back to the server.

[1658] Step 6:

[1659] The server requests the generative AI to generate a message based on the results of the emotion engine.

[1660] Step 7:

[1661] The generative AI generates an appropriate response based on the emotion and sends it back to the server.

[1662] Step 8:

[1663] The server receives the returned message, formats it, and sends it to the terminal.

[1664] Step 9:

[1665] Displays messages received by the device in the chat window.

[1666] (Robot Control)

[1667] Step 1:

[1668] The user selects a specific action (e.g., requesting event information) on the tablet device and clicks the send button.

[1669] Step 2:

[1670] The terminal sends the transmission content to the server.

[1671] Step 3:

[1672] The server sends the received request as a command to the appropriate robot.

[1673] Step 4:

[1674] The robot receives commands and performs the specified action (e.g., reading out information about an event).

[1675] Step 5:

[1676] The robot reports the results of its actions to the server.

[1677] Step 6:

[1678] The server checks the results of the operation and sends additional commands to the robot if necessary.

[1679] Step 7:

[1680] The terminal notifies the user that the robot's operation was successful.

[1681] These specific processing steps make communication between users in the cafe smooth and enjoyable, and the intervention of the emotion engine enables deeper communication.

[1682] Example 2

[1683] 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."

[1684] In existing social forums, communication between users is not smooth, and support for creating new interactions is insufficient. In particular, it is difficult to generate natural conversations in real time and respond with consideration for emotions. Furthermore, it is difficult to appropriately match users based on their interests, making it difficult to promote interactions with people who share their interests.

[1685] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1686] In this invention, the server includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a sentiment analysis means using a sentiment analysis engine, an AI model response generation means based on the sentiment analysis engine, and a robot control command means. This enables natural conversation between users, realizes responses that take emotions into consideration, and promotes effective matching based on common interests.

[1687] A "login authentication means" is a means for verifying the identity of a user when the user accesses a system.

[1688] "User profile management means" refers to a means by which a user can register and update their own interests and other information in the system.

[1689] The "means for generating conversation data" is a means for generating information necessary for conversation between users.

[1690] "User matching means" refers to a means for finding and matching users who share common interests based on user profile information.

[1691] "Real-time conversation management means" means means for controlling and managing a conversation in real time so that the conversation progresses continuously and fluently.

[1692] The "emotion analysis means using an emotion analysis engine" is a means for analyzing the user's emotions from the input message and outputting the results.

[1693] "A generative AI model response generation means based on an emotion analysis engine" is a means for generating an appropriate response based on the output of an emotion analysis engine.

[1694] The "robot control command means" is a means for sending specific commands to the robot and controlling its operation.

[1695] The present invention is a system for promoting communication between users in social settings such as cafes. The system includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a sentiment analysis means using a sentiment analysis engine, a generative AI model response generation means based on the sentiment analysis engine, and a robot control command means.

[1696] During the login process, the user operates a tablet device installed in the cafe to access the login page. After entering the required information such as their name and password, the user clicks the login button. The device sends the entered user information to the server, which then compares the received user information with its database. If authentication is successful, the server generates an authentication token and returns it to the device. The device saves the authentication token and displays a message to the user indicating that login was successful.

[1697] Next, after logging in, the user accesses a page to add or update profile information, including interests. The device sends the entered profile information to the server, which stores the received profile information in a database and uses it to match users with other users.

[1698] During the matching process, the server searches for and extracts users with common interests based on profile information in the database, and creates a matching list. The server then sends the matching list to each device, which receives it and displays it to the user. The user then selects the desired partner from the displayed list and presses the button to start chatting.

[1699] In real-time conversation generation, a user enters a message on the chat screen and clicks the send button. The device sends the entered message to the server, which receives the message and sends a request to the generative AI. The generative AI generates an appropriate response to the message and sends it back to the server. The server receives the returned message, formats it, and sends it to the device, which then displays the received message in the chat window.

[1700] The system also integrates a sentiment analysis engine. When a user types a message on the chat screen, the device sends the input to the server, which then sends the received message to the sentiment analysis engine, which analyzes the user's emotions. The sentiment analysis engine then sends the analysis results back to the server, and the generative AI adjusts the content and style of the reply based on the results. The server then sends the adjusted reply to the device, where it is displayed in the chat window.

[1701] As a concrete example, user A and user B visit a cafe and each log in. User A likes music, and user B likes movies. After logging in, their profile information is updated, and the server matches them based on their shared interest in "entertainment." Once matching is complete, the devices notify users A and B, and a chat begins. When user A types and sends the question, "What's a recent movie you recommend?", the server sends the message to the generative AI and the emotion analysis engine, and the emotion analysis engine detects user A's emotions of excitement and anticipation. Based on the results, the generative AI generates a response such as, "The recent movie I recommend is 'Inception.' It's an amazing movie!" and displays it on user B's device. In this way, the conversation between user A and user B becomes richer and more natural with the intervention of the emotion analysis engine.

[1702] It also controls robots. When a user selects and sends a specific action (e.g., requesting event information) from a tablet device, the device sends the request to the server. The server then sends the request as a control command to the appropriate robot, which then receives the command and performs the specified action (e.g., reading out event information). The robot then reports the results of its action to the server, which then notifies the device of the results.

[1703] Examples of prompts for generative AI models include:

[1704] "A user asks, 'What are some recent movie recommendations?' Generate an appropriate response."

[1705] "Based on the results of the sentiment analysis engine, generate responses that reflect the user's feelings of excitement and anticipation."

[1706] In this way, by implementing the system of the present invention, communication between users in the cafe becomes smooth and enjoyable, and the introduction of an emotion analysis engine enables even deeper communication.

[1707] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1708] Specific explanation of program processing

[1709] Step 1:

[1710] Login Process

[1711] Input: User information such as name and password

[1712] process:

[1713] 1. The user operates a tablet device in the cafe, enters their name and password, and clicks the login button.

[1714] 2. The terminal sends the entered user information to the server.

[1715] 3. The server checks the received user information against the information in its database.

[1716] 4. If the authentication is successful, the server generates an authentication token and returns it to the terminal.

[1717] 5. The device stores the authentication token and displays a successful login to the user.

[1718] Output: Authentication token and login result displayed

[1719] Specific examples of behavior:

[1720] The user enters "Yamada Taro" and "password123," and the device sends this information to the server. The server checks it against the database, and if it matches, it returns an authentication token called token12345, and the device displays "Login successful."

[1721] Step 2:

[1722] Profile Management

[1723] Input: Profile information such as interests

[1724] process:

[1725] 1. After logging in, the user visits the profile management page and enters or updates new information.

[1726] 2. The device sends the entered profile information to the server.

[1727] 3. The server stores the received profile information in a database and uses it for future matching.

[1728] Output: Updated profile information saved to database

[1729] Specific examples of behavior:

[1730] Users add interests such as "music, movies, reading" to their profile, and the device sends this information to the server, which stores it in a database.

[1731] Step 3:

[1732] User matching

[1733] Input: Profile information in the database

[1734] process:

[1735] 1. The server searches the profile information in the database and extracts users with common interests.

[1736] 2. The server generates a matching list based on the extraction results and sends it to each device.

[1737] 3. The device receives the matching list and displays it to the user.

[1738] 4. The user selects the desired partner and presses the chat start button.

[1739] Output: Match list and information displayed to the user

[1740] Specific examples of behavior:

[1741] The server matches user A and user B based on the common interests of "music and movies," and the device displays "A and B have been matched."

