System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving and matching user credentials based on a database; means for generating a session ID and notifying the user if the user is successfully authenticated; means for generating a AI chat bot based on the user credentials and setting an optimal dialogue scenario; and means for storing a log of conversations between the chat bot and the user in real-time for later analysis.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern society, many people suffer from stress and worries, which often have a negative impact on their mental health. Conventional mental health support requires face-to-face consultations with specialists, making it difficult to provide immediate support and is limited by clinic hours and physical location. Therefore, there is a need for a support system that is available 24 hours a day and provides immediate support. [Means for solving the problem]

[0005] The present invention builds an online mental health support system that provides users with an AI chatbot that can respond immediately 24 hours a day. It includes a means for receiving user authentication information and verifying it against a database, and a means for generating a session ID and notifying the user if the user authentication is successful. It also includes a means for generating an AI chatbot based on user data and setting an optimal dialogue scenario, as well as a means for saving a conversation log between the chatbot and the user in real time for later analysis. It also includes a means for receiving input messages from the user and sending them to a server, a means for receiving response messages from the server and displaying them to the user, and a means for suggesting referral to a specialist if necessary. This allows users to receive instant mental health support, maximizing its effectiveness.

[0006] "User authentication" is the process of verifying that a user is a legitimate user by checking the information (e.g., user ID and password) entered by the user when using a system against a database.

[0007] A "session ID" is a unique identifier that is generated after a user is successfully authenticated and is used to maintain the state of the session.

[0008] An "AI chatbot" is a program that uses artificial intelligence technology to interact with users and provide appropriate responses and advice in response to user input.

[0009] A "dialogue scenario" is a set of response patterns and question configurations that an AI chatbot uses in dialogue with a user, and is selected depending on the user's situation.

[0010] A "conversation log" is a record of the dialogue between a user and an AI chatbot, and is data that is stored for later analysis.

[0011] "Referral" is the process by which an AI chatbot suggests consulting with an expert based on the user's situation. [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 showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[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] This invention provides a 24-hour online mental health support system using an AI chatbot. This system provides immediate and effective mental health support to users by linking the user, terminal, and server components.

[0034] Server Roles

[0035] The server plays a central role in this system. First, it receives the authentication information sent by the user from the device and checks it against a database. If the user is authenticated, the server generates a session ID and sends it to the device to start the session. Next, the server generates an AI chatbot based on the user data. This AI chatbot sets up an optimal dialogue scenario based on the user's past stress level and conversation log. Furthermore, the server saves the conversation log between the user and the AI ​​chatbot in real time and manages it as data for later analysis.

[0036] Device Role

[0037] The terminal provides an interface that connects the user and the server. When the user launches the application, an authentication information input screen is displayed. The user enters the authentication information, and the terminal sends it to the server. When a session ID is returned from the server, the terminal initializes the session and displays a chat interface to the user. When the user enters a message, the terminal sends it to the server, receives a response message from the server, and displays it to the user.

[0038] User operations

[0039] To use this system, users first access the application from their device. After entering their authentication information on the login screen and pressing the login button, the server performs authentication. If authentication is successful, the user is redirected to a chat interface. Here, the user enters their stress and worries and receives appropriate advice from an AI chatbot. If necessary, the user can also be referred to a specialist.

[0040] Specific examples

[0041] For example, imagine a situation where a user is feeling very stressed at work. The user opens an application and types, "I'm stressed at work." This message is sent to the server via the device, and the server generates a response using an AI chatbot. The AI ​​chatbot asks, "What specifically is causing you stress?" and suggests next steps based on the user's response. If the user answers, "A particular project is putting a lot of pressure on me," the AI ​​chatbot might suggest, "Would you like me to provide you with specific support or resources to help with the progress of this project?"

[0042] This entire conversation takes place in real time, and the server stores the conversation log, allowing for continuous tracking of the user's mental health status. If necessary, the system can smoothly refer the user to a specialist.

[0043] As described above, the present invention provides immediate and effective support for the user's mental health care.

[0044] The processing flow will be explained below.

[0045] Program processing flow

[0046] Server Processing Steps

[0047] Step 1:

[0048] Server receives authentication information (user ID and password) sent by the user.

[0049] Step 2:

[0050] The server queries the database for authentication information and checks whether the corresponding user exists.

[0051] Step 3:

[0052] If the user exists, the server generates a session ID and sends it to the terminal along with a response indicating successful authentication.

[0053] Step 4:

[0054] For users who are successfully authenticated, the server generates an AI chatbot based on the user data.

[0055] Step 5:

[0056] The server sets up the optimal dialogue scenario based on user data and applies it to the AI ​​chatbot.

[0057] Step 6:

[0058] Conversation logs between users and AI chatbots are saved in real time and managed as data for later analysis.

[0059] Terminal processing steps

[0060] Step 1:

[0061] The terminal displays a screen for the user to input authentication information.

[0062] Step 2:

[0063] When the user inputs the authentication information and presses the send button, the terminal sends the authentication information to the server.

[0064] Step 3:

[0065] When the server returns the session ID, the terminal initializes the session.

[0066] Step 4:

[0067] The terminal receives the chatbot data sent from the server and displays a user-friendly chat interface.

[0068] Step 5:

[0069] When the user enters a message, the terminal sends the message to the server and waits for a response.

[0070] Step 6:

[0071] The terminal that receives the response message from the server displays it to the user.

[0072] User operation steps

[0073] Step 1:

[0074] The user starts the application and enters authentication information (user ID and password).

[0075] Step 2:

[0076] The user presses the login button to request authentication from the server.

[0077] Step 3:

[0078] Upon successful authentication, the user is redirected to the chat interface.

[0079] Step 4:

[0080] Users input their stress and worries into a chat interface.

[0081] Step 5:

[0082] The user receives a response from the AI ​​chatbot and checks the advice and solutions displayed.

[0083] Step 6:

[0084] Accept expert referrals suggested by the AI ​​chatbot when needed.

[0085] This series of steps allows users to receive immediate mental health support 24 hours a day.

[0086] Example 1

[0087] 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."

[0088] Mental health care is becoming an increasingly important issue in modern society. However, it is difficult to provide professional mental health support available 24 hours a day. There is a need for a system that can comprehensively manage a wide range of elements, such as user authentication, data management, and the provision of appropriate support, and provide immediate and effective support. Furthermore, when referral to a specialist is necessary, a system is also needed to ensure smooth referrals.

[0089] 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.

[0090] In this invention, the server includes means for receiving user authentication information and verifying it based on a database, means for generating a session ID and notifying the user if the user authentication is successful, means for generating a conversational bot using a generative AI model based on user data and setting an optimal conversation scenario, means for saving a conversation log between the conversational bot and the user in real time so that it can be analyzed later, and means for analyzing the conversation log and suggesting a referral to a specialist if necessary. This realizes online mental health support available 24 hours a day, allowing users to receive immediate and effective mental health care.

[0091] "Authentication Information" means the username, password, or other means of authentication used by a User to access a System.

[0092] "Database" refers to a system that stores user authentication information and past data and performs verification and reference as needed.

[0093] "Session ID" refers to an identifier that is generated by the server after a user has been successfully authenticated and that uniquely identifies the user's session.

[0094] A "generative AI model" refers to an artificial intelligence model that generates appropriate dialogue scenarios based on user data.

[0095] A "conversational bot" refers to a chatbot built on a generative AI model to engage in dialogue with users.

[0096] A "dialogue scenario" refers to a series of appropriate dialogue content presented by a generative AI model in a dialogue with a user.

[0097] A "conversation log" refers to the history of messages exchanged between a conversational bot and a user.

[0098] "Professional referral" refers to the process of referring a user to a professional mental health care provider, if necessary.

[0099] "Real-time" refers to the system's ability to interact with and process users instantly.

[0100] This invention provides a 24-hour online mental health support system using an AI chatbot. This system provides immediate and effective mental health support to users by linking the user, terminal, and server components.

[0101] Server Roles

[0102] The server plays a central role in this system. First, it receives the authentication information sent by the user from the device and checks it against a database. Databases such as MySQL or PostgreSQL are typically used. Once the user is authenticated, the server generates a session ID and sends it to the device to start the session. The session ID is usually generated as a UUID (Universally Unique Identifier). The server then generates a conversational bot based on the user data using a generative AI model. OpenAI's GPT-4 is one example of a generative AI model. This conversational bot sets an optimal conversation scenario based on the user's past stress level and conversation log. Furthermore, the server saves the conversation log between the user and the conversational bot in real time and manages it as data for later analysis. Storage services such as Amazon S3 and Google Cloud Storage can be used.

[0103] Device Role

[0104] The terminal provides an interface that connects the user and the server. When the user starts the application, an authentication information input screen is displayed. The user enters their username and password here. Once the input is complete, the terminal sends it to the server. When the server returns a session ID, the terminal initializes the session and displays a chat interface to the user. When the user enters a message, the terminal sends it to the server, receives a response message from the server in real time, and displays it to the user.

[0105] User operations

[0106] To use this system, users first access the application from their device. After entering their authentication information on the login screen and pressing the login button, the server performs authentication. If authentication is successful, the user is redirected to a chat interface. Here, the user inputs their stress and worries and receives appropriate advice from a conversational bot using a generative AI model. If necessary, the user can also be referred to an expert.

[0107] Specific examples

[0108] For example, a user might type, "I'm feeling stressed at work." The device then sends this message to the server. The server uses a generative AI model to generate a response, asking, "What specifically is causing you stress?" If the user types, "A particular project is putting a lot of pressure on me," the conversational bot might suggest, "Would you like us to provide you with specific support or resources to help with the progress of this project?" This entire conversation takes place in real time, and the server stores the conversation log, continuously tracking the user's mental health status. If necessary, the server can smoothly refer the user to a specialist.

[0109] Prompt Sentence Examples

[0110] "I'm stressed about a particular work issue. What specifically is causing it? And what specific solutions do you suggest for that issue?"

[0111] As described above, the present invention provides immediate and effective support for the user's mental health care.

[0112] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0113] Step 1:

[0114] The user launches the application and enters their authentication information (username and password).

[0115] Input: Username and Password

[0116] How it works: A user accesses a login screen on their device and enters their credentials.

[0117] Output: The entered credentials

[0118] Step 2:

[0119] The terminal sends the user's authentication information to the server.

[0120] Input: Authentication information (username and password)

[0121] How it works: The device sends authentication information to the server using an HTTP POST request.

[0122] Output: Authentication information sent to the server

[0123] Step 3:

[0124] The server checks the credentials against a database and authenticates the user.

[0125] Input: Credentials

[0126] What happens: The server queries a database (e.g. MySQL, PostgreSQL) and matches the credentials. If successful, the user is authenticated.

[0127] Output: User authentication result (success or failure)

[0128] Step 4:

[0129] When authentication is successful, the server generates a session ID and notifies the terminal.

[0130] Input: Authentication result (success)

[0131] How it works: If authentication is successful, the server generates a session ID as a unique UUID and sends it to the device.

[0132] Output: Session ID

[0133] Step 5:

[0134] The terminal receives the session ID and initializes the session.

[0135] Input: Session ID

[0136] Behavior: The terminal uses the received session ID to initialize the session and displays a login success screen to the user.

[0137] Output: Session initialized

[0138] Step 6:

[0139] The server obtains the user's past data (stress level, conversation log) and generates a conversational bot using a generative AI model.

[0140] Input: Session ID, User Data

[0141] How it works: The server retrieves the user's past data from the database and sets the parameters of a generative AI model (e.g., GPT-4) to generate a conversational bot.

[0142] Output: The generated conversational bot

[0143] Step 7:

[0144] The server generates an initial message for the conversational bot and sends it to the terminal.

[0145] Input: Generated conversational bot, user data

[0146] How it works: The server launches the conversational bot, generates an initial question or message, and sends it to the user.

[0147] Output: Initial message

[0148] Step 8:

[0149] The device receives the initial message and displays it in the chat interface.

[0150] Input: initial message

[0151] Behavior: The terminal displays the initial message it receives in the chat interface.

[0152] Output: Initial message displayed

[0153] Step 9:

[0154] The user inputs their stress and worries into a chat interface.

[0155] Input: Details of stress and worries

[0156] How it works: The user enters their stress and worries and presses the send button.

[0157] Output: The input message

[0158] Step 10:

[0159] The terminal sends the user's message to the server.

[0160] Input: The message entered

[0161] Operation: The terminal sends the user's message to the server.

[0162] Output: Message sent to the server

[0163] Step 11:

[0164] The server generates a response message using a generative AI model based on the user's message.

[0165] Input: User message, generative AI model

[0166] How it works: The server parses the user's message and uses a generative AI model to generate an appropriate response message.

[0167] Output: Response message

[0168] Step 12:

[0169] The server sends a response message to the terminal.

[0170] Input: Response message

[0171] Operation: The server sends the generated response message to the terminal.

[0172] Output: Response message sent to the terminal

[0173] Step 13:

[0174] The terminal receives the response message and displays it to the user.

[0175] Input: Response message

[0176] Behavior: The device displays the received reply message in the chat interface.

[0177] Output: The displayed response message

[0178] Step 14:

[0179] The server stores the conversation log between the user and the conversational bot in real time.

[0180] Input: User's message, reply message

[0181] How it works: The server stores all messages between users and conversational bots in a database.

[0182] Output: Saved conversation logs

[0183] Step 15:

[0184] The server analyzes the conversation log and suggests referrals to experts if necessary.

[0185] Input: conversation log

[0186] How it works: The server analyzes the saved conversation logs and, if it determines that a referral to an expert is necessary, makes such a suggestion to the user.

[0187] Output: Referral message if necessary

[0188] The above is the flow of processing of the program of this system.

[0189] (Application example 1)

[0190] 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."

[0191] Conventional mental health care systems often delay providing appropriate support for users' stress and worries. Furthermore, in brick-and-mortar stores, it can be difficult for staff to constantly respond to customers, which can lead to a decline in customer satisfaction. To solve these problems, a fast and effective customer support system is needed, but current technology does not provide a sufficient solution.

[0192] 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.

[0193] In this invention, the server includes means for receiving user authentication information and verifying it based on a database, means for generating a session ID and notifying the user if the user authentication is successful, means for generating an AI chatbot using a generative AI model based on user data and setting an optimal dialogue scenario, means for saving a conversation log between the chatbot and the user in real time for later analysis, and means for the generated dialogue scenario to include responses generated based on prompt sentences intended for customer support in a physical store. This enables effective mental health care for users and prompt and appropriate customer support in a physical store.

[0194] "Authentication information" refers to information used by a user when logging in to a system, such as a user name and password.

[0195] A "database" is a system for organizing and managing a wide variety of data, and is a place where user authentication information, conversation logs, etc. are stored.

[0196] "Session ID" means a unique identifier generated after successful user authentication to identify an interactive session between a particular user and a system.

[0197] A "generative AI model" is an algorithm that uses artificial intelligence techniques to design a conversational interface based on user data.

[0198] An "AI chatbot" is a program that uses artificial intelligence to automatically generate responses to users' questions and inquiries.

[0199] A "dialogue scenario" refers to a series of scenes and responses that define the flow and content when an AI chatbot converses with a user.

[0200] A "conversation log" is data that records the content of the conversation between a user and an AI chatbot, and is saved in a format that can be analyzed later.

[0201] A "prompt" is a piece of text or phrase that serves as a starting point for a generative AI model to generate a specific response.

[0202] A "brick and mortar store" refers to a retail or service establishment that has a physical presence in a physical location where face-to-face commerce with customers takes place.

[0203] "Customer support" refers to the activity of providing assistance to customers to respond to and resolve questions or problems that arise when using a product or service.

[0204] "Referral to an expert" refers to connecting the user to a person or department with specialized knowledge if the AI ​​chatbot determines this is necessary through dialogue.

[0205] This invention relates to an AI chatbot system for customer support in brick-and-mortar stores. This system involves user, terminal, and server components interacting with each other to provide instant and effective question responses and support to users.

[0206] Server Roles

[0207] The server plays a central role in this system. Its functions are realized by the following procedure.

[0208] 1. Receiving and verifying authentication information

[0209] The server receives the authentication information sent by the user from the terminal and compares it with the database. If the authentication is successful, the server generates a session ID and notifies the user terminal.

[0210] 2. Use of generative AI models

[0211] The AI ​​chatbot is generated using a generative AI model based on user data and the optimal dialogue scenario is set up. Specifically, prompts are prepared based on the user's past inquiry history and stress level, and the chatbot's responses are generated.

[0212] 3. Save conversation logs

[0213] The conversation log between the chatbot and the user is saved in real time and can be analyzed later. This allows us to understand user behavior patterns and problems, leading to further improvements to the service.

[0214] Hardware used: Server

[0215] Software used: Generative AI models, database management system

[0216] Device Role

[0217] The terminal provides an interface between the user and the server.

[0218] 1. Enter and submit authentication information

[0219] When a user launches an application, a screen for entering authentication information appears. The user enters the authentication information, and the device sends it to the server.

[0220] 2. Displaying the chat interface

[0221] Once the server returns a session ID, the terminal initializes the session and displays a chat interface to the user. When the user enters a message, the terminal sends it to the server, receives a response message from the server, and displays it to the user.

[0222] Hardware used: smartphone, tablet

[0223] Software used: Front-end application (e.g., Flutter, React Native)

[0224] User operations

[0225] To use this system, a user first accesses the application from their device and enters their authentication information on the login screen. After successful authentication, the user is redirected to a chat interface. Here, the user enters their question or concern and receives appropriate advice or a response from the AI ​​chatbot. For example, if a user enters "I'd like to know more about this product," this message is sent to the server via the device, and the server uses a generative AI model to generate a response. An example of a prompt for the generated response is "User: "I'd like to know more about this product"\nAI:". Based on this prompt, the AI ​​chatbot returns a detailed answer such as: "Of course. This product is made of high-quality materials and has the following features..."

[0226] This entire dialogue is conducted in real time, and the server stores the conversation log, allowing for continuous tracking of the user's behavior and needs. If necessary, the user can be smoothly referred to an expert. This improves the customer experience in physical stores and makes it possible to provide high-quality customer support.

[0227] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0228] Step 1:

[0229] A user starts an application from a terminal and enters authentication information (user name and password). The terminal sends this authentication information to the server. The input is the username and password, and the output is the authentication information sent.

[0230] Step 2:

[0231] The server compares the received authentication information with a database. The operation involves running a database query to determine whether the user is valid. The input is the username and password, and the output is the authentication result. If authentication is successful, the server generates a session ID and notifies the terminal.

[0232] Step 3:

[0233] The terminal initializes the session using the session ID received from the server. This ensures that only authenticated users can use the chat interface. The input is the session ID, and the output is session initialization.

[0234] Step 4:

[0235] The user inputs a question or concern into the chat interface. The terminal sends this message to the server. The input is the user's message, and the output is the message sent.

[0236] Step 5:

[0237] The server uses a generative AI model to create a prompt sentence to generate a response based on the received user message. The inputs are the user message, user data, and past conversation logs, and the output is the generated prompt sentence. Specific operation involves generating an example prompt sentence: "User: 'I'd like to know more about this product'\nAI:".

[0238] Step 6:

[0239] The server uses a generative AI model to generate a response based on the prompt. The input is the prompt, and the output is the generated AI chatbot's response. The generated response is sent from the server to the device.

[0240] Step 7:

[0241] The terminal receives a response message from the server and displays it to the user. The input is the generated AI chatbot's response, and the output is the response displayed to the user. This allows the user to obtain an appropriate answer to their question or concern.

[0242] Step 8:

[0243] The server stores the conversation log between the chatbot and the user in real time for later analysis. The input is the content of the conversation, and the output is the saved conversation log. Operations include writing the conversation log to the database.

[0244] Step 9:

[0245] If necessary, the server can refer the user to an expert. The input is the user's problem and the analysis results, and the output is a referral suggestion to an expert. Specific actions can include providing the expert's contact information or inviting the user to chat directly.

[0246] 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.

[0247] This invention combines an online mental health support system using an AI chatbot that is available 24 hours a day with an emotion engine that recognizes the user's emotions. This system provides immediate and effective mental health support to users by linking the user, device, server, and emotion engine components.

[0248] Server Roles

[0249] The server plays a central role in the system. First, it receives authentication information sent by the user and verifies the user's identity by checking it against a database. If authentication is successful, it generates a session ID and sends it to the device to start the session. Next, the server generates an AI chatbot based on the user data. This AI chatbot sets an optimal dialogue scenario based on the user's past stress level and conversation logs. Furthermore, it uses an emotion engine to analyze emotions from the user's input messages and past dialogue logs, and dynamically adjusts the dialogue scenario based on the user's emotions. In addition, the server saves the conversation logs and emotion data between the user and the AI ​​chatbot in real time and manages them as data for later analysis.

[0250] Device Role

[0251] The terminal provides an interface that connects the user and the server. When the user launches the application, an authentication information input screen is displayed and the user enters their authentication information. The terminal sends that information to the server, and upon receiving a session ID from the server, initializes the session. Next, the terminal receives the chatbot data sent from the server and displays a user-friendly chat interface. When the user enters a message, the terminal sends that message to the server and waits for a response. After receiving the response message from the server, the terminal displays it to the user.

[0252] User operations

[0253] Users access the application using a smartphone or PC and log in by entering their authentication information. Once authentication is successful, the user is redirected to a chat interface where they can enter their stress and worries and receive a response from the AI ​​chatbot. An emotion engine analyzes the user's emotions, and the AI ​​chatbot provides optimal advice and solutions based on those emotions. If necessary, the user can be referred to an expert.

[0254] Specific examples

[0255] For example, consider a situation where a user types, "Work has been really hard lately." The user's message is sent from the device to the server, and the server uses an emotion engine to analyze the emotion from the user's message content. The emotion engine detects that the user is feeling stressed and identifies the emotion "hard." The AI ​​chatbot generates a response based on this emotion. The chatbot asks the user, "That must be really hard. What specifically is causing you hardship?" and provides specific advice through dialogue. If the user replies, "I'm feeling pressured because the project progress is not going well," the chatbot suggests, "Can I introduce you to some tools or support to help you manage the project progress?" This allows the user to find a specific solution.

[0256] This system allows users to receive effective mental health support in real time, 24 hours a day. By combining it with an emotion engine, it is possible to accurately grasp the user's emotions and provide more appropriate responses. This allows for immediate and effective support in the user's mental health care.

[0257] The processing flow will be explained below.

[0258] Server Processing Steps

[0259] Step 1:

[0260] Server receives authentication information (user ID and password) sent by the user.

[0261] Step 2:

[0262] The server queries the database for authentication information and checks whether the corresponding user exists.

[0263] Step 3:

[0264] If the user exists, the server generates a session ID and sends it to the terminal along with a response indicating successful authentication.

[0265] Step 4:

[0266] For users who are successfully authenticated, the server generates an AI chatbot based on the user data.

[0267] Step 5:

[0268] The server sets up the optimal dialogue scenario based on user data and applies it to the AI ​​chatbot.

[0269] Step 6:

[0270] The server runs an emotion engine to analyze emotions from user input messages and past dialogue logs.

[0271] Step 7:

[0272] Based on the emotional information analyzed by the emotion engine, the server dynamically adjusts the dialogue scenario.

[0273] Step 8:

[0274] The server generates responses for the AI ​​chatbot based on the adjusted dialogue scenario.

[0275] Step 9:

[0276] Conversation logs and emotional data between users and AI chatbots are saved in real time and managed as data for later analysis.

[0277] Terminal processing steps

[0278] Step 1:

[0279] The terminal displays a screen for the user to input authentication information.

[0280] Step 2:

[0281] When the user inputs the authentication information and presses the send button, the terminal sends the authentication information to the server.

[0282] Step 3:

[0283] When the server returns the session ID, the terminal initializes the session.

[0284] Step 4:

[0285] The terminal receives the chatbot data sent from the server and displays a user-friendly chat interface.

[0286] Step 5:

[0287] When the user enters a message, the terminal sends the message to the server and waits for a response.

[0288] Step 6:

[0289] The terminal that receives the response message from the server displays it to the user.

[0290] User operation steps

[0291] Step 1:

[0292] The user accesses the application using a smartphone or PC and enters authentication information (user ID and password).

[0293] Step 2:

[0294] The user presses the login button to request authentication from the server.

[0295] Step 3:

[0296] Upon successful authentication, the user is redirected to the chat interface.

[0297] Step 4:

[0298] Users input their stress and worries into a chat interface.

[0299] Step 5:

[0300] The user receives a response from the AI ​​chatbot and checks the advice and solutions displayed.

[0301] Step 6:

[0302] Users input detailed information in response to follow-up questions and suggestions from the AI ​​chatbot.

[0303] Step 7:

[0304] Accept expert referrals suggested by the AI ​​chatbot when needed.

[0305] Example 2

[0306] 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."

[0307] Conventional online mental health support systems have had difficulty accurately recognizing users' emotions and providing appropriate dialogue and advice based on those emotions. It has also been difficult to provide user support 24 hours a day. This has resulted in an inability to respond appropriately to users' emotions, limiting the effectiveness of mental health care.

[0308] 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.

[0309] In this invention, the server includes means for receiving user authentication information and verifying it based on a database, means for generating a session ID and notifying the user if the user authentication is successful, means for generating a dialogue agent based on user data and setting an optimal dialogue scenario, means for analyzing user input messages in real time using emotion analysis means and dynamically adjusting the dialogue scenario based on the emotions, and means for saving a conversation log between the dialogue agent and the user in real time so that it can be analyzed later. This makes it possible to accurately grasp the user's emotions and provide appropriate and timely dialogue and advice based on them.

[0310] "User authentication information" refers to the identification information (e.g., user ID and password) that a user enters to log in to a system.

[0311] A "database" is an information storage system for systematically storing and managing information such as user authentication information and past interaction logs.

[0312] A "session ID" is a unique identifier issued to a user who has been successfully authenticated and is used to track and manage the session.

[0313] A "conversational agent" is an artificial intelligence model created to converse with users, and has the ability to provide appropriate dialogue based on the user's past data and emotional analysis.

[0314] "Emotion analysis means" is a technology for extracting emotional information from a user's input message and generating appropriate dialogue scenarios and responses based on that information.

[0315] A "dialogue scenario" defines a series of topics and question sequences that a dialogue agent uses in conversation with a user, and is dynamically adjusted according to the user's situation and emotions.

[0316] A "conversation log" is a record of all interactions between a user and a conversational agent, which can be analyzed and referenced later.

[0317] This invention combines an online mental health support system using an AI chatbot that is available 24 hours a day with an emotion engine that recognizes the user's emotions. This system provides immediate and effective mental health support to users by linking the user, terminal, server, and emotion engine components. A detailed explanation of how to implement this system is provided below.

[0318] Server Roles

[0319] The server plays a central role in the system. First, it receives authentication information sent by the user and verifies the user's identity by checking it against a database. If authentication is successful, it generates a session ID and sends it to the terminal to start the session. Next, the server generates a dialogue agent based on the user data. This dialogue agent sets an optimal dialogue scenario based on the user's past stress level and conversation log. Furthermore, it uses emotion analysis means to analyze emotions from the user's input messages and past dialogue logs, and dynamically adjusts the dialogue scenario based on the user's emotions. In addition, the server saves the dialogue logs and emotion data of the user and dialogue agent in real time and manages them as data for later analysis.

[0320] Device Role

[0321] The terminal provides an interface that connects the user and the server. When the user launches an application, an authentication information entry screen appears and the user enters their authentication information. The terminal sends that information to the server, and upon receiving a session ID from the server, initializes the session. Next, the terminal receives the conversation agent data sent from the server and displays a user-friendly chat interface. When the user enters a message, the terminal sends that message to the server and waits for a response. After receiving the response message from the server, the terminal displays it to the user.

[0322] User operations

[0323] Users access the application using a smartphone or PC and log in by entering their authentication information. Once authentication is successful, the user is redirected to a chat interface, where they can enter their stress and worries and receive a response from a conversational agent. An emotion analysis means analyzes the user's emotions, and the conversational agent provides optimal advice and measures based on those emotions. If necessary, the user can be referred to an expert.

[0324] Hardware and software used

[0325] The hardware used will be a high-performance database and a server machine with processing power. Specifically, cloud service providers (e.g., AWS, Google Cloud Platform) can be used. Normal smartphones and PCs are expected to be used as devices. Software used will likely include emotion analysis technology for emotion analysis and a generative AI model (e.g., GPT-3) for the dialogue agent.

[0326] Examples of concrete examples and prompts

[0327] For example, consider a situation where a user types, "Work has been really hard lately." In this case, the user's message is sent from the terminal to the server, and the server uses emotion analysis means to analyze the emotion from the content of the user's message. The emotion analysis means detects that the user is feeling stressed and identifies the emotion "hard." The dialogue agent generates a response based on this emotion. The dialogue agent asks the user, "That must be really hard. What specifically is causing you to feel hard?" and provides specific advice through dialogue. If the user answers, "I'm feeling pressured because the project progress is not going well," the dialogue agent suggests, "Would you like me to introduce you to some tools or support to help you manage the project progress?" This allows the user to obtain a specific solution.

[0328] Below is an example of a prompt sentence to input to the generative AI model.

[0329] "You are a conversational agent. Your role is to understand the message entered by the user and provide an appropriate response based on the user's sentiment. Below is the user's message and the result of sentiment analysis:

[0330] User message: 'Work has been really hard lately'

[0331] Sentiment analysis: 'Stressful, painful'

[0332] Based on this, generate an appropriate response for the user."

[0333] This system allows users to receive effective mental health support in real time, 24 hours a day. By combining it with emotion analysis methods, it is possible to accurately grasp the user's emotions and provide more appropriate responses. This allows for immediate and effective support in the user's mental health care.

[0334] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0335] Step 1:

[0336] Authenticating Users

[0337] The user starts an application and enters authentication information (user ID and password). The entered authentication information is sent from the terminal to the server. The server receives the authentication information and checks it against a database to verify that it is a valid user. For example, if the authentication information "user name: john_doe, password: password123" is entered, the server checks it against the database. If authentication is successful, the server generates a session ID "abc123" and sends it to the terminal.

[0338] Input: User authentication information (user ID, password)

[0339] Output: Session ID

[0340] Specific operation: When the user enters authentication information and authentication is successful, the server generates a session ID and sends it to the terminal.

[0341] Step 2:

[0342] Initializing the session

[0343] The terminal starts a session using the session ID received from the server and displays a chat interface for the user. After receiving the session ID, the terminal displays the chat screen to the user, allowing the user to enter a message.

[0344] Input: Session ID

[0345] Output: Chat interface displayed

[0346] Specific actions: After receiving the session ID, the device will display the chat interface and allow the user to enter a message.

[0347] Step 3:

[0348] Generating a conversational agent

[0349] The server generates a dialogue agent based on user data. This dialogue agent sets up an optimal dialogue scenario based on the user's past stress level and conversation log. For example, a generative AI model can be used to create an optimal dialogue scenario based on the user profile.

[0350] Input: User data (past stress levels, conversation logs)

[0351] Output: A conversational agent

[0352] Specific operation: The server collects the user's past data and generates a dialogue agent using a generative AI model, while also setting the optimal dialogue scenario.

[0353] Step 4:

[0354] Receiving user messages

[0355] The user enters a message into the chat interface and presses the send button. The device then sends the message to the server. For example, the user enters "Work has been really hard lately," and the device sends this to the server.

[0356] Input: User message

[0357] Output: None (forwarding the message)

[0358] Specific operation: The terminal sends the message entered by the user to the server.

[0359] Step 5:

[0360] Emotion analysis

[0361] The server uses emotion analysis means to analyze the received user message and identify the emotion. For example, from the input message "Work has been really hard lately," the server identifies the emotion "stressed, hard."

[0362] Input: User message

[0363] Output: Emotional information

[0364] Specific operation: The server analyzes the input message and extracts emotional information.

[0365] Step 6:

[0366] Response Generation

[0367] Based on the results of emotion analysis, the dialogue agent generates an appropriate response. For example, if the user's emotion is "painful," the dialogue agent will generate a response such as, "That must be really hard. What specifically is causing you pain?"

[0368] Input: Emotion information, user data

[0369] Output: Response of the conversational agent

[0370] Specific operation: Based on the results of emotion analysis, the dialogue agent uses a generative AI model to generate an appropriate response.

[0371] Step 7:

[0372] Sending and Displaying Responses

[0373] The server then sends the generated response message to the terminal, which then displays it to the user. For example, the response generated by the conversational agent is "That's really hard. What specifically is causing you pain?", and the terminal displays it to the user.

[0374] Input: Response message from the conversation agent

[0375] Output: Display a message on the user's screen

[0376] Specific operation: The terminal receives the response message from the server and displays it to the user.

[0377] Step 8:

[0378] Save conversation logs

[0379] The server saves the conversation log between the user and the conversation agent and their emotional data in real time, and manages it as data for later analysis. For example, information such as "User message: Work has been really hard lately," "Emotion analysis: Stress, hard," and "Dialogue agent response: That's really hard. What specifically is causing you hardship?" is recorded in the database.

[0380] Input: Conversation logs and emotion data

[0381] Output: Saved data

[0382] Specific operation: The server stores conversation logs and emotion data in real time and manages them for later analysis.

[0383] (Application example 2)

[0384] 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."

[0385] As the importance of mental health care has increased in recent years, there is a growing need for systems that provide optimal mental health support and relaxation content according to the user's emotional state. Conventional mental health support systems have had the difficulty of analyzing a user's emotions in real time and individually recommending optimal content based on the results, making them unable to meet the diverse needs of users.

[0386] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user authentication information and verifying it based on a database, means for generating a session ID and notifying the user if user authentication is successful, means for generating an AI chatbot based on user data and setting an optimal dialogue scenario, means for saving a conversation log between the chatbot and the user in real time so that it can be analyzed later, and means for analyzing the user's emotional information and recommending optimal content based on the analysis results. This makes it possible to provide mental health support and relaxation content in real time that is tailored to the user's emotional state.

[0387] "User authentication information" is data used to identify a particular user and verify that the user is authorized to access a system.

[0388] A "database" is a system for efficiently storing, managing, and retrieving structured information.

[0389] A "session ID" is a unique identifier generated to identify a user's individual session.

[0390] An "AI chatbot" is a program that uses artificial intelligence to automate conversations with users.

[0391] A "dialogue scenario" is a plan that sets the flow and content of a dialogue with a user in advance.

[0392] A "conversation log" is data that records the interactions between a user and a chatbot.

[0393] "Emotion information" is data that expresses the user's emotional state.

[0394] "Emotion analysis" is the process of identifying a user's emotional state from words, facial expressions, etc.

[0395] "Content recommendation" is the act of suggesting optimal content based on a user's interests and emotional state.

[0396] An "input message" is text or voice data that a user sends to the system.