[1742] Step 4:

[1743] Real-time conversation generation

[1744] Input: The message entered by the user

[1745] process:

[1746] 1. The user enters a message in the chat screen and clicks the send button.

[1747] 2. The terminal sends the entered message to the server.

[1748] 3. The server sends the received message as a request to the generative AI model.

[1749] 4. The generative AI model generates an appropriate response to the message and sends it back to the server.

[1750] 5. The server formats the returned message and sends it to the terminal.

[1751] 6. The device will display the received message in the chat window.

[1752] Output: The generated reply message

[1753] Specific examples of behavior:

[1754] The user types "What are some recent recommended movies?", the device sends the message to the server, and the server sends the prompt "User asks about recent recommended movies" to the generative AI model. The generative AI model replies "The recent recommended movie is 'Inception'", which is displayed on the device via the server.

[1755] Step 5:

[1756] Sentiment analysis engine integration

[1757] Input: The message entered by the user

[1758] process:

[1759] 1. When a user enters a message on the chat screen, the device sends the content to the server.

[1760] 2. The server sends the received message to the sentiment analysis engine.

[1761] 3. The sentiment analysis engine analyzes the input message and detects the user's emotions.

[1762] 4. The sentiment analysis engine sends the analysis results back to the server, and the server sends a prompt based on the analysis results to the generative AI model.

[1763] 5. The generative AI model generates a tailored response based on the sentiment analysis results and sends it back to the server.

[1764] 6. The server sends this adjusted response to the device, which displays it in the chat window.

[1765] Output: Tailored response message based on sentiment analysis results

[1766] Specific examples of behavior:

[1767] A user excitedly types, "What's the best recent movie?" The sentiment analysis engine detects this excitement, and the generative AI model adjusts and responds, "The best recent movie is 'Inception.' It's an amazing movie!"

[1768] Step 6:

[1769] Robot Control

[1770] Input: User action selection (e.g., event information request)

[1771] process:

[1772] 1. The user selects and submits a specific action (e.g., requesting event information) on a tablet device.

[1773] 2. The device sends the selection to the server.

[1774] 3. The server sends the request as a control command to the appropriate robot.

[1775] 4. The robot receives the control command and performs the specified action (e.g., reading out an event announcement).

[1776] 5. The robot reports the results of its operation to the server, and the server notifies the terminal of the results.

[1777] Output: Robot operation results and notification

[1778] Specific examples of behavior:

[1779] When the user selects "I want to hear about the next event," the device sends a request to the server, and the server sends a command to the robot to "read out the event information." The robot reads out the information, reports to the server that "the event information has been read out," and notifies the device.

[1780] (Application example 2)

[1781] 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."

[1782] In today's social settings, it is difficult to foster communication between users and realize natural and rich conversations. Conventional systems lack the ability to match users based on their interests and generate appropriate conversations based on their emotions, presenting technical challenges for achieving deeper communication. Furthermore, to efficiently operate these functions in physical stores, it is necessary to integrate multiple technologies and improve the user experience.

[1783] 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.

[1784] In this invention, the server includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a robot control command means, an emotion analysis means, and an application means including chat conversations with users. This makes it possible to realize natural and rich communication by matching users with other users who share common interests based on their profile information and generating and adjusting conversation content that takes emotions into consideration using an emotion analysis engine.

[1785] The "login authentication means" is an authentication process used by a user to access the system, and involves inputting authentication information such as a user name and password to perform authentication.

[1786] "User profile management means" refers to a function for adding, updating, and managing profile information such as a user's interests.

[1787] "Means for generating conversational data" is a function that uses generative AI to generate appropriate responses based on messages entered by users.

[1788] "User matching means" is a function that searches for and extracts other users who share common interests based on the user's profile information, and creates a matching list.

[1789] "Real-time conversation management means" is a function that manages the sending and receiving of messages on the chat screen in real time, ensuring that conversations progress smoothly.

[1790] The "robot control command means" is a function that sends control commands to the robots in the cafe to cause them to perform specific actions, and manages the robots' operations.

[1791] The "emotion analysis means" is a function that analyzes messages entered by users and adjusts the content of conversations by detecting their emotions.

[1792] "Application means including chat conversations with users" refers to an application that is installed on a smartphone or tablet device and provides matching and chat functions between users.

[1793] The present invention is a system for promoting communication between users in social spaces such as cafes. The system includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a robot control command means, an emotion analysis means, and an application means including a chat conversation with a user.

[1794] Login authentication method

[1795] The user accesses the login page using a tablet device or smartphone installed in the cafe and enters their name and password to log in. The device sends the entered user information to the server, which then performs authentication and returns an authentication token if successful.

[1796] Profile Management Methods

[1797] After logging in, the user accesses a page for adding or updating profile information, including interests, and enters the profile information. The device sends the entered information to the server, which stores it in a database.

[1798] User matching method

[1799] The server searches for and extracts users with common interests based on the saved profile information, creates a matching list, and sends the matching list to each device, which then displays the list to the user.

[1800] Real-time conversation management

[1801] When a user enters and sends a message on the chat screen, the device sends the message to the server, which then sends the message to the generative AI model, which generates an appropriate response. The response is then adjusted by the sentiment analysis means and sent back to the device via the server.

[1802] Robot control command means

[1803] When a user sends a specific action (e.g., a request for event information), the device sends the request to the server, which then sends the request as a control command to the appropriate robot, which then performs the specified action.

[1804] Emotion analysis means

[1805] The sentiment analyzer analyzes messages entered by users to detect their emotions, and the server sends the results to a generative AI model to adjust the content and style of the reply, making the conversation more natural and rich.

[1806] Application means including chat conversations with users

[1807] Chat conversations are conducted through an application installed on smartphones and tablets, which provides comprehensive profile entry, matching, and chat functions.

[1808] Specific examples

[1809] For example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the device notifies Person A and Person B, and the chat begins.

[1810] When Person A types in "What recent movie would you recommend?" and submits it, the server uses emotion analysis to detect Person A's feelings of excitement and anticipation, and based on the results, the generative AI model generates a response saying, "The recent movie I recommend is 'Inception.' It's an absolutely amazing film!" and displays it on Person B's device.

[1811] Prompt Sentence Examples

[1812] What recent movies do you recommend?

[1813] What recent music albums do you recommend?

[1814] What's today's recommended cafe menu?

[1815] This will make communication between users in the cafe smooth and enjoyable, and the introduction of an emotion engine will enable even deeper communication.

[1816] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1817] Step 1:

[1818] The user accesses the login page using a tablet or smartphone installed in the cafe and logs in by entering their username and password. The device sends the entered authentication information to the server, which checks it against a database. If authentication is successful, the server issues an authentication token and returns it to the device. The authentication token is then displayed to the user.

[1819] Input: Username, Password

[1820] Data processing: Database matching of authentication information

[1821] Output: Authentication token

[1822] Step 2:

[1823] After logging in, users enter and update their profile information, including their interests. The device sends the entered profile information to the server, which stores it in a database.

[1824] Input: Profile information (interests, etc.)

[1825] Data processing: Profile information stored in a database

[1826] Output: Profile information update results

[1827] Step 3:

[1828] The server searches for and extracts users with common interests based on the saved profile information, creating a matching list. The server then sends the matching list to each device, which then displays it to the user.

[1829] Input: Profile information stored in the database

[1830] Data processing: Creating a matching list based on common interests

[1831] Output: Matching list

[1832] Step 4:

[1833] When a user enters a message on the chat screen and presses the send button, the device sends the message to the server. The server sends the message to a generative AI model, which generates an appropriate response. The generated response is then sent to a sentiment analysis means, where it is adjusted based on the user's emotions. The adjusted response is then sent back to the device via the server and displayed in the chat window.

[1834] Input: Chat message

[1835] Data processing: Response generation using generative AI models, adjustments using sentiment analysis methods

[1836] Output: Adjusted response

[1837] Step 5:

[1838] When a user requests a robot in a cafe to perform a specific action (e.g., an event announcement), the terminal sends the request to the server. The server then sends the request as a control command to the appropriate robot, which then executes the specified action. The robot then reports the results of its action to the server, which then notifies the terminal of the results.

[1839] Input: Request to the robot (e.g., event information)

[1840] Data processing: generating and transmitting robot control commands

[1841] Output: Robot movement results

[1842] For example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches them based on their shared interest in "entertainment," sending a notification to their device. User A then types, "What's a recommended recent movie?" The server's sentiment analysis engine analyzes this message, and the generative AI model generates a response: "The recommended recent movie is 'Inception.' It's an amazing movie!", which is displayed on Person B's device.

[1843] The above are the specific processing steps performed by this system.

[1844] 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.

[1845] 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.

[1846] 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.

[1847] [Fourth embodiment]

[1848] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1849] 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.

[1850] 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).

[1851] 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.

[1852] 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.

[1853] 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).

[1854] 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.

[1855] 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.

[1856] 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.

[1857] 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.

[1858] 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.

[1859] 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.

[1860] 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."

[1861] The present invention is a system for promoting communication between users in social spaces such as cafes. A specific embodiment of this system and the processing of the program will be described below.

[1862] The system mainly consists of the following components:

[1863] Login authentication method

[1864] User profile management means

[1865] Conversation data generation method

[1866] User matching method

[1867] Real-time conversation management

[1868] Robot control command means

[1869] Login Process

[1870] The user operates a tablet device installed in the cafe and accesses the login page. The user enters the required information such as name and password and clicks the login button.

[1871] The terminal transmits the input user information to the server.

[1872] The server checks the received user information against a database, and if authentication is successful, generates an authentication token and returns it to the terminal.

[1873] The device stores the authentication token and proceeds to the next step.

[1874] Profile Management

[1875] After logging in, users access a page where they can add or update their profile information, including their interests.

[1876] The terminal transmits the entered profile information to the server.

[1877] The server stores the received profile information in a database and uses it to match users with other users.

[1878] User matching

[1879] The server searches for and extracts users who share common interests based on the profile information of the logged-in user, adds the users to a matching list, and sends it to the device.

[1880] The terminal receives the matching list and displays it to the user.

[1881] The user selects a person with whom he or she wants to start a chat from the displayed list and presses the chat start button.

[1882] Real-time conversation generation

[1883] The user enters a message on the chat screen and clicks the send button.

[1884] The terminal transmits the input message to the server.

[1885] The server receives the message, analyzes it, and sends a request to the generative AI.

[1886] The generative AI generates an appropriate response to the message and sends it back to the server.

[1887] The server receives the generated response, formats it appropriately, and sends it to the chat partner's device.

[1888] The device will display the received message in the chat window.

[1889] Robot Control

[1890] The user selects a specific action (e.g., requesting event information) from the tablet device and sends a command.

[1891] The terminal transmits the command content to the server.

[1892] The server receives the commands and sends control commands to the appropriate robots.

[1893] The robot receives commands and performs the specified action (e.g., reading out event information).

[1894] The robot reports the results of its operations to the server, and the server notifies the terminal of the results.

[1895] Specific examples

[1896] For example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the device notifies Person A and Person B, and they begin chatting with each other.

[1897] When Person A types "What recent movies do you recommend?" into the chat and sends it, the server uses generative AI to generate an appropriate response, which is displayed on Person B's device. Furthermore, if Person A requests information about events, the robot will provide information about events currently being held in the cafe.

[1898] In this way, customers can communicate efficiently and enjoyably within the cafe and receive guidance from the robot.

[1899] The processing flow will be explained below.

[1900] (Login process)

[1901] Step 1:

[1902] The user operates a tablet device installed in the cafe and accesses the login page.

[1903] Step 2:

[1904] The user enters login information such as name and password and clicks the login button.

[1905] Step 3:

[1906] The terminal sends the entered login information to the server.

[1907] Step 4:

[1908] The server receives the login information and checks it against the user information in its database.

[1909] Step 5:

[1910] If the server is successful in the authentication, it generates an authentication token and sends it to the terminal.

[1911] Step 6:

[1912] The device stores the received authentication token and displays a message to the user indicating that the login was successful.

[1913] (Profile Management)

[1914] Step 1:

[1915] After the user logs in, they access the profile settings page.

[1916] Step 2:

[1917] The user enters their profile information, such as interests, and clicks the save button.

[1918] Step 3:

[1919] The device transmits the entered profile information to the server.

[1920] Step 4:

[1921] The server stores the received profile information in a database.

[1922] (User matching)

[1923] Step 1:

[1924] The server searches for users with common interests based on each user's profile information.

[1925] Step 2:

[1926] The server extracts the relevant users and creates a matching list.

[1927] Step 3:

[1928] The server sends the matching list to each device.

[1929] Step 4:

[1930] The terminal displays the received matching list to the user.

[1931] Step 5:

[1932] The user selects a chat partner from the displayed list and presses the chat start button.

[1933] (Generating real-time conversations)

[1934] Step 1:

[1935] The user enters a message in the chat screen and clicks the send button.

[1936] Step 2:

[1937] The terminal sends the input message to the server.

[1938] Step 3:

[1939] The server analyzes the received message and sends a request to the generative AI.

[1940] Step 4:

[1941] The generative AI generates an appropriate response to the message and sends it back to the server.

[1942] Step 5:

[1943] The server receives the returned message, formats it, and sends it to the terminal.

[1944] Step 6:

[1945] Displays messages received by the device in the chat window.

[1946] (Robot Control)

[1947] Step 1:

[1948] The user selects a specific action (e.g., requesting event information) on the tablet device and clicks the send button.

[1949] Step 2:

[1950] The terminal sends the transmission content to the server.

[1951] Step 3:

[1952] The server sends the received request as a command to the appropriate robot.

[1953] Step 4:

[1954] The robot receives commands and performs the specified action (e.g., reading out information about an event).

[1955] Step 5:

[1956] The robot reports the results of its actions to the server.

[1957] Step 6:

[1958] The server checks the results of the operation and sends additional commands to the robot if necessary.

[1959] Step 7:

[1960] The terminal notifies the user that the robot's operation was successful.

[1961] These steps will make communication between customers in the cafe smooth and enjoyable.

[1962] Example 1

[1963] 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."

[1964] In modern society, it is often difficult for users to naturally interact with each other, especially in social spaces such as cafes. Furthermore, there is a lack of mechanisms for users with different interests to communicate efficiently. As a result, users tend to feel isolated, and social spaces are not fully utilized. Furthermore, there is a need for a mechanism that allows smooth real-time conversations and the sharing of information.

[1965] 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.

[1966] In this invention, the server includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a means for a user to select a specific action and send a command, a robot control command means for a robot to receive the command and execute the action, and a means for generating a response to an input message using a generative AI model. This allows users to be efficiently matched based on shared interests and concerns, and appropriate responses are generated in real time using the generative AI model, enabling smooth communication and information provision.