[0397] A "response message" is response data sent from a server or chatbot to a user.

[0398] A "viewing history" is a record of content that a user has viewed in the past.

[0399] "Analysis results" are the conclusions and findings obtained after conducting data analysis.

[0400] This invention is a 24-hour online mental health support system using an AI chatbot, combined with an emotion engine that recognizes and analyzes the user's emotions. This system is also capable of recommending optimal content in real time according to the user's emotional state. Below, we will explain how this system is implemented in detail.

[0401] Overall system structure

[0402] This system consists of a device used by the user, a central processing server, and an emotion engine that analyzes emotions. The device can be a smartphone, PC, tablet, etc., and is responsible for interacting with the user. The server processes data, generates AI chatbots, and sets up dialogue scenarios. The emotion engine then analyzes emotions from user input and provides optimal responses and content recommendations.

[0403] Program processing explanation

[0404] Authenticating a User and Starting a Session

[0405] 1. Device: The user accesses the application using a smartphone or PC and enters authentication information (user ID and password).

[0406] 2. Server: Receives the authentication information sent from the device and checks the database to verify the user's authenticity. If authentication is successful, generates a session ID and sends it to the device.

[0407] Creating an AI chatbot and setting up dialogue scenarios

[0408] 1. Server: Generates an AI chatbot based on user data and sets up optimal conversation scenarios. Individual scenarios are constructed taking into account data such as past conversation logs and stress levels.

[0409] Message sending and receiving and sentiment analysis

[0410] 1. Terminal: Receives input messages from the user and sends them to the server. For example, the user might input a message such as "Work has been really hard lately."

[0411] 2. Server: Passes the received message to the emotion engine for analysis. The emotion engine analyzes the user's emotion from the input message and identifies the emotional state, such as "stress" or "sadness."

[0412] Recommending content and continuing the conversation

[0413] 1. Server: Based on the sentiment analysis, the recommendation engine selects the most suitable content, such as relaxing music or a guided meditation video.

[0414] 2. Terminal: Displays the content recommendation list sent from the server to the user and plays the content selected by the user.

[0415] Examples of concrete examples and prompts

[0416] Specific examples

[0417] If the user types "Work has been really hard lately," the system will do the following:

[0418] 1. The user's message is sent from the device to the server.

[0419] 2. The server uses the emotion engine to identify the user's emotional state as "stress."

[0420] 3. Based on the results of the emotion analysis, the AI ​​chatbot asks, "That must be really tough. What specifically is causing you distress?"

[0421] 4. At the same time, it also recommends music playlists that have a relaxing effect.

[0422] Prompt Sentence Examples

[0423] The prompt to analyze the sentiment of the input "tired" is as follows:

[0424] User Input: I'm tired

[0425] Emotional state: stress, fatigue

[0426] Recommended content: Relaxation music, meditation videos

[0427] In this way, mental health support and content recommendations can be provided that are tailored to the user's emotional state, enhancing the user's experience.

[0428] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0429] Step 1:

[0430] A user accesses an application using a smartphone or PC and enters authentication information (user ID and password). The authentication information is obtained as input data. This authentication information is then sent from the device to the server.

[0431] Step 2:

[0432] The server compares the authentication information received from the terminal with a database to confirm whether the user is a legitimate user. The data processing performed here is to compare the authentication information, and the output is the result of authentication success or failure. If authentication is successful, the server generates a session ID and sends it to the terminal.

[0433] Step 3:

[0434] If the user is successfully authenticated, the terminal initializes the session using the session ID received from the server, allowing the user to log in to the system and prepare for the next operation.

[0435] Step 4:

[0436] The user inputs a message related to stress or emotion and sends it from the terminal to the server. The input data here is the user's message, and the output is the data sent to the server.

[0437] Step 5:

[0438] The server passes the user's input message to the emotion engine for emotion analysis. The emotion engine uses a generative AI model to analyze the emotional state (e.g., stress, fatigue) from the input message. The input is the user's message, and the output is the analyzed emotion data.

[0439] Step 6:

[0440] The server sets the optimal dialogue scenario based on the analysis results of the emotion engine and generates an AI chatbot. Here, data processing is performed to set the dialogue scenario using emotion data, and the optimized dialogue scenario is obtained as the output.

[0441] Step 7:

[0442] The server generates content recommendation results according to the user's emotional state. Specifically, the recommendation engine uses the emotion analysis results as prompts to suggest appropriate content (music, videos, guided meditations, etc.). The input is the emotion analysis results, and the output is a list of recommended content.

[0443] Step 8:

[0444] The terminal displays the content recommendation results received from the server to the user and plays the content selected by the user. Here, the content recommendation results are obtained as input, and the output is content information displayed to the user. The user can select content and start playing it.

[0445] Step 9:

[0446] The server stores the conversation log between the chatbot and the user, as well as the user's viewing history, in real time. It then performs big data analysis and manages the data to provide more accurate support in the future. The input is the conversation log and viewing history, and the output is an analyzable database entry.

[0447] 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.

[0448] 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.

[0449] 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.

[0450] [Second embodiment]

[0451] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0452] 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.

[0453] 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).

[0454] 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.

[0455] 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.

[0456] 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).

[0457] 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.

[0458] 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.

[0459] 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.

[0460] 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.

[0461] 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.

[0462] 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."

[0463] This invention provides a 24-hour online mental health support system using an AI chatbot. This system provides immediate and effective mental health support to users by linking the user, terminal, and server components.

[0464] Server Roles

[0465] The server plays a central role in this system. First, it receives the authentication information sent by the user from the device and checks it against a database. If the user is authenticated, the server generates a session ID and sends it to the device to start the session. Next, the server generates an AI chatbot based on the user data. This AI chatbot sets up an optimal dialogue scenario based on the user's past stress level and conversation log. Furthermore, the server saves the conversation log between the user and the AI ​​chatbot in real time and manages it as data for later analysis.

[0466] Device Role

[0467] The terminal provides an interface that connects the user and the server. When the user launches the application, an authentication information input screen is displayed. The user enters the authentication information, and the terminal sends it to the server. When a session ID is returned from the server, the terminal initializes the session and displays a chat interface to the user. When the user enters a message, the terminal sends it to the server, receives a response message from the server, and displays it to the user.

[0468] User operations

[0469] To use this system, users first access the application from their device. After entering their authentication information on the login screen and pressing the login button, the server performs authentication. If authentication is successful, the user is redirected to a chat interface. Here, the user enters their stress and worries and receives appropriate advice from an AI chatbot. If necessary, the user can also be referred to a specialist.

[0470] Specific examples

[0471] For example, imagine a situation where a user is feeling very stressed at work. The user opens an application and types, "I'm stressed at work." This message is sent to the server via the device, and the server generates a response using an AI chatbot. The AI ​​chatbot asks, "What specifically is causing you stress?" and suggests next steps based on the user's response. If the user answers, "A particular project is putting a lot of pressure on me," the AI ​​chatbot might suggest, "Would you like me to provide you with specific support or resources to help with the progress of this project?"

[0472] This entire conversation takes place in real time, and the server stores the conversation log, allowing for continuous tracking of the user's mental health status. If necessary, the system can smoothly refer the user to a specialist.

[0473] As described above, the present invention provides immediate and effective support for the user's mental health care.

[0474] The processing flow will be explained below.

[0475] Program processing flow

[0476] Server Processing Steps

[0477] Step 1:

[0478] Server receives authentication information (user ID and password) sent by the user.

[0479] Step 2:

[0480] The server queries the database for authentication information and checks whether the corresponding user exists.

[0481] Step 3:

[0482] If the user exists, the server generates a session ID and sends it to the terminal along with a response indicating successful authentication.

[0483] Step 4:

[0484] For users who are successfully authenticated, the server generates an AI chatbot based on the user data.

[0485] Step 5:

[0486] The server sets up the optimal dialogue scenario based on user data and applies it to the AI ​​chatbot.

[0487] Step 6:

[0488] Conversation logs between users and AI chatbots are saved in real time and managed as data for later analysis.

[0489] Terminal processing steps

[0490] Step 1:

[0491] The terminal displays a screen for the user to input authentication information.

[0492] Step 2:

[0493] When the user inputs the authentication information and presses the send button, the terminal sends the authentication information to the server.

[0494] Step 3:

[0495] When the server returns the session ID, the terminal initializes the session.

[0496] Step 4:

[0497] The terminal receives the chatbot data sent from the server and displays a user-friendly chat interface.

[0498] Step 5:

[0499] When the user enters a message, the terminal sends the message to the server and waits for a response.

[0500] Step 6:

[0501] The terminal that receives the response message from the server displays it to the user.

[0502] User operation steps

[0503] Step 1:

[0504] The user starts the application and enters authentication information (user ID and password).

[0505] Step 2:

[0506] The user presses the login button to request authentication from the server.

[0507] Step 3:

[0508] Upon successful authentication, the user is redirected to the chat interface.

[0509] Step 4:

[0510] Users input their stress and worries into a chat interface.

[0511] Step 5:

[0512] The user receives a response from the AI ​​chatbot and checks the advice and solutions displayed.

[0513] Step 6:

[0514] Accept expert referrals suggested by the AI ​​chatbot when needed.

[0515] This series of steps allows users to receive immediate mental health support 24 hours a day.

[0516] Example 1

[0517] 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."

[0518] Mental health care is becoming an increasingly important issue in modern society. However, it is difficult to provide professional mental health support available 24 hours a day. There is a need for a system that can comprehensively manage a wide range of elements, such as user authentication, data management, and the provision of appropriate support, and provide immediate and effective support. Furthermore, when referral to a specialist is necessary, a system is also needed to ensure smooth referrals.

[0519] 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.

[0520] In this invention, the server includes means for receiving user authentication information and verifying it based on a database, means for generating a session ID and notifying the user if the user authentication is successful, means for generating a conversational bot using a generative AI model based on user data and setting an optimal conversation scenario, means for saving a conversation log between the conversational bot and the user in real time so that it can be analyzed later, and means for analyzing the conversation log and suggesting a referral to a specialist if necessary. This realizes online mental health support available 24 hours a day, allowing users to receive immediate and effective mental health care.

[0521] "Authentication Information" means the username, password, or other means of authentication used by a User to access a System.

[0522] "Database" refers to a system that stores user authentication information and past data and performs verification and reference as needed.

[0523] "Session ID" refers to an identifier that is generated by the server after a user has been successfully authenticated and that uniquely identifies the user's session.

[0524] A "generative AI model" refers to an artificial intelligence model that generates appropriate dialogue scenarios based on user data.

[0525] A "conversational bot" refers to a chatbot built on a generative AI model to engage in dialogue with users.

[0526] A "dialogue scenario" refers to a series of appropriate dialogue content presented by a generative AI model in a dialogue with a user.

[0527] A "conversation log" refers to the history of messages exchanged between a conversational bot and a user.

[0528] "Professional referral" refers to the process of referring a user to a professional mental health care provider, if necessary.

[0529] "Real-time" refers to the system's ability to interact with and process users instantly.

[0530] This invention provides a 24-hour online mental health support system using an AI chatbot. This system provides immediate and effective mental health support to users by linking the user, terminal, and server components.

[0531] Server Roles

[0532] The server plays a central role in this system. First, it receives the authentication information sent by the user from the device and checks it against a database. Databases such as MySQL or PostgreSQL are typically used. Once the user is authenticated, the server generates a session ID and sends it to the device to start the session. The session ID is usually generated as a UUID (Universally Unique Identifier). The server then generates a conversational bot based on the user data using a generative AI model. OpenAI's GPT-4 is one example of a generative AI model. This conversational bot sets an optimal conversation scenario based on the user's past stress level and conversation log. Furthermore, the server saves the conversation log between the user and the conversational bot in real time and manages it as data for later analysis. Storage services such as Amazon S3 and Google Cloud Storage can be used.

[0533] Device Role

[0534] The terminal provides an interface that connects the user and the server. When the user starts the application, an authentication information input screen is displayed. The user enters their username and password here. Once the input is complete, the terminal sends it to the server. When the server returns a session ID, the terminal initializes the session and displays a chat interface to the user. When the user enters a message, the terminal sends it to the server, receives a response message from the server in real time, and displays it to the user.

[0535] User operations

[0536] To use this system, users first access the application from their device. After entering their authentication information on the login screen and pressing the login button, the server performs authentication. If authentication is successful, the user is redirected to a chat interface. Here, the user inputs their stress and worries and receives appropriate advice from a conversational bot using a generative AI model. If necessary, the user can also be referred to an expert.

[0537] Specific examples

[0538] For example, a user might type, "I'm feeling stressed at work." The device then sends this message to the server. The server uses a generative AI model to generate a response, asking, "What specifically is causing you stress?" If the user types, "A particular project is putting a lot of pressure on me," the conversational bot might suggest, "Would you like us to provide you with specific support or resources to help with the progress of this project?" This entire conversation takes place in real time, and the server stores the conversation log, continuously tracking the user's mental health status. If necessary, the server can smoothly refer the user to a specialist.

[0539] Prompt Sentence Examples

[0540] "I'm stressed about a particular work issue. What specifically is causing it? And what specific solutions do you suggest for that issue?"

[0541] As described above, the present invention provides immediate and effective support for the user's mental health care.

[0542] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0543] Step 1:

[0544] The user launches the application and enters their authentication information (username and password).

[0545] Input: Username and Password

[0546] How it works: A user accesses a login screen on their device and enters their credentials.

[0547] Output: The entered credentials

[0548] Step 2:

[0549] The terminal sends the user's authentication information to the server.

[0550] Input: Authentication information (username and password)

[0551] How it works: The device sends authentication information to the server using an HTTP POST request.

[0552] Output: Authentication information sent to the server

[0553] Step 3:

[0554] The server checks the credentials against a database and authenticates the user.

[0555] Input: Credentials

[0556] What happens: The server queries a database (e.g. MySQL, PostgreSQL) and matches the credentials. If successful, the user is authenticated.

[0557] Output: User authentication result (success or failure)

[0558] Step 4:

[0559] When authentication is successful, the server generates a session ID and notifies the terminal.

[0560] Input: Authentication result (success)

[0561] How it works: If authentication is successful, the server generates a session ID as a unique UUID and sends it to the device.

[0562] Output: Session ID

[0563] Step 5:

[0564] The terminal receives the session ID and initializes the session.

[0565] Input: Session ID

[0566] Behavior: The terminal uses the received session ID to initialize the session and displays a login success screen to the user.

[0567] Output: Session initialized

[0568] Step 6:

[0569] The server obtains the user's past data (stress level, conversation log) and generates a conversational bot using a generative AI model.

[0570] Input: Session ID, User Data

[0571] How it works: The server retrieves the user's past data from the database and sets the parameters of a generative AI model (e.g., GPT-4) to generate a conversational bot.

[0572] Output: The generated conversational bot

[0573] Step 7:

[0574] The server generates an initial message for the conversational bot and sends it to the terminal.

[0575] Input: Generated conversational bot, user data

[0576] How it works: The server launches the conversational bot, generates an initial question or message, and sends it to the user.

[0577] Output: Initial message

[0578] Step 8:

[0579] The device receives the initial message and displays it in the chat interface.

[0580] Input: initial message

[0581] Behavior: The terminal displays the initial message it receives in the chat interface.

[0582] Output: Initial message displayed

[0583] Step 9:

[0584] The user inputs their stress and worries into a chat interface.

[0585] Input: Details of stress and worries

[0586] How it works: The user enters their stress and worries and presses the send button.

[0587] Output: The input message

[0588] Step 10:

[0589] The terminal sends the user's message to the server.

[0590] Input: The message entered

[0591] Operation: The terminal sends the user's message to the server.

[0592] Output: Message sent to the server

[0593] Step 11:

[0594] The server generates a response message using a generative AI model based on the user's message.

[0595] Input: User message, generative AI model

[0596] How it works: The server parses the user's message and uses a generative AI model to generate an appropriate response message.

[0597] Output: Response message

[0598] Step 12:

[0599] The server sends a response message to the terminal.

[0600] Input: Response message

[0601] Operation: The server sends the generated response message to the terminal.

[0602] Output: Response message sent to the terminal

[0603] Step 13:

[0604] The terminal receives the response message and displays it to the user.

[0605] Input: Response message

[0606] Behavior: The device displays the received reply message in the chat interface.

[0607] Output: The displayed response message

[0608] Step 14:

[0609] The server stores the conversation log between the user and the conversational bot in real time.

[0610] Input: User's message, reply message

[0611] How it works: The server stores all messages between users and conversational bots in a database.

[0612] Output: Saved conversation logs

[0613] Step 15:

[0614] The server analyzes the conversation log and suggests referrals to experts if necessary.

[0615] Input: conversation log

[0616] How it works: The server analyzes the saved conversation logs and, if it determines that a referral to an expert is necessary, makes such a suggestion to the user.

[0617] Output: Referral message if necessary

[0618] The above is the flow of processing of the program of this system.

[0619] (Application example 1)

[0620] 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."

[0621] Conventional mental health care systems often delay providing appropriate support for users' stress and worries. Furthermore, in brick-and-mortar stores, it can be difficult for staff to constantly respond to customers, which can lead to a decline in customer satisfaction. To solve these problems, a fast and effective customer support system is needed, but current technology does not provide a sufficient solution.

[0622] 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.

[0623] In this invention, the server includes means for receiving user authentication information and verifying it based on a database, means for generating a session ID and notifying the user if the user authentication is successful, means for generating an AI chatbot using a generative AI model based on user data and setting an optimal dialogue scenario, means for saving a conversation log between the chatbot and the user in real time for later analysis, and means for the generated dialogue scenario to include responses generated based on prompt sentences intended for customer support in a physical store. This enables effective mental health care for users and prompt and appropriate customer support in a physical store.

[0624] "Authentication information" refers to information used by a user when logging in to a system, such as a user name and password.

[0625] A "database" is a system for organizing and managing a wide variety of data, and is a place where user authentication information, conversation logs, etc. are stored.

[0626] "Session ID" means a unique identifier generated after successful user authentication to identify an interactive session between a particular user and a system.

[0627] A "generative AI model" is an algorithm that uses artificial intelligence techniques to design a conversational interface based on user data.

[0628] An "AI chatbot" is a program that uses artificial intelligence to automatically generate responses to users' questions and inquiries.

[0629] A "dialogue scenario" refers to a series of scenes and responses that define the flow and content when an AI chatbot converses with a user.

[0630] A "conversation log" is data that records the content of the conversation between a user and an AI chatbot, and is saved in a format that can be analyzed later.

[0631] A "prompt" is a piece of text or phrase that serves as a starting point for a generative AI model to generate a specific response.

[0632] A "brick and mortar store" refers to a retail or service establishment that has a physical presence in a physical location where face-to-face commerce with customers takes place.

[0633] "Customer support" refers to the activity of providing assistance to customers to respond to and resolve questions or problems that arise when using a product or service.

[0634] "Referral to an expert" refers to connecting the user to a person or department with specialized knowledge if the AI ​​chatbot determines this is necessary through dialogue.

[0635] This invention relates to an AI chatbot system for customer support in brick-and-mortar stores. This system involves user, terminal, and server components interacting with each other to provide instant and effective question responses and support to users.

[0636] Server Roles

[0637] The server plays a central role in this system. Its functions are realized by the following procedure.

[0638] 1. Receiving and verifying authentication information

[0639] The server receives the authentication information sent by the user from the terminal and compares it with the database. If the authentication is successful, the server generates a session ID and notifies the user terminal.

[0640] 2. Use of generative AI models

[0641] The AI ​​chatbot is generated using a generative AI model based on user data and the optimal dialogue scenario is set up. Specifically, prompts are prepared based on the user's past inquiry history and stress level, and the chatbot's responses are generated.

[0642] 3. Save conversation logs

[0643] The conversation log between the chatbot and the user is saved in real time and can be analyzed later. This allows us to understand user behavior patterns and problems, leading to further improvements to the service.

[0644] Hardware used: Server

[0645] Software used: Generative AI models, database management system

[0646] Device Role

[0647] The terminal provides an interface between the user and the server.

[0648] 1. Enter and submit authentication information

[0649] When a user launches an application, a screen for entering authentication information appears. The user enters the authentication information, and the device sends it to the server.

[0650] 2. Displaying the chat interface

[0651] Once the server returns a session ID, the terminal initializes the session and displays a chat interface to the user. When the user enters a message, the terminal sends it to the server, receives a response message from the server, and displays it to the user.

[0652] Hardware used: smartphone, tablet

[0653] Software used: Front-end application (e.g., Flutter, React Native)

[0654] User operations

[0655] To use this system, a user first accesses the application from their device and enters their authentication information on the login screen. After successful authentication, the user is redirected to a chat interface. Here, the user enters their question or concern and receives appropriate advice or a response from the AI ​​chatbot. For example, if a user enters "I'd like to know more about this product," this message is sent to the server via the device, and the server uses a generative AI model to generate a response. An example of a prompt for the generated response is "User: "I'd like to know more about this product"\nAI:". Based on this prompt, the AI ​​chatbot returns a detailed answer such as: "Of course. This product is made of high-quality materials and has the following features..."

[0656] This entire dialogue is conducted in real time, and the server stores the conversation log, allowing for continuous tracking of the user's behavior and needs. If necessary, the user can be smoothly referred to an expert. This improves the customer experience in physical stores and makes it possible to provide high-quality customer support.

[0657] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0658] Step 1:

[0659] A user starts an application from a terminal and enters authentication information (user name and password). The terminal sends this authentication information to the server. The input is the username and password, and the output is the authentication information sent.

[0660] Step 2:

[0661] The server compares the received authentication information with a database. The operation involves running a database query to determine whether the user is valid. The input is the username and password, and the output is the authentication result. If authentication is successful, the server generates a session ID and notifies the terminal.

[0662] Step 3:

[0663] The terminal initializes the session using the session ID received from the server. This ensures that only authenticated users can use the chat interface. The input is the session ID, and the output is session initialization.

[0664] Step 4:

[0665] The user inputs a question or concern into the chat interface. The terminal sends this message to the server. The input is the user's message, and the output is the message sent.

[0666] Step 5:

[0667] The server uses a generative AI model to create a prompt sentence to generate a response based on the received user message. The inputs are the user message, user data, and past conversation logs, and the output is the generated prompt sentence. Specific operation involves generating an example prompt sentence: "User: 'I'd like to know more about this product'\nAI:".

[0668] Step 6:

[0669] The server uses a generative AI model to generate a response based on the prompt. The input is the prompt, and the output is the generated AI chatbot's response. The generated response is sent from the server to the device.

[0670] Step 7:

[0671] The terminal receives a response message from the server and displays it to the user. The input is the generated AI chatbot's response, and the output is the response displayed to the user. This allows the user to obtain an appropriate answer to their question or concern.

[0672] Step 8:

[0673] The server stores the conversation log between the chatbot and the user in real time for later analysis. The input is the content of the conversation, and the output is the saved conversation log. Operations include writing the conversation log to the database.

[0674] Step 9:

[0675] If necessary, the server can refer the user to an expert. The input is the user's problem and the analysis results, and the output is a referral suggestion to an expert. Specific actions can include providing the expert's contact information or inviting the user to chat directly.

[0676] 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.

[0677] This invention combines an online mental health support system using an AI chatbot that is available 24 hours a day with an emotion engine that recognizes the user's emotions. This system provides immediate and effective mental health support to users by linking the user, device, server, and emotion engine components.

[0678] Server Roles

[0679] The server plays a central role in the system. First, it receives authentication information sent by the user and verifies the user's identity by checking it against a database. If authentication is successful, it generates a session ID and sends it to the device to start the session. Next, the server generates an AI chatbot based on the user data. This AI chatbot sets an optimal dialogue scenario based on the user's past stress level and conversation logs. Furthermore, it uses an emotion engine to analyze emotions from the user's input messages and past dialogue logs, and dynamically adjusts the dialogue scenario based on the user's emotions. In addition, the server saves the conversation logs and emotion data between the user and the AI ​​chatbot in real time and manages them as data for later analysis.

[0680] Device Role

[0681] The terminal provides an interface that connects the user and the server. When the user launches the application, an authentication information input screen is displayed and the user enters their authentication information. The terminal sends that information to the server, and upon receiving a session ID from the server, initializes the session. Next, the terminal receives the chatbot data sent from the server and displays a user-friendly chat interface. When the user enters a message, the terminal sends that message to the server and waits for a response. After receiving the response message from the server, the terminal displays it to the user.

[0682] User operations

[0683] Users access the application using a smartphone or PC and log in by entering their authentication information. Once authentication is successful, the user is redirected to a chat interface where they can enter their stress and worries and receive a response from the AI ​​chatbot. An emotion engine analyzes the user's emotions, and the AI ​​chatbot provides optimal advice and solutions based on those emotions. If necessary, the user can be referred to an expert.

[0684] Specific examples

[0685] For example, consider a situation where a user types, "Work has been really hard lately." The user's message is sent from the device to the server, and the server uses an emotion engine to analyze the emotion from the user's message content. The emotion engine detects that the user is feeling stressed and identifies the emotion "hard." The AI ​​chatbot generates a response based on this emotion. The chatbot asks the user, "That must be really hard. What specifically is causing you hardship?" and provides specific advice through dialogue. If the user replies, "I'm feeling pressured because the project progress is not going well," the chatbot suggests, "Can I introduce you to some tools or support to help you manage the project progress?" This allows the user to find a specific solution.

[0686] This system allows users to receive effective mental health support in real time, 24 hours a day. By combining it with an emotion engine, it is possible to accurately grasp the user's emotions and provide more appropriate responses. This allows for immediate and effective support in the user's mental health care.

[0687] The processing flow will be explained below.

[0688] Server Processing Steps

[0689] Step 1:

[0690] Server receives authentication information (user ID and password) sent by the user.

[0691] Step 2:

[0692] The server queries the database for authentication information and checks whether the corresponding user exists.

[0693] Step 3:

[0694] If the user exists, the server generates a session ID and sends it to the terminal along with a response indicating successful authentication.

[0695] Step 4:

[0696] For users who are successfully authenticated, the server generates an AI chatbot based on the user data.

[0697] Step 5:

[0698] The server sets up the optimal dialogue scenario based on user data and applies it to the AI ​​chatbot.

[0699] Step 6:

[0700] The server runs an emotion engine to analyze emotions from user input messages and past dialogue logs.

[0701] Step 7:

[0702] Based on the emotional information analyzed by the emotion engine, the server dynamically adjusts the dialogue scenario.

[0703] Step 8:

[0704] The server generates responses for the AI ​​chatbot based on the adjusted dialogue scenario.

[0705] Step 9:

[0706] Conversation logs and emotional data between users and AI chatbots are saved in real time and managed as data for later analysis.

[0707] Terminal processing steps

[0708] Step 1:

[0709] The terminal displays a screen for the user to input authentication information.

[0710] Step 2:

[0711] When the user inputs the authentication information and presses the send button, the terminal sends the authentication information to the server.

[0712] Step 3:

[0713] When the server returns the session ID, the terminal initializes the session.

[0714] Step 4:

[0715] The terminal receives the chatbot data sent from the server and displays a user-friendly chat interface.

[0716] Step 5:

[0717] When the user enters a message, the terminal sends the message to the server and waits for a response.

[0718] Step 6:

[0719] The terminal that receives the response message from the server displays it to the user.

[0720] User operation steps

[0721] Step 1:

[0722] The user accesses the application using a smartphone or PC and enters authentication information (user ID and password).

[0723] Step 2:

[0724] The user presses the login button to request authentication from the server.

[0725] Step 3:

[0726] Upon successful authentication, the user is redirected to the chat interface.

[0727] Step 4:

[0728] Users input their stress and worries into a chat interface.

[0729] Step 5:

[0730] The user receives a response from the AI ​​chatbot and checks the advice and solutions displayed.

[0731] Step 6:

[0732] Users input detailed information in response to follow-up questions and suggestions from the AI ​​chatbot.

[0733] Step 7:

[0734] Accept expert referrals suggested by the AI ​​chatbot when needed.

[0735] Example 2

[0736] 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."

[0737] Conventional online mental health support systems have had difficulty accurately recognizing users' emotions and providing appropriate dialogue and advice based on those emotions. It has also been difficult to provide user support 24 hours a day. This has resulted in an inability to respond appropriately to users' emotions, limiting the effectiveness of mental health care.

[0738] 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.

[0739] In this invention, the server includes means for receiving user authentication information and verifying it based on a database, means for generating a session ID and notifying the user if the user authentication is successful, means for generating a dialogue agent based on user data and setting an optimal dialogue scenario, means for analyzing user input messages in real time using emotion analysis means and dynamically adjusting the dialogue scenario based on the emotions, and means for saving a conversation log between the dialogue agent and the user in real time so that it can be analyzed later. This makes it possible to accurately grasp the user's emotions and provide appropriate and timely dialogue and advice based on them.

[0740] "User authentication information" refers to the identification information (e.g., user ID and password) that a user enters to log in to a system.

[0741] A "database" is an information storage system for systematically storing and managing information such as user authentication information and past interaction logs.

[0742] A "session ID" is a unique identifier issued to a user who has been successfully authenticated and is used to track and manage the session.

[0743] A "conversational agent" is an artificial intelligence model created to converse with users, and has the ability to provide appropriate dialogue based on the user's past data and emotional analysis.

[0744] "Emotion analysis means" is a technology for extracting emotional information from a user's input message and generating appropriate dialogue scenarios and responses based on that information.

[0745] A "dialogue scenario" defines a series of topics and question sequences that a dialogue agent uses in conversation with a user, and is dynamically adjusted according to the user's situation and emotions.

[0746] A "conversation log" is a record of all interactions between a user and a conversational agent, which can be analyzed and referenced later.

[0747] This invention combines an online mental health support system using an AI chatbot that is available 24 hours a day with an emotion engine that recognizes the user's emotions. This system provides immediate and effective mental health support to users by linking the user, terminal, server, and emotion engine components. A detailed explanation of how to implement this system is provided below.

[0748] Server Roles

[0749] The server plays a central role in the system. First, it receives authentication information sent by the user and verifies the user's identity by checking it against a database. If authentication is successful, it generates a session ID and sends it to the terminal to start the session. Next, the server generates a dialogue agent based on the user data. This dialogue agent sets an optimal dialogue scenario based on the user's past stress level and conversation log. Furthermore, it uses emotion analysis means to analyze emotions from the user's input messages and past dialogue logs, and dynamically adjusts the dialogue scenario based on the user's emotions. In addition, the server saves the dialogue logs and emotion data of the user and dialogue agent in real time and manages them as data for later analysis.

[0750] Device Role

[0751] The terminal provides an interface that connects the user and the server. When the user launches an application, an authentication information entry screen appears and the user enters their authentication information. The terminal sends that information to the server, and upon receiving a session ID from the server, initializes the session. Next, the terminal receives the conversation agent data sent from the server and displays a user-friendly chat interface. When the user enters a message, the terminal sends that message to the server and waits for a response. After receiving the response message from the server, the terminal displays it to the user.

[0752] User operations

[0753] Users access the application using a smartphone or PC and log in by entering their authentication information. Once authentication is successful, the user is redirected to a chat interface, where they can enter their stress and worries and receive a response from a conversational agent. An emotion analysis means analyzes the user's emotions, and the conversational agent provides optimal advice and measures based on those emotions. If necessary, the user can be referred to an expert.

[0754] Hardware and software used

[0755] The hardware used will be a high-performance database and a server machine with processing power. Specifically, cloud service providers (e.g., AWS, Google Cloud Platform) can be used. Normal smartphones and PCs are expected to be used as devices. Software used will likely include emotion analysis technology for emotion analysis and a generative AI model (e.g., GPT-3) for the dialogue agent.

[0756] Examples of concrete examples and prompts

[0757] For example, consider a situation where a user types, "Work has been really hard lately." In this case, the user's message is sent from the terminal to the server, and the server uses emotion analysis means to analyze the emotion from the content of the user's message. The emotion analysis means detects that the user is feeling stressed and identifies the emotion "hard." The dialogue agent generates a response based on this emotion. The dialogue agent asks the user, "That must be really hard. What specifically is causing you to feel hard?" and provides specific advice through dialogue. If the user answers, "I'm feeling pressured because the project progress is not going well," the dialogue agent suggests, "Would you like me to introduce you to some tools or support to help you manage the project progress?" This allows the user to obtain a specific solution.

[0758] Below is an example of a prompt sentence to input to the generative AI model.

[0759] "You are a conversational agent. Your role is to understand the message entered by the user and provide an appropriate response based on the user's sentiment. Below is the user's message and the result of sentiment analysis:

[0760] User message: 'Work has been really hard lately'

[0761] Sentiment analysis: 'Stressful, painful'

[0762] Based on this, generate an appropriate response for the user."

[0763] This system allows users to receive effective mental health support in real time, 24 hours a day. By combining it with emotion analysis methods, it is possible to accurately grasp the user's emotions and provide more appropriate responses. This allows for immediate and effective support in the user's mental health care.

[0764] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0765] Step 1:

[0766] Authenticating Users

[0767] The user starts an application and enters authentication information (user ID and password). The entered authentication information is sent from the terminal to the server. The server receives the authentication information and checks it against a database to verify that it is a valid user. For example, if the authentication information "user name: john_doe, password: password123" is entered, the server checks it against the database. If authentication is successful, the server generates a session ID "abc123" and sends it to the terminal.

[0768] Input: User authentication information (user ID, password)

[0769] Output: Session ID

[0770] Specific operation: When the user enters authentication information and authentication is successful, the server generates a session ID and sends it to the terminal.

[0771] Step 2:

[0772] Initializing the session

[0773] The terminal starts a session using the session ID received from the server and displays a chat interface for the user. After receiving the session ID, the terminal displays the chat screen to the user, allowing the user to enter a message.

[0774] Input: Session ID

[0775] Output: Chat interface displayed

[0776] Specific actions: After receiving the session ID, the device will display the chat interface and allow the user to enter a message.

[0777] Step 3:

[0778] Generating a conversational agent

[0779] The server generates a dialogue agent based on user data. This dialogue agent sets up an optimal dialogue scenario based on the user's past stress level and conversation log. For example, a generative AI model can be used to create an optimal dialogue scenario based on the user profile.

[0780] Input: User data (past stress levels, conversation logs)

[0781] Output: A conversational agent

[0782] Specific operation: The server collects the user's past data and generates a dialogue agent using a generative AI model, while also setting the optimal dialogue scenario.

[0783] Step 4:

[0784] Receiving user messages

[0785] The user enters a message into the chat interface and presses the send button. The device then sends the message to the server. For example, the user enters "Work has been really hard lately," and the device sends this to the server.

[0786] Input: User message

[0787] Output: None (forwarding the message)

[0788] Specific operation: The terminal sends the message entered by the user to the server.