[1967] A "login authentication method" is a mechanism for verifying and authenticating the authentication information (e.g., name and password) entered by a user when accessing a system.

[1968] "User profile management means" means a mechanism by which a user can enter and update their interests and other profile information and store it in a database.

[1969] The "means for generating conversation data" is a mechanism for analyzing and processing messages and conversation content entered by users and generating conversation data.

[1970] "User matching means" is a system that searches for and extracts users with common interests and concerns based on user profile information, and matches them together.

[1971] The "real-time conversation management means" is a mechanism for sending and receiving messages between users in real time and managing conversations.

[1972] "Means for users to select specific actions and send commands" refers to a mechanism by which users select specific actions using a tablet device or the like and send commands to the system.

[1973] The "robot control command means" is a mechanism for transmitting commands received by the system to an appropriate robot, which then executes the operation.

[1974] "Means for generating a response to a message input by a generative AI model" refers to a mechanism that uses a generative AI model (e.g., GPT-3) to generate an appropriate response to a message input by a user.

[1975] This system is designed to promote communication between users in social settings such as cafes. The system mainly consists of a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a means for users to select specific actions and send commands, a robot control command means, and a means for generating replies to input messages using a generative AI model.

[1976] First, the user operates a tablet device installed in the cafe to access the login page. The user enters the required information, such as their name and password, and clicks the login button. The device sends the entered user information to the server. The server compares the received user information with its database, and if authentication is successful, generates an authentication token and sends it back to the device. The device saves the authentication token and proceeds to the next step.

[1977] After logging in, the user accesses the profile page and adds or updates profile information, including interests. The device sends the entered profile information to the server, which stores the received profile information in a database.

[1978] The server searches for and extracts users who share common interests based on the profile information of the logged-in user. The server adds the matching users to a matching list and sends it to the device. The device receives the matching list and displays it to the user. The user then selects the person they want to chat with from the displayed list and presses the start chat button.

[1979] The user enters a message on the chat screen and clicks the send button. The device sends the entered message to the server. The server receives the message, analyzes it, and sends a request to a generative AI (such as OpenAI's GPT-3 model). The generative AI generates an appropriate response to the message and sends it back to the server. The server receives the generated response, formats it appropriately, and sends it to the device of the chat partner. The device displays the received message in the chat window.

[1980] The user can also select a specific action (e.g., requesting event information) from the tablet device and send a command. The device then sends the command to the server. The server receives the command and sends a control command to the appropriate robot. The robot then receives the command and performs the specified action (e.g., reading out event information). The robot then reports the results of its action to the server, which then notifies the device of the results.

[1981] As a concrete example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the device notifies Person A and Person B, and they begin chatting with each other.

[1982] When Person A types "What recent movies do you recommend?" into the chat and sends it, the server uses generative AI to generate an appropriate response, which is displayed on Person B's device. Furthermore, if Person A requests information about events, the robot will provide information about events currently being held in the cafe.

[1983] An example prompt is:

[1984] User Question:

[1985] "What recent movies would you recommend?"

[1986] AI response prompt:

[1987] "A recently released movie that has received particularly high praise is 'Movie Title'. This movie is 'Brief Movie Description'. You might enjoy it too."

[1988] In this way, customers can communicate efficiently and enjoyably within the cafe and receive guidance from the robot.

[1989] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1990] Step 1:

[1991] Users access the login page using a tablet device installed in the cafe.

[1992] Input: Login page on tablet device

[1993] Output: Login screen displayed

[1994] Specific operation: Tap the login icon on the device's home screen to display the login screen.

[1995] Step 2:

[1996] The user enters the required information such as name and password and clicks the login button.

[1997] Input: Name, Password

[1998] Output: Sending input information

[1999] Specific actions: Enter your name in the input field, then enter your password and tap the "Login" button.

[2000] Step 3:

[2001] The terminal transmits the input user information to the server.

[2002] Input: User name, password

[2003] Output: Request sent to server

[2004] Specific operation: When the login button is clicked, the device encrypts the data and sends it to the server using an HTTP POST request.

[2005] Step 4:

[2006] The server checks the received user information against a database, and if authentication is successful, generates an authentication token and returns it to the terminal.

[2007] Input: Username, Password

[2008] Output: Authentication token

[2009] Specific operation: The server queries the database, and if there is matching information, it generates a JWT (JSON Web Token) and sends it to the terminal.

[2010] Step 5:

[2011] The device stores the authentication token and proceeds to the next step.

[2012] Input: Authentication Token

[2013] Output: Authentication token saved

[2014] Specific operation: The received token is saved in local storage and prepared for the user's next operation.

[2015] Step 6:

[2016] After logging in, users access their profile page to add or update their profile information, including their interests.

[2017] Input: Interests, concerns

[2018] Output: Display of input information

[2019] Specific operation: Once you have logged in, a link to your profile page will appear; tap on it.

[2020] Step 7:

[2021] The terminal transmits the entered profile information to the server.

[2022] Input: Interests, concerns

[2023] Output: Request sent to server

[2024] Specific operation: Tap the submit button to send the information entered in the form to the server.

[2025] Step 8:

[2026] The server stores the received profile information in a database.

[2027] Input: Interests, concerns

[2028] Output: Save to database

[2029] Specific operation: The server inserts or updates the received data into the user profile table in the database.

[2030] Step 9:

[2031] The server searches for and extracts users who share common interests and concerns based on the profile information of the logged-in user.

[2032] Input: User profile information

[2033] Output: Matching list

[2034] What it does: The server filters other user profiles based on the user's areas of interest and generates a list of users with whom you have something in common.

[2035] Step 10:

[2036] The server sends the matching list to the terminal.

[2037] Input: Matching List

[2038] Output: Sending a request to the terminal

[2039] Specific operation: The generated list is sent to the terminal in JSON format.

[2040] Step 11:

[2041] The terminal receives the matching list and displays it to the user.

[2042] Input: Matching List

[2043] Output: Display list

[2044] Specific operation: When the list is received, it is reflected in the display UI and displayed in a format that is easy for the user to see.

[2045] Step 12:

[2046] The user selects a person with whom he or she wants to start a chat from the displayed list and presses the chat start button.

[2047] Input: List item

[2048] Output: Chat start request

[2049] What it does: Tap on the user's name in the list and click the "Start Chat" button.

[2050] Step 13:

[2051] The user enters a message on the chat screen and clicks the send button.

[2052] Input: Message text

[2053] Output: Message send request

[2054] Specific actions: Enter a message in the text box and press the "Send" button.

[2055] Step 14:

[2056] The terminal transmits the input message to the server.

[2057] Input: Message text

[2058] Output: Request sent to server

[2059] Specific operation: The message text is sent to the server using an HTTP POST request.

[2060] Step 15:

[2061] The server receives the message, analyzes it, and sends a request to the generative AI.

[2062] Input: Message text

[2063] Output: Send prompt to AI

[2064] Specific operation: Analyze the message content and generate and send an appropriate prompt to a generative AI (e.g., GPT-3).

[2065] Step 16:

[2066] The generative AI generates an appropriate response to the message and sends it back to the server.

[2067] Input: prompt

[2068] Output: The generated response

[2069] How it works: The AI ​​model generates a response based on the prompt, and the response is received by the server.

[2070] Step 17:

[2071] The server receives the generated response, formats it appropriately, and sends it to the chat partner's device.

[2072] Input: Generated response

[2073] Output: Sending a request to the terminal

[2074] Specific operation: The response is formatted as JSON and sent to the chat participant's device.