[0789] Step 5:

[0790] Emotion analysis

[0791] The server uses emotion analysis means to analyze the received user message and identify the emotion. For example, from the input message "Work has been really hard lately," the server identifies the emotion "stressed, hard."

[0792] Input: User message

[0793] Output: Emotional information

[0794] Specific operation: The server analyzes the input message and extracts emotional information.

[0795] Step 6:

[0796] Response Generation

[0797] Based on the results of emotion analysis, the dialogue agent generates an appropriate response. For example, if the user's emotion is "painful," the dialogue agent will generate a response such as, "That must be really hard. What specifically is causing you pain?"

[0798] Input: Emotion information, user data

[0799] Output: Response of the conversational agent

[0800] Specific operation: Based on the results of emotion analysis, the dialogue agent uses a generative AI model to generate an appropriate response.

[0801] Step 7:

[0802] Sending and Displaying Responses

[0803] The server then sends the generated response message to the terminal, which then displays it to the user. For example, the response generated by the conversational agent is "That's really hard. What specifically is causing you pain?", and the terminal displays it to the user.

[0804] Input: Response message from the conversation agent

[0805] Output: Display a message on the user's screen

[0806] Specific operation: The terminal receives the response message from the server and displays it to the user.

[0807] Step 8:

[0808] Save conversation logs

[0809] The server saves the conversation log between the user and the conversation agent and their emotional data in real time, and manages it as data for later analysis. For example, information such as "User message: Work has been really hard lately," "Emotion analysis: Stress, hard," and "Dialogue agent response: That's really hard. What specifically is causing you hardship?" is recorded in the database.

[0810] Input: Conversation logs and emotion data

[0811] Output: Saved data

[0812] Specific operation: The server stores conversation logs and emotion data in real time and manages them for later analysis.

[0813] (Application example 2)

[0814] 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."

[0815] As the importance of mental health care has increased in recent years, there is a growing need for systems that provide optimal mental health support and relaxation content according to the user's emotional state. Conventional mental health support systems have had the difficulty of analyzing a user's emotions in real time and individually recommending optimal content based on the results, making them unable to meet the diverse needs of users.

[0816] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user authentication information and verifying it based on a database, means for generating a session ID and notifying the user if user authentication is successful, means for generating an AI chatbot based on user data and setting an optimal dialogue scenario, means for saving a conversation log between the chatbot and the user in real time so that it can be analyzed later, and means for analyzing the user's emotional information and recommending optimal content based on the analysis results. This makes it possible to provide mental health support and relaxation content in real time that is tailored to the user's emotional state.

[0817] "User authentication information" is data used to identify a particular user and verify that the user is authorized to access a system.

[0818] A "database" is a system for efficiently storing, managing, and retrieving structured information.

[0819] A "session ID" is a unique identifier generated to identify a user's individual session.

[0820] An "AI chatbot" is a program that uses artificial intelligence to automate conversations with users.

[0821] A "dialogue scenario" is a plan that sets the flow and content of a dialogue with a user in advance.

[0822] A "conversation log" is data that records the interactions between a user and a chatbot.

[0823] "Emotion information" is data that expresses the user's emotional state.

[0824] "Emotion analysis" is the process of identifying a user's emotional state from words, facial expressions, etc.

[0825] "Content recommendation" is the act of suggesting optimal content based on a user's interests and emotional state.

[0826] An "input message" is text or voice data that a user sends to the system.

[0827] A "response message" is response data sent from a server or chatbot to a user.

[0828] A "viewing history" is a record of content that a user has viewed in the past.

[0829] "Analysis results" are the conclusions and findings obtained after conducting data analysis.

[0830] This invention is a 24-hour online mental health support system using an AI chatbot, combined with an emotion engine that recognizes and analyzes the user's emotions. This system is also capable of recommending optimal content in real time according to the user's emotional state. Below, we will explain how this system is implemented in detail.

[0831] Overall system structure

[0832] This system consists of a device used by the user, a central processing server, and an emotion engine that analyzes emotions. The device can be a smartphone, PC, tablet, etc., and is responsible for interacting with the user. The server processes data, generates AI chatbots, and sets up dialogue scenarios. The emotion engine then analyzes emotions from user input and provides optimal responses and content recommendations.

[0833] Program processing explanation

[0834] Authenticating a User and Starting a Session

[0835] 1. Device: The user accesses the application using a smartphone or PC and enters authentication information (user ID and password).

[0836] 2. Server: Receives the authentication information sent from the device and checks the database to verify the user's authenticity. If authentication is successful, generates a session ID and sends it to the device.

[0837] Creating an AI chatbot and setting up dialogue scenarios

[0838] 1. Server: Generates an AI chatbot based on user data and sets up optimal conversation scenarios. Individual scenarios are constructed taking into account data such as past conversation logs and stress levels.

[0839] Message sending and receiving and sentiment analysis

[0840] 1. Terminal: Receives input messages from the user and sends them to the server. For example, the user might input a message such as "Work has been really hard lately."

[0841] 2. Server: Passes the received message to the emotion engine for analysis. The emotion engine analyzes the user's emotion from the input message and identifies the emotional state, such as "stress" or "sadness."

[0842] Recommending content and continuing the conversation

[0843] 1. Server: Based on the sentiment analysis, the recommendation engine selects the most suitable content, such as relaxing music or a guided meditation video.

[0844] 2. Terminal: Displays the content recommendation list sent from the server to the user and plays the content selected by the user.

[0845] Examples of concrete examples and prompts

[0846] Specific examples

[0847] If the user types "Work has been really hard lately," the system will do the following:

[0848] 1. The user's message is sent from the device to the server.

[0849] 2. The server uses the emotion engine to identify the user's emotional state as "stress."

[0850] 3. Based on the results of the emotion analysis, the AI ​​chatbot asks, "That must be really tough. What specifically is causing you distress?"

[0851] 4. At the same time, it also recommends music playlists that have a relaxing effect.

[0852] Prompt Sentence Examples

[0853] The prompt to analyze the sentiment of the input "tired" is as follows:

[0854] User Input: I'm tired

[0855] Emotional state: stress, fatigue

[0856] Recommended content: Relaxation music, meditation videos

[0857] In this way, mental health support and content recommendations can be provided that are tailored to the user's emotional state, enhancing the user's experience.

[0858] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0859] Step 1:

[0860] A user accesses an application using a smartphone or PC and enters authentication information (user ID and password). The authentication information is obtained as input data. This authentication information is then sent from the device to the server.

[0861] Step 2:

[0862] The server compares the authentication information received from the terminal with a database to confirm whether the user is a legitimate user. The data processing performed here is to compare the authentication information, and the output is the result of authentication success or failure. If authentication is successful, the server generates a session ID and sends it to the terminal.

[0863] Step 3:

[0864] If the user is successfully authenticated, the terminal initializes the session using the session ID received from the server, allowing the user to log in to the system and prepare for the next operation.

[0865] Step 4:

[0866] The user inputs a message related to stress or emotion and sends it from the terminal to the server. The input data here is the user's message, and the output is the data sent to the server.

[0867] Step 5:

[0868] The server passes the user's input message to the emotion engine for emotion analysis. The emotion engine uses a generative AI model to analyze the emotional state (e.g., stress, fatigue) from the input message. The input is the user's message, and the output is the analyzed emotion data.

[0869] Step 6:

[0870] The server sets the optimal dialogue scenario based on the analysis results of the emotion engine and generates an AI chatbot. Here, data processing is performed to set the dialogue scenario using emotion data, and the optimized dialogue scenario is obtained as the output.

[0871] Step 7:

[0872] The server generates content recommendation results according to the user's emotional state. Specifically, the recommendation engine uses the emotion analysis results as prompts to suggest appropriate content (music, videos, guided meditations, etc.). The input is the emotion analysis results, and the output is a list of recommended content.

[0873] Step 8:

[0874] The terminal displays the content recommendation results received from the server to the user and plays the content selected by the user. Here, the content recommendation results are obtained as input, and the output is content information displayed to the user. The user can select content and start playing it.

[0875] Step 9:

[0876] The server stores the conversation log between the chatbot and the user, as well as the user's viewing history, in real time. It then performs big data analysis and manages the data to provide more accurate support in the future. The input is the conversation log and viewing history, and the output is an analyzable database entry.

[0877] 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.

[0878] 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.

[0879] 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.

[0880] [Third embodiment]

[0881] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0882] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0883] 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).

[0884] 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.

[0885] 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.

[0886] 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).

[0887] 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.

[0888] 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.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] 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."

[0893] This invention provides a 24-hour online mental health support system using an AI chatbot. This system provides immediate and effective mental health support to users by linking the user, terminal, and server components.

[0894] Server Roles

[0895] The server plays a central role in this system. First, it receives the authentication information sent by the user from the device and checks it against a database. If the user is authenticated, the server generates a session ID and sends it to the device to start the session. Next, the server generates an AI chatbot based on the user data. This AI chatbot sets up an optimal dialogue scenario based on the user's past stress level and conversation log. Furthermore, the server saves the conversation log between the user and the AI ​​chatbot in real time and manages it as data for later analysis.

[0896] Device Role

[0897] The terminal provides an interface that connects the user and the server. When the user launches the application, an authentication information input screen is displayed. The user enters the authentication information, and the terminal sends it to the server. When a session ID is returned from the server, the terminal initializes the session and displays a chat interface to the user. When the user enters a message, the terminal sends it to the server, receives a response message from the server, and displays it to the user.

[0898] User operations

[0899] To use this system, users first access the application from their device. After entering their authentication information on the login screen and pressing the login button, the server performs authentication. If authentication is successful, the user is redirected to a chat interface. Here, the user enters their stress and worries and receives appropriate advice from an AI chatbot. If necessary, the user can also be referred to a specialist.

[0900] Specific examples

[0901] For example, imagine a situation where a user is feeling very stressed at work. The user opens an application and types, "I'm stressed at work." This message is sent to the server via the device, and the server generates a response using an AI chatbot. The AI ​​chatbot asks, "What specifically is causing you stress?" and suggests next steps based on the user's response. If the user answers, "A particular project is putting a lot of pressure on me," the AI ​​chatbot might suggest, "Would you like me to provide you with specific support or resources to help with the progress of this project?"

[0902] This entire conversation takes place in real time, and the server stores the conversation log, allowing for continuous tracking of the user's mental health status. If necessary, the system can smoothly refer the user to a specialist.

[0903] As described above, the present invention provides immediate and effective support for the user's mental health care.

[0904] The processing flow will be explained below.

[0905] Program processing flow

[0906] Server Processing Steps

[0907] Step 1:

[0908] Server receives authentication information (user ID and password) sent by the user.

[0909] Step 2:

[0910] The server queries the database for authentication information and checks whether the corresponding user exists.

[0911] Step 3:

[0912] If the user exists, the server generates a session ID and sends it to the terminal along with a response indicating successful authentication.

[0913] Step 4:

[0914] For users who are successfully authenticated, the server generates an AI chatbot based on the user data.

[0915] Step 5:

[0916] The server sets up the optimal dialogue scenario based on user data and applies it to the AI ​​chatbot.

[0917] Step 6:

[0918] Conversation logs between users and AI chatbots are saved in real time and managed as data for later analysis.

[0919] Terminal processing steps

[0920] Step 1:

[0921] The terminal displays a screen for the user to input authentication information.

[0922] Step 2:

[0923] When the user inputs the authentication information and presses the send button, the terminal sends the authentication information to the server.

[0924] Step 3:

[0925] When the server returns the session ID, the terminal initializes the session.

[0926] Step 4:

[0927] The terminal receives the chatbot data sent from the server and displays a user-friendly chat interface.

[0928] Step 5:

[0929] When the user enters a message, the terminal sends the message to the server and waits for a response.

[0930] Step 6:

[0931] The terminal that receives the response message from the server displays it to the user.

[0932] User operation steps

[0933] Step 1:

[0934] The user starts the application and enters authentication information (user ID and password).

[0935] Step 2:

[0936] The user presses the login button to request authentication from the server.

[0937] Step 3:

[0938] Upon successful authentication, the user is redirected to the chat interface.

[0939] Step 4:

[0940] Users input their stress and worries into a chat interface.

[0941] Step 5:

[0942] The user receives a response from the AI ​​chatbot and checks the advice and solutions displayed.

[0943] Step 6:

[0944] Accept expert referrals suggested by the AI ​​chatbot when needed.

[0945] This series of steps allows users to receive immediate mental health support 24 hours a day.

[0946] Example 1

[0947] 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."

[0948] Mental health care is becoming an increasingly important issue in modern society. However, it is difficult to provide professional mental health support available 24 hours a day. There is a need for a system that can comprehensively manage a wide range of elements, such as user authentication, data management, and the provision of appropriate support, and provide immediate and effective support. Furthermore, when referral to a specialist is necessary, a system is also needed to ensure smooth referrals.

[0949] 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.

[0950] In this invention, the server includes means for receiving user authentication information and verifying it based on a database, means for generating a session ID and notifying the user if the user authentication is successful, means for generating a conversational bot using a generative AI model based on user data and setting an optimal conversation scenario, means for saving a conversation log between the conversational bot and the user in real time so that it can be analyzed later, and means for analyzing the conversation log and suggesting a referral to a specialist if necessary. This realizes online mental health support available 24 hours a day, allowing users to receive immediate and effective mental health care.

[0951] "Authentication Information" means the username, password, or other means of authentication used by a User to access a System.

[0952] "Database" refers to a system that stores user authentication information and past data and performs verification and reference as needed.

[0953] "Session ID" refers to an identifier that is generated by the server after a user has been successfully authenticated and that uniquely identifies the user's session.

[0954] A "generative AI model" refers to an artificial intelligence model that generates appropriate dialogue scenarios based on user data.

[0955] A "conversational bot" refers to a chatbot built on a generative AI model to engage in dialogue with users.

[0956] A "dialogue scenario" refers to a series of appropriate dialogue content presented by a generative AI model in a dialogue with a user.

[0957] A "conversation log" refers to the history of messages exchanged between a conversational bot and a user.

[0958] "Professional referral" refers to the process of referring a user to a professional mental health care provider, if necessary.

[0959] "Real-time" refers to the system's ability to interact with and process users instantly.

[0960] This invention provides a 24-hour online mental health support system using an AI chatbot. This system provides immediate and effective mental health support to users by linking the user, terminal, and server components.

[0961] Server Roles

[0962] The server plays a central role in this system. First, it receives the authentication information sent by the user from the device and checks it against a database. Databases such as MySQL or PostgreSQL are typically used. Once the user is authenticated, the server generates a session ID and sends it to the device to start the session. The session ID is usually generated as a UUID (Universally Unique Identifier). The server then generates a conversational bot based on the user data using a generative AI model. OpenAI's GPT-4 is one example of a generative AI model. This conversational bot sets an optimal conversation scenario based on the user's past stress level and conversation log. Furthermore, the server saves the conversation log between the user and the conversational bot in real time and manages it as data for later analysis. Storage services such as Amazon S3 and Google Cloud Storage can be used.

[0963] Device Role

[0964] The terminal provides an interface that connects the user and the server. When the user starts the application, an authentication information input screen is displayed. The user enters their username and password here. Once the input is complete, the terminal sends it to the server. When the server returns a session ID, the terminal initializes the session and displays a chat interface to the user. When the user enters a message, the terminal sends it to the server, receives a response message from the server in real time, and displays it to the user.

[0965] User operations

[0966] To use this system, users first access the application from their device. After entering their authentication information on the login screen and pressing the login button, the server performs authentication. If authentication is successful, the user is redirected to a chat interface. Here, the user inputs their stress and worries and receives appropriate advice from a conversational bot using a generative AI model. If necessary, the user can also be referred to an expert.

[0967] Specific examples

[0968] For example, a user might type, "I'm feeling stressed at work." The device then sends this message to the server. The server uses a generative AI model to generate a response, asking, "What specifically is causing you stress?" If the user types, "A particular project is putting a lot of pressure on me," the conversational bot might suggest, "Would you like us to provide you with specific support or resources to help with the progress of this project?" This entire conversation takes place in real time, and the server stores the conversation log, continuously tracking the user's mental health status. If necessary, the server can smoothly refer the user to a specialist.

[0969] Prompt Sentence Examples

[0970] "I'm stressed about a particular work issue. What specifically is causing it? And what specific solutions do you suggest for that issue?"

[0971] As described above, the present invention provides immediate and effective support for the user's mental health care.

[0972] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0973] Step 1:

[0974] The user launches the application and enters their authentication information (username and password).

[0975] Input: Username and Password

[0976] How it works: A user accesses a login screen on their device and enters their credentials.

[0977] Output: The entered credentials

[0978] Step 2:

[0979] The terminal sends the user's authentication information to the server.

[0980] Input: Authentication information (username and password)

[0981] How it works: The device sends authentication information to the server using an HTTP POST request.

[0982] Output: Authentication information sent to the server

[0983] Step 3:

[0984] The server checks the credentials against a database and authenticates the user.

[0985] Input: Credentials

[0986] What happens: The server queries a database (e.g. MySQL, PostgreSQL) and matches the credentials. If successful, the user is authenticated.

[0987] Output: User authentication result (success or failure)

[0988] Step 4:

[0989] When authentication is successful, the server generates a session ID and notifies the terminal.

[0990] Input: Authentication result (success)

[0991] How it works: If authentication is successful, the server generates a session ID as a unique UUID and sends it to the device.

[0992] Output: Session ID

[0993] Step 5:

[0994] The terminal receives the session ID and initializes the session.

[0995] Input: Session ID

[0996] Behavior: The terminal uses the received session ID to initialize the session and displays a login success screen to the user.