[2075] Step 18:

[2076] The device will display the received message in the chat window.

[2077] Input: Generated response

[2078] Output: Display message

[2079] Specific behavior: When a message is received, it is displayed in the UI and can be confirmed by the user.

[2080] Step 19:

[2081] The user selects a specific action from the tablet device and sends a command.

[2082] Input: Action selection

[2083] Output: Command transmission request

[2084] Specific actions: Select "Event Information" from the menu and press the send button.

[2085] Step 20:

[2086] The terminal transmits the command content to the server.

[2087] Input: Action command

[2088] Output: Request sent to server

[2089] Specific Operation: An HTTP request is used to send the selected command information to the server.

[2090] Step 21:

[2091] The server receives the commands and sends control commands to the appropriate robots.

[2092] Input: Command information

[2093] Output: Sending control commands to the robot

[2094] Specific operation: Analyzes the command content and sends the command to the necessary robot.

[2095] Step 22:

[2096] The robot receives commands and performs the specified actions.

[2097] Input: Control command

[2098] Output: Action execution

[2099] Specific Action: The robot moves to the designated area and performs the programmed action.

[2100] Step 23:

[2101] The robot reports the results of its operations to the server, and the server notifies the terminal of the results.

[2102] Input: Operation result

[2103] Output: Result notification

[2104] Specific operation: An operation completion report is sent to the server, and the server sends a notification to the user's terminal.

[2105] (Application example 1)

[2106] 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."

[2107] In social spaces such as cafes, there is a need for an efficient system to promote communication between users and to automate information about events and services within the cafe.In addition, there is a need for a system that can generate conversations between users in real time using smartphones and act as a mobile guide.

[2108] 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.

[2109] In this invention, the server includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a mobile control command means, and a mobile information terminal application execution means. This allows users to be easily matched based on their shared interests and concerns, enables real-time conversations using generative AI, and automates information about events and services in the cafe via a smartphone application.

[2110] The "login authentication means" is a means for a user to input authentication information required to access the system and verify the user's identity.

[2111] "User profile management means" means a means for entering and updating a user's interests and other personal information and storing it in a database.

[2112] The "means for generating conversation data" is a means for generating the content of conversation necessary to promote communication between users.

[2113] "User matching means" refers to a means for searching for and matching users who share common interests.

[2114] "Real-time conversation management means" refers to a means for managing and supporting conversations between users in real time.

[2115] The "mobile object control command means" is a means for controlling and instructing the operation of a mobile object (such as a robot) for purposes such as event announcements and service provision.

[2116] "Mobile information terminal application execution means" refers to means for executing applications that run on mobile information terminals such as smartphones and tablets.

[2117] A "generative AI model" is an artificial intelligence model that generates appropriate responses and information based on input text and data.

[2118] A "prompt sentence" is an input sentence to a generative AI model, and is an instruction sentence that enables the AI ​​to generate an appropriate response.

[2119] MODE FOR CARRYING OUT THE INVENTION

[2120] The present invention is a system for promoting communication between users in social spaces such as cafes and providing information about events and services available within the cafe. Specific embodiments of this system are described below.

[2121] Login Authentication

[2122] Users log in using a tablet device installed in the cafe or their own smartphone. The user information entered through the login authentication means is sent to the server, which then collates it with a database for authentication. If authentication is successful, an authentication token is returned to the device.

[2123] Profile Management

[2124] After logging in, users can add or update their profile information, including their interests. The device sends the entered profile information to the server, which stores it in a database. The stored data is then used to match users with other users.

[2125] User matching

[2126] The server searches for and extracts other users who share common interests based on the profile information of the logged-in user. Matching users are added to a matching list, which is sent to the device. The user then selects the person they want to chat with from the displayed list and presses the Start Chat button.

[2127] Real-time conversation generation

[2128] The user enters a message on the chat screen and clicks the send button. The device sends the message to the server, which then uses the generative AI model to generate an appropriate reply. The generated reply is sent from the server to the chat partner's device and displayed in the chat window.

[2129] Event Information

[2130] Users can request information about events taking place in the cafe via a tablet or smartphone. This command is sent to the server, which then uses the mobile control command means to instruct the robot based on the command, and the robot then performs the specified action, such as reading out information about the event. The results of the robot's actions are reported to the server, which then notifies the terminal of the results.

[2131] Hardware and software used

[2132] Hardware: Tablets, smartphones, robots, servers

[2133] Software: User profile management software, generative AI models (e.g., GPT-3), authentication systems, matching algorithms, real-time chat software

[2134] Specific examples

[2135] For example, Person A and Person B visit a cafe and log in from their respective smartphones. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the devices notify Person A and Person B, and they begin chatting with each other. When Person A types and sends "What movies do you recommend these days?" in the chat, the server uses a generative AI model to generate an appropriate response, which is displayed on Person B's device. Furthermore, if Person A requests information about events, the robot will provide information about events currently being held in the cafe.

[2136] Prompt Sentence Examples

[2137] Simply launch the SmartCafe Connect app, log in, and update your interest profile. Then, check your match list and start chatting with other users who share your interests. If you request event information, a robot in the cafe will guide you to the event.

[2138] Login name: User name

[2139] Password:Password

[2140] Interests: Music, movies

[2141] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2142] Step 1:

[2143] Login Authentication

[2144] The user accesses the login page using a tablet device installed in the cafe or their own smartphone and enters their name and password. The device sends this input information to the server. The server compares the received user information with a database, and if authentication is successful, it generates an authentication token and sends it back to the device. The device saves the authentication token and moves the user to the next step.

[2145] Input: User name, password

[2146] Output: Authentication token

[2147] Step 2:

[2148] Profile Management

[2149] After logging in, users access a page where they can enter and update their profile information, including their interests. The device sends the entered profile information to the server, which stores this information in a database and uses it to match users with other users.

[2150] Input: User profile information (interests, concerns)

[2151] Output: Profile information stored in a database

[2152] Step 3:

[2153] User matching

[2154] The server searches for other users who share common interests based on the logged-in user's profile information and adds those users to a matching list. This matching list is sent to the user's device, which then displays it to the user. The user selects the person they want to chat with from the displayed list and presses the start chat button.

[2155] Input: Profile information stored in the database

[2156] Output: Matching list

[2157] Step 4:

[2158] Real-time conversation generation

[2159] The user enters a message on the chat screen and clicks the send button. The device sends the entered message to the server, which analyzes the message and sends a request to the generative AI model. The generative AI model generates an appropriate response to the message and sends it back to the server. The server receives the generated response and sends it to the device of the chat partner. The device displays the received message in the chat window.

[2160] Input: User's message

[2161] Output: The response from the generative AI model

[2162] Step 5:

[2163] Event Information

[2164] A user requests a specific action, such as an event announcement, via a tablet or smartphone. The device sends this command to the server. The server receives the command and sends a control command to the robot using the mobile object control command means. The robot receives the command and performs the specified action (e.g., reading out an event announcement). The robot reports the results of its action to the server, which then notifies the device of the result.

[2165] Input: User's event information request

[2166] Output: Event information by robot

[2167] Specific behavior:

[2168] Server: User authentication, storing information in a database, matching, requests to the generative AI model, sending vehicle control commands

[2169] Device: Sending user input, storing authentication tokens, displaying match lists, sending and receiving chat messages

[2170] Users: Log in, enter profile information, use chat, and send event invitation requests

[2171] Robot: Event guide execution 34,,

[2172] 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.