[0997] Output: Session initialized

[0998] Step 6:

[0999] The server obtains the user's past data (stress level, conversation log) and generates a conversational bot using a generative AI model.

[1000] Input: Session ID, User Data

[1001] How it works: The server retrieves the user's past data from the database and sets the parameters of a generative AI model (e.g., GPT-4) to generate a conversational bot.

[1002] Output: The generated conversational bot

[1003] Step 7:

[1004] The server generates an initial message for the conversational bot and sends it to the terminal.

[1005] Input: Generated conversational bot, user data

[1006] How it works: The server launches the conversational bot, generates an initial question or message, and sends it to the user.

[1007] Output: Initial message

[1008] Step 8:

[1009] The device receives the initial message and displays it in the chat interface.

[1010] Input: initial message

[1011] Behavior: The terminal displays the initial message it receives in the chat interface.

[1012] Output: Initial message displayed

[1013] Step 9:

[1014] The user inputs their stress and worries into a chat interface.

[1015] Input: Details of stress and worries

[1016] How it works: The user enters their stress and worries and presses the send button.

[1017] Output: The input message

[1018] Step 10:

[1019] The terminal sends the user's message to the server.

[1020] Input: The message entered

[1021] Operation: The terminal sends the user's message to the server.

[1022] Output: Message sent to the server

[1023] Step 11:

[1024] The server generates a response message using a generative AI model based on the user's message.

[1025] Input: User message, generative AI model

[1026] How it works: The server parses the user's message and uses a generative AI model to generate an appropriate response message.

[1027] Output: Response message

[1028] Step 12:

[1029] The server sends a response message to the terminal.

[1030] Input: Response message

[1031] Operation: The server sends the generated response message to the terminal.

[1032] Output: Response message sent to the terminal

[1033] Step 13:

[1034] The terminal receives the response message and displays it to the user.

[1035] Input: Response message

[1036] Behavior: The device displays the received reply message in the chat interface.

[1037] Output: The displayed response message

[1038] Step 14:

[1039] The server stores the conversation log between the user and the conversational bot in real time.

[1040] Input: User's message, reply message

[1041] How it works: The server stores all messages between users and conversational bots in a database.

[1042] Output: Saved conversation logs

[1043] Step 15:

[1044] The server analyzes the conversation log and suggests referrals to experts if necessary.

[1045] Input: conversation log

[1046] How it works: The server analyzes the saved conversation logs and, if it determines that a referral to an expert is necessary, makes such a suggestion to the user.

[1047] Output: Referral message if necessary

[1048] The above is the flow of processing of the program of this system.

[1049] (Application example 1)

[1050] 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."

[1051] Conventional mental health care systems often delay providing appropriate support for users' stress and worries. Furthermore, in brick-and-mortar stores, it can be difficult for staff to constantly respond to customers, which can lead to a decline in customer satisfaction. To solve these problems, a fast and effective customer support system is needed, but current technology does not provide a sufficient solution.

[1052] 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.

[1053] In this invention, the server includes means for receiving user authentication information and verifying it based on a database, means for generating a session ID and notifying the user if the user authentication is successful, means for generating an AI chatbot using a generative AI model based on user data and setting an optimal dialogue scenario, means for saving a conversation log between the chatbot and the user in real time for later analysis, and means for the generated dialogue scenario to include responses generated based on prompt sentences intended for customer support in a physical store. This enables effective mental health care for users and prompt and appropriate customer support in a physical store.

[1054] "Authentication information" refers to information used by a user when logging in to a system, such as a user name and password.

[1055] A "database" is a system for organizing and managing a wide variety of data, and is a place where user authentication information, conversation logs, etc. are stored.

[1056] "Session ID" means a unique identifier generated after successful user authentication to identify an interactive session between a particular user and a system.

[1057] A "generative AI model" is an algorithm that uses artificial intelligence techniques to design a conversational interface based on user data.

[1058] An "AI chatbot" is a program that uses artificial intelligence to automatically generate responses to users' questions and inquiries.

[1059] A "dialogue scenario" refers to a series of scenes and responses that define the flow and content when an AI chatbot converses with a user.

[1060] A "conversation log" is data that records the content of the conversation between a user and an AI chatbot, and is saved in a format that can be analyzed later.

[1061] A "prompt" is a piece of text or phrase that serves as a starting point for a generative AI model to generate a specific response.

[1062] A "brick and mortar store" refers to a retail or service establishment that has a physical presence in a physical location where face-to-face commerce with customers takes place.

[1063] "Customer support" refers to the activity of providing assistance to customers to respond to and resolve questions or problems that arise when using a product or service.

[1064] "Referral to an expert" refers to connecting the user to a person or department with specialized knowledge if the AI ​​chatbot determines this is necessary through dialogue.

[1065] This invention relates to an AI chatbot system for customer support in brick-and-mortar stores. This system involves user, terminal, and server components interacting with each other to provide instant and effective question responses and support to users.

[1066] Server Roles

[1067] The server plays a central role in this system. Its functions are realized by the following procedure.

[1068] 1. Receiving and verifying authentication information

[1069] The server receives the authentication information sent by the user from the terminal and compares it with the database. If the authentication is successful, the server generates a session ID and notifies the user terminal.

[1070] 2. Use of generative AI models

[1071] The AI ​​chatbot is generated using a generative AI model based on user data and the optimal dialogue scenario is set up. Specifically, prompts are prepared based on the user's past inquiry history and stress level, and the chatbot's responses are generated.

[1072] 3. Save conversation logs

[1073] The conversation log between the chatbot and the user is saved in real time and can be analyzed later. This allows us to understand user behavior patterns and problems, leading to further improvements to the service.

[1074] Hardware used: Server

[1075] Software used: Generative AI models, database management system

[1076] Device Role

[1077] The terminal provides an interface between the user and the server.

[1078] 1. Enter and submit authentication information

[1079] When a user launches an application, a screen for entering authentication information appears. The user enters the authentication information, and the device sends it to the server.

[1080] 2. Displaying the chat interface

[1081] Once the server returns a session ID, the terminal initializes the session and displays a chat interface to the user. When the user enters a message, the terminal sends it to the server, receives a response message from the server, and displays it to the user.

[1082] Hardware used: smartphone, tablet

[1083] Software used: Front-end application (e.g., Flutter, React Native)

[1084] User operations

[1085] To use this system, a user first accesses the application from their device and enters their authentication information on the login screen. After successful authentication, the user is redirected to a chat interface. Here, the user enters their question or concern and receives appropriate advice or a response from the AI ​​chatbot. For example, if a user enters "I'd like to know more about this product," this message is sent to the server via the device, and the server uses a generative AI model to generate a response. An example of a prompt for the generated response is "User: "I'd like to know more about this product"\nAI:". Based on this prompt, the AI ​​chatbot returns a detailed answer such as: "Of course. This product is made of high-quality materials and has the following features..."

[1086] This entire dialogue is conducted in real time, and the server stores the conversation log, allowing for continuous tracking of the user's behavior and needs. If necessary, the user can be smoothly referred to an expert. This improves the customer experience in physical stores and makes it possible to provide high-quality customer support.

[1087] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1088] Step 1:

[1089] A user starts an application from a terminal and enters authentication information (user name and password). The terminal sends this authentication information to the server. The input is the username and password, and the output is the authentication information sent.

[1090] Step 2:

[1091] The server compares the received authentication information with a database. The operation involves running a database query to determine whether the user is valid. The input is the username and password, and the output is the authentication result. If authentication is successful, the server generates a session ID and notifies the terminal.

[1092] Step 3:

[1093] The terminal initializes the session using the session ID received from the server. This ensures that only authenticated users can use the chat interface. The input is the session ID, and the output is session initialization.

[1094] Step 4:

[1095] The user inputs a question or concern into the chat interface. The terminal sends this message to the server. The input is the user's message, and the output is the message sent.

[1096] Step 5:

[1097] The server uses a generative AI model to create a prompt sentence to generate a response based on the received user message. The inputs are the user message, user data, and past conversation logs, and the output is the generated prompt sentence. Specific operation involves generating an example prompt sentence: "User: 'I'd like to know more about this product'\nAI:".

[1098] Step 6:

[1099] The server uses a generative AI model to generate a response based on the prompt. The input is the prompt, and the output is the generated AI chatbot's response. The generated response is sent from the server to the device.

[1100] Step 7:

[1101] The terminal receives a response message from the server and displays it to the user. The input is the generated AI chatbot's response, and the output is the response displayed to the user. This allows the user to obtain an appropriate answer to their question or concern.

[1102] Step 8:

[1103] The server stores the conversation log between the chatbot and the user in real time for later analysis. The input is the content of the conversation, and the output is the saved conversation log. Operations include writing the conversation log to the database.

[1104] Step 9:

[1105] If necessary, the server can refer the user to an expert. The input is the user's problem and the analysis results, and the output is a referral suggestion to an expert. Specific actions can include providing the expert's contact information or inviting the user to chat directly.

[1106] 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.

[1107] This invention combines an online mental health support system using an AI chatbot that is available 24 hours a day with an emotion engine that recognizes the user's emotions. This system provides immediate and effective mental health support to users by linking the user, device, server, and emotion engine components.

[1108] Server Roles

[1109] The server plays a central role in the system. First, it receives authentication information sent by the user and verifies the user's identity by checking it against a database. If authentication is successful, it generates a session ID and sends it to the device to start the session. Next, the server generates an AI chatbot based on the user data. This AI chatbot sets an optimal dialogue scenario based on the user's past stress level and conversation logs. Furthermore, it uses an emotion engine to analyze emotions from the user's input messages and past dialogue logs, and dynamically adjusts the dialogue scenario based on the user's emotions. In addition, the server saves the conversation logs and emotion data between the user and the AI ​​chatbot in real time and manages them as data for later analysis.

[1110] Device Role

[1111] The terminal provides an interface that connects the user and the server. When the user launches the application, an authentication information input screen is displayed and the user enters their authentication information. The terminal sends that information to the server, and upon receiving a session ID from the server, initializes the session. Next, the terminal receives the chatbot data sent from the server and displays a user-friendly chat interface. When the user enters a message, the terminal sends that message to the server and waits for a response. After receiving the response message from the server, the terminal displays it to the user.

[1112] User operations

[1113] Users access the application using a smartphone or PC and log in by entering their authentication information. Once authentication is successful, the user is redirected to a chat interface where they can enter their stress and worries and receive a response from the AI ​​chatbot. An emotion engine analyzes the user's emotions, and the AI ​​chatbot provides optimal advice and solutions based on those emotions. If necessary, the user can be referred to an expert.

[1114] Specific examples

[1115] For example, consider a situation where a user types, "Work has been really hard lately." The user's message is sent from the device to the server, and the server uses an emotion engine to analyze the emotion from the user's message content. The emotion engine detects that the user is feeling stressed and identifies the emotion "hard." The AI ​​chatbot generates a response based on this emotion. The chatbot asks the user, "That must be really hard. What specifically is causing you hardship?" and provides specific advice through dialogue. If the user replies, "I'm feeling pressured because the project progress is not going well," the chatbot suggests, "Can I introduce you to some tools or support to help you manage the project progress?" This allows the user to find a specific solution.

[1116] This system allows users to receive effective mental health support in real time, 24 hours a day. By combining it with an emotion engine, it is possible to accurately grasp the user's emotions and provide more appropriate responses. This allows for immediate and effective support in the user's mental health care.

[1117] The processing flow will be explained below.

[1118] Server Processing Steps

[1119] Step 1:

[1120] Server receives authentication information (user ID and password) sent by the user.

[1121] Step 2:

[1122] The server queries the database for authentication information and checks whether the corresponding user exists.

[1123] Step 3:

[1124] If the user exists, the server generates a session ID and sends it to the terminal along with a response indicating successful authentication.

[1125] Step 4:

[1126] For users who are successfully authenticated, the server generates an AI chatbot based on the user data.

[1127] Step 5:

[1128] The server sets up the optimal dialogue scenario based on user data and applies it to the AI ​​chatbot.

[1129] Step 6:

[1130] The server runs an emotion engine to analyze emotions from user input messages and past dialogue logs.

[1131] Step 7:

[1132] Based on the emotional information analyzed by the emotion engine, the server dynamically adjusts the dialogue scenario.

[1133] Step 8:

[1134] The server generates responses for the AI ​​chatbot based on the adjusted dialogue scenario.

[1135] Step 9:

[1136] Conversation logs and emotional data between users and AI chatbots are saved in real time and managed as data for later analysis.

[1137] Terminal processing steps

[1138] Step 1:

[1139] The terminal displays a screen for the user to input authentication information.

[1140] Step 2:

[1141] When the user inputs the authentication information and presses the send button, the terminal sends the authentication information to the server.

[1142] Step 3:

[1143] When the server returns the session ID, the terminal initializes the session.

[1144] Step 4:

[1145] The terminal receives the chatbot data sent from the server and displays a user-friendly chat interface.

[1146] Step 5:

[1147] When the user enters a message, the terminal sends the message to the server and waits for a response.

[1148] Step 6:

[1149] The terminal that receives the response message from the server displays it to the user.

[1150] User operation steps

[1151] Step 1:

[1152] The user accesses the application using a smartphone or PC and enters authentication information (user ID and password).

[1153] Step 2:

[1154] The user presses the login button to request authentication from the server.

[1155] Step 3:

[1156] Upon successful authentication, the user is redirected to the chat interface.

[1157] Step 4:

[1158] Users input their stress and worries into a chat interface.

[1159] Step 5:

[1160] The user receives a response from the AI ​​chatbot and checks the advice and solutions displayed.

[1161] Step 6:

[1162] Users input detailed information in response to follow-up questions and suggestions from the AI ​​chatbot.

[1163] Step 7:

[1164] Accept expert referrals suggested by the AI ​​chatbot when needed.

[1165] Example 2

[1166] 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."

[1167] Conventional online mental health support systems have had difficulty accurately recognizing users' emotions and providing appropriate dialogue and advice based on those emotions. It has also been difficult to provide user support 24 hours a day. This has resulted in an inability to respond appropriately to users' emotions, limiting the effectiveness of mental health care.

[1168] 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.

[1169] In this invention, the server includes means for receiving user authentication information and verifying it based on a database, means for generating a session ID and notifying the user if the user authentication is successful, means for generating a dialogue agent based on user data and setting an optimal dialogue scenario, means for analyzing user input messages in real time using emotion analysis means and dynamically adjusting the dialogue scenario based on the emotions, and means for saving a conversation log between the dialogue agent and the user in real time so that it can be analyzed later. This makes it possible to accurately grasp the user's emotions and provide appropriate and timely dialogue and advice based on them.

[1170] "User authentication information" refers to the identification information (e.g., user ID and password) that a user enters to log in to a system.

[1171] A "database" is an information storage system for systematically storing and managing information such as user authentication information and past interaction logs.

[1172] A "session ID" is a unique identifier issued to a user who has been successfully authenticated and is used to track and manage the session.

[1173] A "conversational agent" is an artificial intelligence model created to converse with users, and has the ability to provide appropriate dialogue based on the user's past data and emotional analysis.

[1174] "Emotion analysis means" is a technology for extracting emotional information from a user's input message and generating appropriate dialogue scenarios and responses based on that information.

[1175] A "dialogue scenario" defines a series of topics and question sequences that a dialogue agent uses in conversation with a user, and is dynamically adjusted according to the user's situation and emotions.

[1176] A "conversation log" is a record of all interactions between a user and a conversational agent, which can be analyzed and referenced later.

[1177] This invention combines an online mental health support system using an AI chatbot that is available 24 hours a day with an emotion engine that recognizes the user's emotions. This system provides immediate and effective mental health support to users by linking the user, terminal, server, and emotion engine components. A detailed explanation of how to implement this system is provided below.

[1178] Server Roles

[1179] The server plays a central role in the system. First, it receives authentication information sent by the user and verifies the user's identity by checking it against a database. If authentication is successful, it generates a session ID and sends it to the terminal to start the session. Next, the server generates a dialogue agent based on the user data. This dialogue agent sets an optimal dialogue scenario based on the user's past stress level and conversation log. Furthermore, it uses emotion analysis means to analyze emotions from the user's input messages and past dialogue logs, and dynamically adjusts the dialogue scenario based on the user's emotions. In addition, the server saves the dialogue logs and emotion data of the user and dialogue agent in real time and manages them as data for later analysis.

[1180] Device Role

[1181] The terminal provides an interface that connects the user and the server. When the user launches an application, an authentication information entry screen appears and the user enters their authentication information. The terminal sends that information to the server, and upon receiving a session ID from the server, initializes the session. Next, the terminal receives the conversation agent data sent from the server and displays a user-friendly chat interface. When the user enters a message, the terminal sends that message to the server and waits for a response. After receiving the response message from the server, the terminal displays it to the user.

[1182] User operations

[1183] Users access the application using a smartphone or PC and log in by entering their authentication information. Once authentication is successful, the user is redirected to a chat interface, where they can enter their stress and worries and receive a response from a conversational agent. An emotion analysis means analyzes the user's emotions, and the conversational agent provides optimal advice and measures based on those emotions. If necessary, the user can be referred to an expert.

[1184] Hardware and software used

[1185] The hardware used will be a high-performance database and a server machine with processing power. Specifically, cloud service providers (e.g., AWS, Google Cloud Platform) can be used. Normal smartphones and PCs are expected to be used as devices. Software used will likely include emotion analysis technology for emotion analysis and a generative AI model (e.g., GPT-3) for the dialogue agent.

[1186] Examples of concrete examples and prompts

[1187] For example, consider a situation where a user types, "Work has been really hard lately." In this case, the user's message is sent from the terminal to the server, and the server uses emotion analysis means to analyze the emotion from the content of the user's message. The emotion analysis means detects that the user is feeling stressed and identifies the emotion "hard." The dialogue agent generates a response based on this emotion. The dialogue agent asks the user, "That must be really hard. What specifically is causing you to feel hard?" and provides specific advice through dialogue. If the user answers, "I'm feeling pressured because the project progress is not going well," the dialogue agent suggests, "Would you like me to introduce you to some tools or support to help you manage the project progress?" This allows the user to obtain a specific solution.

[1188] Below is an example of a prompt sentence to input to the generative AI model.

[1189] "You are a conversational agent. Your role is to understand the message entered by the user and provide an appropriate response based on the user's sentiment. Below is the user's message and the result of sentiment analysis:

[1190] User message: 'Work has been really hard lately'

[1191] Sentiment analysis: 'Stressful, painful'

[1192] Based on this, generate an appropriate response for the user."

[1193] This system allows users to receive effective mental health support in real time, 24 hours a day. By combining it with emotion analysis methods, it is possible to accurately grasp the user's emotions and provide more appropriate responses. This allows for immediate and effective support in the user's mental health care.

[1194] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1195] Step 1:

[1196] Authenticating Users

[1197] The user starts an application and enters authentication information (user ID and password). The entered authentication information is sent from the terminal to the server. The server receives the authentication information and checks it against a database to verify that it is a valid user. For example, if the authentication information "user name: john_doe, password: password123" is entered, the server checks it against the database. If authentication is successful, the server generates a session ID "abc123" and sends it to the terminal.

[1198] Input: User authentication information (user ID, password)

[1199] Output: Session ID

[1200] Specific operation: When the user enters authentication information and authentication is successful, the server generates a session ID and sends it to the terminal.

[1201] Step 2:

[1202] Initializing the session

[1203] The terminal starts a session using the session ID received from the server and displays a chat interface for the user. After receiving the session ID, the terminal displays the chat screen to the user, allowing the user to enter a message.

[1204] Input: Session ID

[1205] Output: Chat interface displayed

[1206] Specific actions: After receiving the session ID, the device will display the chat interface and allow the user to enter a message.

[1207] Step 3:

[1208] Generating a conversational agent

[1209] The server generates a dialogue agent based on user data. This dialogue agent sets up an optimal dialogue scenario based on the user's past stress level and conversation log. For example, a generative AI model can be used to create an optimal dialogue scenario based on the user profile.

[1210] Input: User data (past stress levels, conversation logs)

[1211] Output: A conversational agent

[1212] Specific operation: The server collects the user's past data and generates a dialogue agent using a generative AI model, while also setting the optimal dialogue scenario.

[1213] Step 4:

[1214] Receiving user messages

[1215] The user enters a message into the chat interface and presses the send button. The device then sends the message to the server. For example, the user enters "Work has been really hard lately," and the device sends this to the server.

[1216] Input: User message

[1217] Output: None (forwarding the message)

[1218] Specific operation: The terminal sends the message entered by the user to the server.

[1219] Step 5:

[1220] Emotion analysis

[1221] The server uses emotion analysis means to analyze the received user message and identify the emotion. For example, from the input message "Work has been really hard lately," the server identifies the emotion "stressed, hard."

[1222] Input: User message

[1223] Output: Emotional information

[1224] Specific operation: The server analyzes the input message and extracts emotional information.

[1225] Step 6:

[1226] Response Generation

[1227] Based on the results of emotion analysis, the dialogue agent generates an appropriate response. For example, if the user's emotion is "painful," the dialogue agent will generate a response such as, "That must be really hard. What specifically is causing you pain?"

[1228] Input: Emotion information, user data

[1229] Output: Response of the conversational agent

[1230] Specific operation: Based on the results of emotion analysis, the dialogue agent uses a generative AI model to generate an appropriate response.

[1231] Step 7:

[1232] Sending and Displaying Responses

[1233] The server then sends the generated response message to the terminal, which then displays it to the user. For example, the response generated by the conversational agent is "That's really hard. What specifically is causing you pain?", and the terminal displays it to the user.

[1234] Input: Response message from the conversation agent

[1235] Output: Display a message on the user's screen

[1236] Specific operation: The terminal receives the response message from the server and displays it to the user.

[1237] Step 8:

[1238] Save conversation logs

[1239] The server saves the conversation log between the user and the conversation agent and their emotional data in real time, and manages it as data for later analysis. For example, information such as "User message: Work has been really hard lately," "Emotion analysis: Stress, hard," and "Dialogue agent response: That's really hard. What specifically is causing you hardship?" is recorded in the database.

[1240] Input: Conversation logs and emotion data

[1241] Output: Saved data

[1242] Specific operation: The server stores conversation logs and emotion data in real time and manages them for later analysis.

[1243] (Application example 2)

[1244] 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."

[1245] As the importance of mental health care has increased in recent years, there is a growing need for systems that provide optimal mental health support and relaxation content according to the user's emotional state. Conventional mental health support systems have had the difficulty of analyzing a user's emotions in real time and individually recommending optimal content based on the results, making them unable to meet the diverse needs of users.

[1246] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user authentication information and verifying it based on a database, means for generating a session ID and notifying the user if user authentication is successful, means for generating an AI chatbot based on user data and setting an optimal dialogue scenario, means for saving a conversation log between the chatbot and the user in real time so that it can be analyzed later, and means for analyzing the user's emotional information and recommending optimal content based on the analysis results. This makes it possible to provide mental health support and relaxation content in real time that is tailored to the user's emotional state.

[1247] "User authentication information" is data used to identify a particular user and verify that the user is authorized to access a system.

[1248] A "database" is a system for efficiently storing, managing, and retrieving structured information.

[1249] A "session ID" is a unique identifier generated to identify a user's individual session.

[1250] An "AI chatbot" is a program that uses artificial intelligence to automate conversations with users.

[1251] A "dialogue scenario" is a plan that sets the flow and content of a dialogue with a user in advance.

[1252] A "conversation log" is data that records the interactions between a user and a chatbot.

[1253] "Emotion information" is data that expresses the user's emotional state.

[1254] "Emotion analysis" is the process of identifying a user's emotional state from words, facial expressions, etc.

[1255] "Content recommendation" is the act of suggesting optimal content based on a user's interests and emotional state.

[1256] An "input message" is text or voice data that a user sends to the system.

[1257] A "response message" is response data sent from a server or chatbot to a user.

[1258] A "viewing history" is a record of content that a user has viewed in the past.

[1259] "Analysis results" are the conclusions and findings obtained after conducting data analysis.

[1260] This invention is a 24-hour online mental health support system using an AI chatbot, combined with an emotion engine that recognizes and analyzes the user's emotions. This system is also capable of recommending optimal content in real time according to the user's emotional state. Below, we will explain how this system is implemented in detail.

[1261] Overall system structure

[1262] This system consists of a device used by the user, a central processing server, and an emotion engine that analyzes emotions. The device can be a smartphone, PC, tablet, etc., and is responsible for interacting with the user. The server processes data, generates AI chatbots, and sets up dialogue scenarios. The emotion engine then analyzes emotions from user input and provides optimal responses and content recommendations.

[1263] Program processing explanation

[1264] Authenticating a User and Starting a Session

[1265] 1. Device: The user accesses the application using a smartphone or PC and enters authentication information (user ID and password).

[1266] 2. Server: Receives the authentication information sent from the device and checks the database to verify the user's authenticity. If authentication is successful, generates a session ID and sends it to the device.

[1267] Creating an AI chatbot and setting up dialogue scenarios

[1268] 1. Server: Generates an AI chatbot based on user data and sets up optimal conversation scenarios. Individual scenarios are constructed taking into account data such as past conversation logs and stress levels.

[1269] Message sending and receiving and sentiment analysis

[1270] 1. Terminal: Receives input messages from the user and sends them to the server. For example, the user might input a message such as "Work has been really hard lately."

[1271] 2. Server: Passes the received message to the emotion engine for analysis. The emotion engine analyzes the user's emotion from the input message and identifies the emotional state, such as "stress" or "sadness."

[1272] Recommending content and continuing the conversation

[1273] 1. Server: Based on the sentiment analysis, the recommendation engine selects the most suitable content, such as relaxing music or a guided meditation video.

[1274] 2. Terminal: Displays the content recommendation list sent from the server to the user and plays the content selected by the user.

[1275] Examples of concrete examples and prompts

[1276] Specific examples

[1277] If the user types "Work has been really hard lately," the system will do the following:

[1278] 1. The user's message is sent from the device to the server.

[1279] 2. The server uses the emotion engine to identify the user's emotional state as "stress."

[1280] 3. Based on the results of the emotion analysis, the AI ​​chatbot asks, "That must be really tough. What specifically is causing you distress?"

[1281] 4. At the same time, it also recommends music playlists that have a relaxing effect.

[1282] Prompt Sentence Examples

[1283] The prompt to analyze the sentiment of the input "tired" is as follows:

[1284] User Input: I'm tired

[1285] Emotional state: stress, fatigue

[1286] Recommended content: Relaxation music, meditation videos

[1287] In this way, mental health support and content recommendations can be provided that are tailored to the user's emotional state, enhancing the user's experience.

[1288] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1289] Step 1:

[1290] A user accesses an application using a smartphone or PC and enters authentication information (user ID and password). The authentication information is obtained as input data. This authentication information is then sent from the device to the server.

[1291] Step 2:

[1292] The server compares the authentication information received from the terminal with a database to confirm whether the user is a legitimate user. The data processing performed here is to compare the authentication information, and the output is the result of authentication success or failure. If authentication is successful, the server generates a session ID and sends it to the terminal.

[1293] Step 3:

[1294] If the user is successfully authenticated, the terminal initializes the session using the session ID received from the server, allowing the user to log in to the system and prepare for the next operation.

[1295] Step 4:

[1296] The user inputs a message related to stress or emotion and sends it from the terminal to the server. The input data here is the user's message, and the output is the data sent to the server.

[1297] Step 5:

[1298] The server passes the user's input message to the emotion engine for emotion analysis. The emotion engine uses a generative AI model to analyze the emotional state (e.g., stress, fatigue) from the input message. The input is the user's message, and the output is the analyzed emotion data.

[1299] Step 6:

[1300] The server sets the optimal dialogue scenario based on the analysis results of the emotion engine and generates an AI chatbot. Here, data processing is performed to set the dialogue scenario using emotion data, and the optimized dialogue scenario is obtained as the output.

[1301] Step 7:

[1302] The server generates content recommendation results according to the user's emotional state. Specifically, the recommendation engine uses the emotion analysis results as prompts to suggest appropriate content (music, videos, guided meditations, etc.). The input is the emotion analysis results, and the output is a list of recommended content.

[1303] Step 8:

[1304] The terminal displays the content recommendation results received from the server to the user and plays the content selected by the user. Here, the content recommendation results are obtained as input, and the output is content information displayed to the user. The user can select content and start playing it.

[1305] Step 9:

[1306] The server stores the conversation log between the chatbot and the user, as well as the user's viewing history, in real time. It then performs big data analysis and manages the data to provide more accurate support in the future. The input is the conversation log and viewing history, and the output is an analyzable database entry.

[1307] 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.

[1308] 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.

[1309] 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.

[1310] [Fourth embodiment]

[1311] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1312] 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.

[1313] 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).

[1314] 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.

[1315] 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.

[1316] 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).

[1317] 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.

[1318] 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.

[1319] 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.

[1320] 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.

[1321] 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.

[1322] 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.

[1323] 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."

[1324] This invention provides a 24-hour online mental health support system using an AI chatbot. This system provides immediate and effective mental health support to users by linking the user, terminal, and server components.

[1325] Server Roles

[1326] The server plays a central role in this system. First, it receives the authentication information sent by the user from the device and checks it against a database. If the user is authenticated, the server generates a session ID and sends it to the device to start the session. Next, the server generates an AI chatbot based on the user data. This AI chatbot sets up an optimal dialogue scenario based on the user's past stress level and conversation log. Furthermore, the server saves the conversation log between the user and the AI ​​chatbot in real time and manages it as data for later analysis.

[1327] Device Role

[1328] The terminal provides an interface that connects the user and the server. When the user launches the application, an authentication information input screen is displayed. The user enters the authentication information, and the terminal sends it to the server. When a session ID is returned from the server, the terminal initializes the session and displays a chat interface to the user. When the user enters a message, the terminal sends it to the server, receives a response message from the server, and displays it to the user.

[1329] User operations

[1330] To use this system, users first access the application from their device. After entering their authentication information on the login screen and pressing the login button, the server performs authentication. If authentication is successful, the user is redirected to a chat interface. Here, the user enters their stress and worries and receives appropriate advice from an AI chatbot. If necessary, the user can also be referred to a specialist.

[1331] Specific examples

[1332] For example, imagine a situation where a user is feeling very stressed at work. The user opens an application and types, "I'm stressed at work." This message is sent to the server via the device, and the server generates a response using an AI chatbot. The AI ​​chatbot asks, "What specifically is causing you stress?" and suggests next steps based on the user's response. If the user answers, "A particular project is putting a lot of pressure on me," the AI ​​chatbot might suggest, "Would you like me to provide you with specific support or resources to help with the progress of this project?"

[1333] This entire conversation takes place in real time, and the server stores the conversation log, allowing for continuous tracking of the user's mental health status. If necessary, the system can smoothly refer the user to a specialist.

[1334] As described above, the present invention provides immediate and effective support for the user's mental health care.

[1335] The processing flow will be explained below.

[1336] Program processing flow

[1337] Server Processing Steps

[1338] Step 1:

[1339] Server receives authentication information (user ID and password) sent by the user.

[1340] Step 2:

[1341] The server queries the database for authentication information and checks whether the corresponding user exists.

[1342] Step 3:

[1343] If the user exists, the server generates a session ID and sends it to the terminal along with a response indicating successful authentication.

[1344] Step 4:

[1345] For users who are successfully authenticated, the server generates an AI chatbot based on the user data.

[1346] Step 5:

[1347] The server sets up the optimal dialogue scenario based on user data and applies it to the AI ​​chatbot.

[1348] Step 6:

[1349] Conversation logs between users and AI chatbots are saved in real time and managed as data for later analysis.

[1350] Terminal processing steps

[1351] Step 1:

[1352] The terminal displays a screen for the user to input authentication information.

[1353] Step 2:

[1354] When the user inputs the authentication information and presses the send button, the terminal sends the authentication information to the server.

[1355] Step 3:

[1356] When the server returns the session ID, the terminal initializes the session.

[1357] Step 4:

[1358] The terminal receives the chatbot data sent from the server and displays a user-friendly chat interface.

[1359] Step 5:

[1360] When the user enters a message, the terminal sends the message to the server and waits for a response.

[1361] Step 6:

[1362] The terminal that receives the response message from the server displays it to the user.

[1363] User operation steps

[1364] Step 1:

[1365] The user starts the application and enters authentication information (user ID and password).

[1366] Step 2:

[1367] The user presses the login button to request authentication from the server.

[1368] Step 3:

[1369] Upon successful authentication, the user is redirected to the chat interface.

[1370] Step 4:

[1371] Users input their stress and worries into a chat interface.

[1372] Step 5:

[1373] The user receives a response from the AI ​​chatbot and checks the advice and solutions displayed.

[1374] Step 6:

[1375] Accept expert referrals suggested by the AI ​​chatbot when needed.

[1376] This series of steps allows users to receive immediate mental health support 24 hours a day.

[1377] Example 1

[1378] 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."

[1379] Mental health care is becoming an increasingly important issue in modern society. However, it is difficult to provide professional mental health support available 24 hours a day. There is a need for a system that can comprehensively manage a wide range of elements, such as user authentication, data management, and the provision of appropriate support, and provide immediate and effective support. Furthermore, when referral to a specialist is necessary, a system is also needed to ensure smooth referrals.

[1380] 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.

[1381] In this invention, the server includes means for receiving user authentication information and verifying it based on a database, means for generating a session ID and notifying the user if the user authentication is successful, means for generating a conversational bot using a generative AI model based on user data and setting an optimal conversation scenario, means for saving a conversation log between the conversational bot and the user in real time so that it can be analyzed later, and means for analyzing the conversation log and suggesting a referral to a specialist if necessary. This realizes online mental health support available 24 hours a day, allowing users to receive immediate and effective mental health care.

[1382] "Authentication Information" means the username, password, or other means of authentication used by a User to access a System.

[1383] "Database" refers to a system that stores user authentication information and past data and performs verification and reference as needed.

[1384] "Session ID" refers to an identifier that is generated by the server after a user has been successfully authenticated and that uniquely identifies the user's session.

[1385] A "generative AI model" refers to an artificial intelligence model that generates appropriate dialogue scenarios based on user data.

[1386] A "conversational bot" refers to a chatbot built on a generative AI model to engage in dialogue with users.

[1387] A "dialogue scenario" refers to a series of appropriate dialogue content presented by a generative AI model in a dialogue with a user.

[1388] A "conversation log" refers to the history of messages exchanged between a conversational bot and a user.

[1389] "Professional referral" refers to the process of referring a user to a professional mental health care provider, if necessary.

[1390] "Real-time" refers to the system's ability to interact with and process users instantly.

[1391] This invention provides a 24-hour online mental health support system using an AI chatbot. This system provides immediate and effective mental health support to users by linking the user, terminal, and server components.