[2173] The present invention is a system for promoting communication between users in social spaces such as cafes. The system includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a robot control command means, and an emotion engine.

[2174] Specific embodiments of the system and program processing will be described below.

[2175] Login Process

[2176] The user operates a tablet device installed in the cafe and accesses the login page. The user enters the required information such as name and password and clicks the login button.

[2177] The terminal transmits the input user information to the server.

[2178] The server checks the received user information against a database, and if authentication is successful, generates an authentication token and returns it to the terminal.

[2179] The terminal stores the authentication token and displays a successful login to the user.

[2180] Profile Management

[2181] After logging in, users access a page where they can add or update their profile information, including their interests.

[2182] The terminal transmits the entered profile information to the server.

[2183] The server stores the received profile information in a database and uses it to match users with other users.

[2184] User matching

[2185] Based on the profile information mentioned above, the server searches and extracts users with common interests and creates a matching list.

[2186] The server sends the matching list to each terminal.

[2187] The terminal receives the matching list and displays it to the user.

[2188] The user selects the desired partner from the displayed list and presses the chat start button.

[2189] Real-time conversation generation

[2190] The user enters a message on the chat screen and clicks the send button.

[2191] The terminal transmits the input message to the server.

[2192] The server receives the message and sends a request to the generative AI.

[2193] The generative AI generates an appropriate response to the message and sends it back to the server.

[2194] The server receives the returned message, formats it, and sends it to the terminal.

[2195] The device will display the received message in the chat window.

[2196] Emotion engine integration

[2197] When a user inputs a message on the chat screen, the terminal transmits the input content to the server.

[2198] The server sends the received message to the emotion engine to analyze the user's emotions.

[2199] The emotion engine sends the analysis results back to the server, and the generative AI adjusts the content and style of the response based on those results.

[2200] The server sends the tailored response to the device, which displays it in the chat window.

[2201] As a concrete example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the device notifies Person A and Person B, and they begin chatting.

[2202] When Person A types in and sends "What recent movie do you recommend?", the server sends the message to the generative AI and emotion engine, and the emotion engine detects Person A's feelings of excitement and anticipation. Based on the results, the generative AI generates a response such as "The recent movie I recommend is 'Inception.' It's an amazing movie!" and displays it on Person B's device. In this way, the conversation between Person A and Person B becomes richer and more natural with the intervention of the emotion engine.

[2203] Robot Control

[2204] The user selects and sends a specific action (e.g., requesting event information) from the tablet device.

[2205] The terminal transmits the transmission contents to the server.

[2206] The server sends the request as a control command to the appropriate robot.

[2207] The robot receives commands and performs the specified action (e.g., reading out event information).

[2208] The robot reports the results of its operations to the server, and the server notifies the terminal of the results.

[2209] In this way, by implementing the system of the present invention, communication between users in a cafe becomes smooth and enjoyable, and the introduction of an emotion engine enables even deeper communication.

[2210] The processing flow will be explained below.

[2211] (Login process)

[2212] Step 1:

[2213] The user operates a tablet device installed in the cafe and accesses the login page.

[2214] Step 2:

[2215] The user enters login information such as name and password and clicks the login button.

[2216] Step 3:

[2217] The terminal sends the entered login information to the server.

[2218] Step 4:

[2219] The server receives the login information and checks it against the user information in its database.

[2220] Step 5:

[2221] If the server is successful in the authentication, it generates an authentication token and sends it to the terminal.

[2222] Step 6:

[2223] The terminal stores the received authentication token and displays a successful login to the user.

[2224] (Profile Management)

[2225] Step 1:

[2226] After the user logs in, they access the profile settings page.

[2227] Step 2:

[2228] The user enters their profile information, such as interests, and clicks the save button.

[2229] Step 3:

[2230] The device transmits the entered profile information to the server.

[2231] Step 4:

[2232] The server stores the received profile information in a database.

[2233] (User matching)

[2234] Step 1:

[2235] The server searches for users with common interests based on each user's profile information.

[2236] Step 2:

[2237] The server extracts the relevant users and creates a matching list.

[2238] Step 3:

[2239] The server sends the matching list to each device.

[2240] Step 4:

[2241] The terminal displays the received matching list to the user.

[2242] Step 5:

[2243] The user selects a chat partner from the displayed list and presses the chat start button.

[2244] (Generating real-time conversations)

[2245] Step 1:

[2246] The user enters a message in the chat screen and clicks the send button.

[2247] Step 2:

[2248] The terminal sends the input message to the server.

[2249] Step 3:

[2250] The server analyzes the received message and sends a request to the generative AI.

[2251] Step 4:

[2252] The generative AI generates an appropriate response to the message and sends it back to the server.

[2253] Step 5:

[2254] The server receives the returned message, formats it, and sends it to the terminal.

[2255] Step 6:

[2256] Displays messages received by the device in the chat window.

[2257] (Emotion engine integration)

[2258] Step 1:

[2259] The user enters a message in the chat screen and clicks the send button.

[2260] Step 2:

[2261] The terminal sends the input message to the server.

[2262] Step 3:

[2263] The server sends the received message to the emotion engine.

[2264] Step 4:

[2265] An emotion engine analyzes the message and identifies the user's emotion.

[2266] Step 5:

[2267] The emotion engine sends the analysis results back to the server.

[2268] Step 6:

[2269] The server requests the generative AI to generate a message based on the results of the emotion engine.

[2270] Step 7:

[2271] The generative AI generates an appropriate response based on the emotion and sends it back to the server.

[2272] Step 8:

[2273] The server receives the returned message, formats it, and sends it to the terminal.

[2274] Step 9:

[2275] Displays messages received by the device in the chat window.

[2276] (Robot Control)

[2277] Step 1:

[2278] The user selects a specific action (e.g., requesting event information) on the tablet device and clicks the send button.

[2279] Step 2:

[2280] The terminal sends the transmission content to the server.

[2281] Step 3:

[2282] The server sends the received request as a command to the appropriate robot.

[2283] Step 4:

[2284] The robot receives commands and performs the specified action (e.g., reading out information about an event).

[2285] Step 5:

[2286] The robot reports the results of its actions to the server.

[2287] Step 6:

[2288] The server checks the results of the operation and sends additional commands to the robot if necessary.

[2289] Step 7:

[2290] The terminal notifies the user that the robot's operation was successful.

[2291] These specific processing steps make communication between users in the cafe smooth and enjoyable, and the intervention of the emotion engine enables deeper communication.

[2292] Example 2

[2293] 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."

[2294] In existing social forums, communication between users is not smooth, and support for creating new interactions is insufficient. In particular, it is difficult to generate natural conversations in real time and respond with consideration for emotions. Furthermore, it is difficult to appropriately match users based on their interests, making it difficult to promote interactions with people who share their interests.

[2295] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2296] In this invention, the server includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a sentiment analysis means using a sentiment analysis engine, an AI model response generation means based on the sentiment analysis engine, and a robot control command means. This enables natural conversation between users, realizes responses that take emotions into consideration, and promotes effective matching based on common interests.

[2297] A "login authentication means" is a means for verifying the identity of a user when the user accesses a system.

[2298] "User profile management means" refers to a means by which a user can register and update their own interests and other information in the system.

[2299] The "means for generating conversation data" is a means for generating information necessary for conversation between users.

[2300] "User matching means" refers to a means for finding and matching users who share common interests based on user profile information.

[2301] A "real-time conversation management means" is a means for controlling and managing a conversation in real time so that the conversation progresses continuously and fluently.

[2302] The "emotion analysis means using an emotion analysis engine" is a means for analyzing the user's emotions from the input message and outputting the results.

[2303] "A generative AI model response generation means based on an emotion analysis engine" is a means for generating an appropriate response based on the output of an emotion analysis engine.

[2304] The "robot control command means" is a means for sending specific commands to the robot and controlling its operation.

[2305] The present invention is a system for promoting communication between users in social settings such as cafes. The system includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a sentiment analysis means using a sentiment analysis engine, a generative AI model response generation means based on the sentiment analysis engine, and a robot control command means.

[2306] During the login process, the user operates a tablet device installed in the cafe to access the login page. After entering the required information such as their name and password, the user clicks the login button. The device sends the entered user information to the server, which then compares the received user information with its database. If authentication is successful, the server generates an authentication token and returns it to the device. The device saves the authentication token and displays a message to the user indicating that login was successful.

[2307] Next, after logging in, the user accesses a page to add or update profile information, including interests. The device sends the entered profile information to the server, which stores the received profile information in a database and uses it to match users with other users.

[2308] During the matching process, the server searches for and extracts users with common interests based on profile information in the database, and creates a matching list. The server then sends the matching list to each device, which receives it and displays it to the user. The user then selects the desired partner from the displayed list and presses the button to start chatting.

[2309] In real-time conversation generation, a user enters a message on the chat screen and clicks the send button. The device sends the entered message to the server, which receives the message and sends a request to the generative AI. The generative AI generates an appropriate response to the message and sends it back to the server. The server receives the returned message, formats it, and sends it to the device, which then displays the received message in the chat window.

[2310] The system also integrates a sentiment analysis engine. When a user types a message on the chat screen, the device sends the input to the server, which then sends the received message to the sentiment analysis engine, which analyzes the user's emotions. The sentiment analysis engine then sends the analysis results back to the server, and the generative AI adjusts the content and style of the reply based on the results. The server then sends the adjusted reply to the device, where it is displayed in the chat window.

[2311] As a concrete example, user A and user B visit a cafe and each log in. User A likes music, and user B likes movies. After logging in, their profile information is updated, and the server matches them based on their shared interest in "entertainment." Once matching is complete, the devices notify users A and B, and a chat begins. When user A types and sends the question, "What's a recent movie you recommend?", the server sends the message to the generative AI and the emotion analysis engine, and the emotion analysis engine detects user A's emotions of excitement and anticipation. Based on the results, the generative AI generates a response such as, "The recent movie I recommend is 'Inception.' It's an amazing movie!" and displays it on user B's device. In this way, the conversation between user A and user B becomes richer and more natural with the intervention of the emotion analysis engine.

[2312] It also controls robots. When a user selects and sends a specific action (e.g., requesting event information) from a tablet device, the device sends the request to the server. The server then sends the request as a control command to the appropriate robot, which then receives the command and performs the specified action (e.g., reading out event information). The robot then reports the results of its action to the server, which then notifies the device of the results.

[2313] Examples of prompts for generative AI models include:

[2314] "A user asks, 'What are some recent movie recommendations?' Generate an appropriate response."

[2315] "Based on the results of the sentiment analysis engine, generate responses that reflect the user's feelings of excitement and anticipation."

[2316] In this way, by implementing the system of the present invention, communication between users in the cafe becomes smooth and enjoyable, and the introduction of an emotion analysis engine enables even deeper communication.

[2317] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2318] Specific explanation of program processing

[2319] Step 1:

[2320] Login Process

[2321] Input: User information such as name and password

[2322] process:

[2323] 1. The user operates a tablet device in the cafe, enters their name and password, and clicks the login button.

[2324] 2. The terminal sends the entered user information to the server.

[2325] 3. The server checks the received user information against the information in its database.

[2326] 4. If the authentication is successful, the server generates an authentication token and returns it to the terminal.

[2327] 5. The device stores the authentication token and displays a successful login to the user.

[2328] Output: Authentication token and login result displayed

[2329] Specific examples of behavior:

[2330] The user enters "Yamada Taro" and "password123," and the device sends this information to the server. The server checks it against the database, and if it matches, it returns an authentication token called token12345, and the device displays "Login successful."

[2331] Step 2:

[2332] Profile Management

[2333] Input: Profile information such as interests

[2334] process:

[2335] 1. After logging in, the user visits the profile management page and enters or updates new information.

[2336] 2. The device sends the entered profile information to the server.

[2337] 3. The server stores the received profile information in a database and uses it for future matching.

[2338] Output: Updated profile information saved to database

[2339] Specific examples of behavior:

[2340] Users add interests such as "music, movies, reading" to their profile, and the device sends this information to the server, which stores it in a database.

[2341] Step 3:

[2342] User matching

[2343] Input: Profile information in the database

[2344] process:

[2345] 1. The server searches the profile information in the database and extracts users with common interests.

[2346] 2. The server generates a matching list based on the extraction results and sends it to each device.

[2347] 3. The device receives the matching list and displays it to the user.

[2348] 4. The user selects the desired partner and presses the chat start button.

[2349] Output: Match list and information displayed to the user

[2350] Specific examples of behavior:

[2351] The server matches user A and user B based on the common interests of "music and movies," and the device displays "A and B have been matched."

[2352] Step 4:

[2353] Real-time conversation generation

[2354] Input: The message entered by the user

[2355] process:

[2356] 1. The user enters a message in the chat screen and clicks the send button.

[2357] 2. The terminal sends the entered message to the server.

[2358] 3. The server sends the received message as a request to the generative AI model.

[2359] 4. The generative AI model generates an appropriate response to the message and sends it back to the server.

[2360] 5. The server formats the returned message and sends it to the terminal.

[2361] 6. The device will display the received message in the chat window.

[2362] Output: The generated reply message

[2363] Specific examples of behavior:

[2364] The user types "What are some recent recommended movies?", the device sends the message to the server, and the server sends the prompt "User asks about recent recommended movies" to the generative AI model. The generative AI model replies "The recent recommended movie is 'Inception'", which is displayed on the device via the server.

[2365] Step 5:

[2366] Sentiment analysis engine integration

[2367] Input: The message entered by the user

[2368] process:

[2369] 1. When a user enters a message on the chat screen, the device sends the content to the server.

[2370] 2. The server sends the received message to the sentiment analysis engine.

[2371] 3. The sentiment analysis engine analyzes the input message and detects the user's emotions.

[2372] 4. The sentiment analysis engine sends the analysis results back to the server, and the server sends a prompt based on the analysis results to the generative AI model.

[2373] 5. The generative AI model generates a tailored response based on the sentiment analysis results and sends it back to the server.

[2374] 6. The server sends this adjusted response to the device, which displays it in the chat window.

[2375] Output: Tailored response message based on sentiment analysis results

[2376] Specific examples of behavior:

[2377] A user excitedly types, "What's the best recent movie?" The sentiment analysis engine detects this excitement, and the generative AI model adjusts and responds, "The best recent movie is 'Inception.' It's an amazing movie!"

[2378] Step 6:

[2379] Robot Control

[2380] Input: User action selection (e.g., event information request)

[2381] process:

[2382] 1. The user selects and submits a specific action (e.g., requesting event information) on a tablet device.

[2383] 2. The device sends the selection to the server.

[2384] 3. The server sends the request as a control command to the appropriate robot.

[2385] 4. The robot receives the control command and performs the specified action (e.g., reading out an event announcement).

[2386] 5. The robot reports the results of its operation to the server, and the server notifies the terminal of the results.

[2387] Output: Robot operation results and notification

[2388] Specific examples of behavior:

[2389] When the user selects "I want to hear about the next event," the device sends a request to the server, and the server sends a command to the robot to "read out the event information." The robot reads out the information, reports to the server that "the event information has been read out," and notifies the device.

[2390] (Application example 2)

[2391] 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."

[2392] In today's social settings, it is difficult to foster communication between users and realize natural and rich conversations. Conventional systems lack the ability to match users based on their interests and generate appropriate conversations based on their emotions, presenting technical challenges for achieving deeper communication. Furthermore, to efficiently operate these functions in physical stores, it is necessary to integrate multiple technologies and improve the user experience.

[2393] 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.

[2394] In this invention, the server includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a robot control command means, an emotion analysis means, and an application means including chat conversations with users. This makes it possible to realize natural and rich communication by matching users with other users who share common interests based on their profile information and generating and adjusting conversation content that takes emotions into consideration using an emotion analysis engine.

[2395] The "login authentication means" is an authentication process used by a user to access the system, and involves inputting authentication information such as a user name and password to perform authentication.

[2396] "User profile management means" refers to a function for adding, updating, and managing profile information such as a user's interests.

[2397] "Means for generating conversational data" is a function that uses generative AI to generate appropriate responses based on messages entered by users.

[2398] "User matching means" is a function that searches for and extracts other users who share common interests based on the user's profile information, and creates a matching list.

[2399] "Real-time conversation management means" is a function that manages the sending and receiving of messages on the chat screen in real time, ensuring that conversations progress smoothly.

[2400] The "robot control command means" is a function that sends control commands to the robots in the cafe to cause them to perform specific actions, and manages the robots' operations.

[2401] The "emotion analysis means" is a function that analyzes messages entered by users and adjusts the content of conversations by detecting their emotions.

[2402] "Application means including chat conversations with users" refers to an application that is installed on a smartphone or tablet device and provides matching and chat functions between users.

[2403] The present invention is a system for promoting communication between users in social spaces such as cafes. The system includes a login authentication means, a user profile management means, a conversation data generation means, a user matching means, a real-time conversation management means, a robot control command means, an emotion analysis means, and an application means including a chat conversation with a user.

[2404] Login authentication method

[2405] The user accesses the login page using a tablet device or smartphone installed in the cafe and enters their name and password to log in. The device sends the entered user information to the server, which then performs authentication and returns an authentication token if successful.

[2406] Profile Management Methods

[2407] After logging in, the user accesses a page for adding or updating profile information, including interests, and enters the profile information. The device sends the entered information to the server, which stores it in a database.

[2408] User matching method

[2409] The server searches for and extracts users with common interests based on the saved profile information, creates a matching list, and sends the matching list to each device, which then displays the list to the user.

[2410] Real-time conversation management

[2411] When a user enters and sends a message on the chat screen, the device sends the message to the server, which then sends the message to the generative AI model, which generates an appropriate response. The response is then adjusted by the sentiment analysis means and sent back to the device via the server.

[2412] Robot control command means

[2413] When a user sends a specific action (e.g., a request for event information), the device sends the request to the server, which then sends the request as a control command to the appropriate robot, which then performs the specified action.

[2414] Emotion analysis means

[2415] The sentiment analyzer analyzes messages entered by users to detect their emotions, and the server sends the results to a generative AI model to adjust the content and style of the reply, making the conversation more natural and rich.

[2416] Application means including chat conversations with users

[2417] Chat conversations are conducted through an application installed on smartphones and tablets, which provides comprehensive profile entry, matching, and chat functions.

[2418] Specific examples

[2419] For example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches Person A and Person B based on their common interest in "entertainment." Once matching is complete, the device notifies Person A and Person B, and the chat begins.

[2420] When Person A types in "What recent movie would you recommend?" and submits it, the server uses emotion analysis to detect Person A's feelings of excitement and anticipation, and based on the results, the generative AI model generates a response saying, "The recent movie I recommend is 'Inception.' It's an absolutely amazing film!" and displays it on Person B's device.

[2421] Prompt Sentence Examples

[2422] What recent movies do you recommend?

[2423] What recent music albums do you recommend?

[2424] What's today's recommended cafe menu?

[2425] This will make communication between users in the cafe smooth and enjoyable, and the introduction of an emotion engine will enable even deeper communication.

[2426] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2427] Step 1:

[2428] The user accesses the login page using a tablet or smartphone installed in the cafe and logs in by entering their username and password. The device sends the entered authentication information to the server, which checks it against a database. If authentication is successful, the server issues an authentication token and returns it to the device. The authentication token is then displayed to the user.

[2429] Input: Username, Password

[2430] Data processing: Database matching of authentication information

[2431] Output: Authentication token

[2432] Step 2:

[2433] After logging in, users enter and update their profile information, including their interests. The device sends the entered profile information to the server, which stores it in a database.

[2434] Input: Profile information (interests, etc.)

[2435] Data processing: Profile information stored in a database

[2436] Output: Profile information update results

[2437] Step 3:

[2438] The server searches for and extracts users with common interests based on the saved profile information, creating a matching list. The server then sends the matching list to each device, which then displays it to the user.

[2439] Input: Profile information stored in the database

[2440] Data processing: Creating a matching list based on common interests

[2441] Output: Matching list

[2442] Step 4:

[2443] When a user enters a message on the chat screen and presses the send button, the device sends the message to the server. The server sends the message to a generative AI model, which generates an appropriate response. The generated response is then sent to a sentiment analysis means, where it is adjusted based on the user's emotions. The adjusted response is then sent back to the device via the server and displayed in the chat window.

[2444] Input: Chat message

[2445] Data processing: Response generation using generative AI models, adjustments using sentiment analysis methods

[2446] Output: Adjusted response

[2447] Step 5:

[2448] When a user requests a robot in a cafe to perform a specific action (e.g., an event announcement), the terminal sends the request to the server. The server then sends the request as a control command to the appropriate robot, which then executes the specified action. The robot then reports the results of its action to the server, which then notifies the terminal of the results.

[2449] Input: Request to the robot (e.g., event information)

[2450] Data processing: generating and transmitting robot control commands

[2451] Output: Robot movement results

[2452] For example, Person A and Person B visit a cafe and each log in. Person A likes music, and Person B likes movies. After logging in, their profile information is updated, and the server matches them based on their shared interest in "entertainment," sending a notification to their device. User A then types, "What's a recommended recent movie?" The server's sentiment analysis engine analyzes this message, and the generative AI model generates a response: "The recommended recent movie is 'Inception.' It's an amazing movie!", which is displayed on Person B's device.

[2453] The above are the specific processing steps performed by this system.

[2454] 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.

[2455] 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.

[2456] 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.

[2457] 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.

[2458] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2459] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2460] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the mor...

Claims

1. a login authentication means for authenticating a user; a user profile management means for managing profile information including user interests; A means for generating conversation data that uses generative AI to generate conversation content between users in real time; A user matching means for finding and matching with other users who share common interests based on the user's profile information; a real-time conversation management means for managing the content of conversations communicated in real time between users; a robot control command means for sending commands to the robot so that the robot provides guidance and services to users; A system including:

2. 10. The system of claim 1, wherein users are matched with each other based on common interests or concerns between the users.

3. The system according to claim 1, which uses generative AI to generate conversation content between users in real time.

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