[1392] Server Roles

[1393] The server plays a central role in this system. First, it receives the authentication information sent by the user from the device and checks it against a database. Databases such as MySQL or PostgreSQL are typically used. Once the user is authenticated, the server generates a session ID and sends it to the device to start the session. The session ID is usually generated as a UUID (Universally Unique Identifier). The server then generates a conversational bot based on the user data using a generative AI model. OpenAI's GPT-4 is one example of a generative AI model. This conversational bot sets an optimal conversation scenario based on the user's past stress level and conversation log. Furthermore, the server saves the conversation log between the user and the conversational bot in real time and manages it as data for later analysis. Storage services such as Amazon S3 and Google Cloud Storage can be used.

[1394] Device Role

[1395] The terminal provides an interface that connects the user and the server. When the user starts the application, an authentication information input screen is displayed. The user enters their username and password here. Once the input is complete, the terminal sends it to the server. When the server returns a session ID, the terminal initializes the session and displays a chat interface to the user. When the user enters a message, the terminal sends it to the server, receives a response message from the server in real time, and displays it to the user.

[1396] User operations

[1397] To use this system, users first access the application from their device. After entering their authentication information on the login screen and pressing the login button, the server performs authentication. If authentication is successful, the user is redirected to a chat interface. Here, the user inputs their stress and worries and receives appropriate advice from a conversational bot using a generative AI model. If necessary, the user can also be referred to an expert.

[1398] Specific examples

[1399] For example, a user might type, "I'm feeling stressed at work." The device then sends this message to the server. The server uses a generative AI model to generate a response, asking, "What specifically is causing you stress?" If the user types, "A particular project is putting a lot of pressure on me," the conversational bot might suggest, "Would you like us to provide you with specific support or resources to help with the progress of this project?" This entire conversation takes place in real time, and the server stores the conversation log, continuously tracking the user's mental health status. If necessary, the server can smoothly refer the user to a specialist.

[1400] Prompt Sentence Examples

[1401] "I'm stressed about a particular work issue. What specifically is causing it? And what specific solutions do you suggest for that issue?"

[1402] As described above, the present invention provides immediate and effective support for the user's mental health care.

[1403] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1404] Step 1:

[1405] The user launches the application and enters their authentication information (username and password).

[1406] Input: Username and Password

[1407] How it works: A user accesses a login screen on their device and enters their credentials.

[1408] Output: The entered credentials

[1409] Step 2:

[1410] The terminal sends the user's authentication information to the server.

[1411] Input: Authentication information (username and password)

[1412] How it works: The device sends authentication information to the server using an HTTP POST request.

[1413] Output: Authentication information sent to the server

[1414] Step 3:

[1415] The server checks the credentials against a database and authenticates the user.

[1416] Input: Credentials

[1417] What happens: The server queries a database (e.g. MySQL, PostgreSQL) and matches the credentials. If successful, the user is authenticated.

[1418] Output: User authentication result (success or failure)

[1419] Step 4:

[1420] When authentication is successful, the server generates a session ID and notifies the terminal.

[1421] Input: Authentication result (success)

[1422] How it works: If authentication is successful, the server generates a session ID as a unique UUID and sends it to the device.

[1423] Output: Session ID

[1424] Step 5:

[1425] The terminal receives the session ID and initializes the session.

[1426] Input: Session ID

[1427] Behavior: The terminal uses the received session ID to initialize the session and displays a login success screen to the user.

[1428] Output: Session initialized

[1429] Step 6:

[1430] The server obtains the user's past data (stress level, conversation log) and generates a conversational bot using a generative AI model.

[1431] Input: Session ID, User Data

[1432] How it works: The server retrieves the user's past data from the database and sets the parameters of a generative AI model (e.g., GPT-4) to generate a conversational bot.

[1433] Output: The generated conversational bot

[1434] Step 7:

[1435] The server generates an initial message for the conversational bot and sends it to the terminal.

[1436] Input: Generated conversational bot, user data

[1437] How it works: The server launches the conversational bot, generates an initial question or message, and sends it to the user.

[1438] Output: Initial message

[1439] Step 8:

[1440] The device receives the initial message and displays it in the chat interface.

[1441] Input: initial message

[1442] Behavior: The terminal displays the initial message it receives in the chat interface.

[1443] Output: Initial message displayed

[1444] Step 9:

[1445] The user inputs their stress and worries into a chat interface.

[1446] Input: Details of stress and worries

[1447] How it works: The user enters their stress and worries and presses the send button.

[1448] Output: The input message

[1449] Step 10:

[1450] The terminal sends the user's message to the server.

[1451] Input: The message entered

[1452] Operation: The terminal sends the user's message to the server.

[1453] Output: Message sent to the server

[1454] Step 11:

[1455] The server generates a response message using a generative AI model based on the user's message.

[1456] Input: User message, generative AI model

[1457] How it works: The server parses the user's message and uses a generative AI model to generate an appropriate response message.

[1458] Output: Response message

[1459] Step 12:

[1460] The server sends a response message to the terminal.

[1461] Input: Response message

[1462] Operation: The server sends the generated response message to the terminal.

[1463] Output: Response message sent to the terminal

[1464] Step 13:

[1465] The terminal receives the response message and displays it to the user.

[1466] Input: Response message

[1467] Behavior: The device displays the received reply message in the chat interface.

[1468] Output: The displayed response message

[1469] Step 14:

[1470] The server stores the conversation log between the user and the conversational bot in real time.

[1471] Input: User's message, reply message

[1472] How it works: The server stores all messages between users and conversational bots in a database.

[1473] Output: Saved conversation logs

[1474] Step 15:

[1475] The server analyzes the conversation log and suggests referrals to experts if necessary.

[1476] Input: conversation log

[1477] How it works: The server analyzes the saved conversation logs and, if it determines that a referral to an expert is necessary, makes such a suggestion to the user.

[1478] Output: Referral message if necessary

[1479] The above is the flow of processing of the program of this system.

[1480] (Application example 1)

[1481] 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."

[1482] Conventional mental health care systems often delay providing appropriate support for users' stress and worries. Furthermore, in brick-and-mortar stores, it can be difficult for staff to constantly respond to customers, which can lead to a decline in customer satisfaction. To solve these problems, a fast and effective customer support system is needed, but current technology does not provide a sufficient solution.

[1483] 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.

[1484] In this invention, the server includes means for receiving user authentication information and verifying it based on a database, means for generating a session ID and notifying the user if the user authentication is successful, means for generating an AI chatbot using a generative AI model based on user data and setting an optimal dialogue scenario, means for saving a conversation log between the chatbot and the user in real time for later analysis, and means for the generated dialogue scenario to include responses generated based on prompt sentences intended for customer support in a physical store. This enables effective mental health care for users and prompt and appropriate customer support in a physical store.

[1485] "Authentication information" refers to information used by a user when logging in to a system, such as a user name and password.

[1486] A "database" is a system for organizing and managing a wide variety of data, and is a place where user authentication information, conversation logs, etc. are stored.

[1487] "Session ID" means a unique identifier generated after successful user authentication to identify an interactive session between a particular user and a system.

[1488] A "generative AI model" is an algorithm that uses artificial intelligence techniques to design a conversational interface based on user data.

[1489] An "AI chatbot" is a program that uses artificial intelligence to automatically generate responses to users' questions and inquiries.

[1490] A "dialogue scenario" refers to a series of scenes and responses that define the flow and content when an AI chatbot converses with a user.

[1491] A "conversation log" is data that records the content of the conversation between a user and an AI chatbot, and is saved in a format that can be analyzed later.

[1492] A "prompt" is a piece of text or phrase that serves as a starting point for a generative AI model to generate a specific response.

[1493] A "brick and mortar store" refers to a retail or service establishment that has a physical presence in a physical location where face-to-face commerce with customers takes place.

[1494] "Customer support" refers to the activity of providing assistance to customers to respond to and resolve questions or problems that arise when using a product or service.

[1495] "Referral to an expert" refers to connecting the user to a person or department with specialized knowledge if the AI ​​chatbot determines this is necessary through dialogue.

[1496] This invention relates to an AI chatbot system for customer support in brick-and-mortar stores. This system involves user, terminal, and server components interacting with each other to provide instant and effective question responses and support to users.

[1497] Server Roles

[1498] The server plays a central role in this system. Its functions are realized by the following procedure.

[1499] 1. Receiving and verifying authentication information

[1500] The server receives the authentication information sent by the user from the terminal and compares it with the database. If the authentication is successful, the server generates a session ID and notifies the user terminal.

[1501] 2. Use of generative AI models

[1502] The AI ​​chatbot is generated using a generative AI model based on user data and the optimal dialogue scenario is set up. Specifically, prompts are prepared based on the user's past inquiry history and stress level, and the chatbot's responses are generated.

[1503] 3. Save conversation logs

[1504] The conversation log between the chatbot and the user is saved in real time and can be analyzed later. This allows us to understand user behavior patterns and problems, leading to further improvements to the service.

[1505] Hardware used: Server

[1506] Software used: Generative AI models, database management system

[1507] Device Role

[1508] The terminal provides an interface between the user and the server.

[1509] 1. Enter and submit authentication information

[1510] When a user launches an application, a screen for entering authentication information appears. The user enters the authentication information, and the device sends it to the server.

[1511] 2. Displaying the chat interface

[1512] Once the server returns a session ID, the terminal initializes the session and displays a chat interface to the user. When the user enters a message, the terminal sends it to the server, receives a response message from the server, and displays it to the user.

[1513] Hardware used: smartphone, tablet

[1514] Software used: Front-end application (e.g., Flutter, React Native)

[1515] User operations

[1516] To use this system, a user first accesses the application from their device and enters their authentication information on the login screen. After successful authentication, the user is redirected to a chat interface. Here, the user enters their question or concern and receives appropriate advice or a response from the AI ​​chatbot. For example, if a user enters "I'd like to know more about this product," this message is sent to the server via the device, and the server uses a generative AI model to generate a response. An example of a prompt for the generated response is "User: "I'd like to know more about this product"\nAI:". Based on this prompt, the AI ​​chatbot returns a detailed answer such as: "Of course. This product is made of high-quality materials and has the following features..."

[1517] This entire dialogue is conducted in real time, and the server stores the conversation log, allowing for continuous tracking of the user's behavior and needs. If necessary, the user can be smoothly referred to an expert. This improves the customer experience in physical stores and makes it possible to provide high-quality customer support.

[1518] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1519] Step 1:

[1520] A user starts an application from a terminal and enters authentication information (user name and password). The terminal sends this authentication information to the server. The input is the username and password, and the output is the authentication information sent.

[1521] Step 2:

[1522] The server compares the received authentication information with a database. The operation involves running a database query to determine whether the user is valid. The input is the username and password, and the output is the authentication result. If authentication is successful, the server generates a session ID and notifies the terminal.

[1523] Step 3:

[1524] The terminal initializes the session using the session ID received from the server. This ensures that only authenticated users can use the chat interface. The input is the session ID, and the output is session initialization.

[1525] Step 4:

[1526] The user inputs a question or concern into the chat interface. The terminal sends this message to the server. The input is the user's message, and the output is the message sent.

[1527] Step 5:

[1528] The server uses a generative AI model to create a prompt sentence to generate a response based on the received user message. The inputs are the user message, user data, and past conversation logs, and the output is the generated prompt sentence. Specific operation involves generating an example prompt sentence: "User: 'I'd like to know more about this product'\nAI:".

[1529] Step 6:

[1530] The server uses a generative AI model to generate a response based on the prompt. The input is the prompt, and the output is the generated AI chatbot's response. The generated response is sent from the server to the device.

[1531] Step 7:

[1532] The terminal receives a response message from the server and displays it to the user. The input is the generated AI chatbot's response, and the output is the response displayed to the user. This allows the user to obtain an appropriate answer to their question or concern.

[1533] Step 8:

[1534] The server stores the conversation log between the chatbot and the user in real time for later analysis. The input is the content of the conversation, and the output is the saved conversation log. Operations include writing the conversation log to the database.

[1535] Step 9:

[1536] If necessary, the server can refer the user to an expert. The input is the user's problem and the analysis results, and the output is a referral suggestion to an expert. Specific actions can include providing the expert's contact information or inviting the user to chat directly.

[1537] 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.

[1538] This invention combines an online mental health support system using an AI chatbot that is available 24 hours a day with an emotion engine that recognizes the user's emotions. This system provides immediate and effective mental health support to users by linking the user, device, server, and emotion engine components.

[1539] Server Roles

[1540] The server plays a central role in the system. First, it receives authentication information sent by the user and verifies the user's identity by checking it against a database. If authentication is successful, it generates a session ID and sends it to the device to start the session. Next, the server generates an AI chatbot based on the user data. This AI chatbot sets an optimal dialogue scenario based on the user's past stress level and conversation logs. Furthermore, it uses an emotion engine to analyze emotions from the user's input messages and past dialogue logs, and dynamically adjusts the dialogue scenario based on the user's emotions. In addition, the server saves the conversation logs and emotion data between the user and the AI ​​chatbot in real time and manages them as data for later analysis.

[1541] Device Role

[1542] The terminal provides an interface that connects the user and the server. When the user launches the application, an authentication information input screen is displayed and the user enters their authentication information. The terminal sends that information to the server, and upon receiving a session ID from the server, initializes the session. Next, the terminal receives the chatbot data sent from the server and displays a user-friendly chat interface. When the user enters a message, the terminal sends that message to the server and waits for a response. After receiving the response message from the server, the terminal displays it to the user.

[1543] User operations

[1544] Users access the application using a smartphone or PC and log in by entering their authentication information. Once authentication is successful, the user is redirected to a chat interface where they can enter their stress and worries and receive a response from the AI ​​chatbot. An emotion engine analyzes the user's emotions, and the AI ​​chatbot provides optimal advice and solutions based on those emotions. If necessary, the user can be referred to an expert.

[1545] Specific examples

[1546] For example, consider a situation where a user types, "Work has been really hard lately." The user's message is sent from the device to the server, and the server uses an emotion engine to analyze the emotion from the user's message content. The emotion engine detects that the user is feeling stressed and identifies the emotion "hard." The AI ​​chatbot generates a response based on this emotion. The chatbot asks the user, "That must be really hard. What specifically is causing you hardship?" and provides specific advice through dialogue. If the user replies, "I'm feeling pressured because the project progress is not going well," the chatbot suggests, "Can I introduce you to some tools or support to help you manage the project progress?" This allows the user to find a specific solution.

[1547] This system allows users to receive effective mental health support in real time, 24 hours a day. By combining it with an emotion engine, it is possible to accurately grasp the user's emotions and provide more appropriate responses. This allows for immediate and effective support in the user's mental health care.

[1548] The processing flow will be explained below.

[1549] Server Processing Steps

[1550] Step 1:

[1551] Server receives authentication information (user ID and password) sent by the user.

[1552] Step 2:

[1553] The server queries the database for authentication information and checks whether the corresponding user exists.

[1554] Step 3:

[1555] If the user exists, the server generates a session ID and sends it to the terminal along with a response indicating successful authentication.

[1556] Step 4:

[1557] For users who are successfully authenticated, the server generates an AI chatbot based on the user data.

[1558] Step 5:

[1559] The server sets up the optimal dialogue scenario based on user data and applies it to the AI ​​chatbot.

[1560] Step 6:

[1561] The server runs an emotion engine to analyze emotions from user input messages and past dialogue logs.

[1562] Step 7:

[1563] Based on the emotional information analyzed by the emotion engine, the server dynamically adjusts the dialogue scenario.

[1564] Step 8:

[1565] The server generates responses for the AI ​​chatbot based on the adjusted dialogue scenario.

[1566] Step 9:

[1567] Conversation logs and emotional data between users and AI chatbots are saved in real time and managed as data for later analysis.

[1568] Terminal processing steps

[1569] Step 1:

[1570] The terminal displays a screen for the user to input authentication information.

[1571] Step 2:

[1572] When the user inputs the authentication information and presses the send button, the terminal sends the authentication information to the server.

[1573] Step 3:

[1574] When the server returns the session ID, the terminal initializes the session.

[1575] Step 4:

[1576] The terminal receives the chatbot data sent from the server and displays a user-friendly chat interface.

[1577] Step 5:

[1578] When the user enters a message, the terminal sends the message to the server and waits for a response.

[1579] Step 6:

[1580] The terminal that receives the response message from the server displays it to the user.

[1581] User operation steps

[1582] Step 1:

[1583] The user accesses the application using a smartphone or PC and enters authentication information (user ID and password).

[1584] Step 2:

[1585] The user presses the login button to request authentication from the server.

[1586] Step 3:

[1587] Upon successful authentication, the user is redirected to the chat interface.

[1588] Step 4:

[1589] Users input their stress and worries into a chat interface.

[1590] Step 5:

[1591] The user receives a response from the AI ​​chatbot and checks the advice and solutions displayed.

[1592] Step 6:

[1593] Users input detailed information in response to follow-up questions and suggestions from the AI ​​chatbot.

[1594] Step 7:

[1595] Accept expert referrals suggested by the AI ​​chatbot when needed.

[1596] Example 2

[1597] 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."

[1598] Conventional online mental health support systems have had difficulty accurately recognizing users' emotions and providing appropriate dialogue and advice based on those emotions. It has also been difficult to provide user support 24 hours a day. This has resulted in an inability to respond appropriately to users' emotions, limiting the effectiveness of mental health care.

[1599] 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.

[1600] In this invention, the server includes means for receiving user authentication information and verifying it based on a database, means for generating a session ID and notifying the user if the user authentication is successful, means for generating a dialogue agent based on user data and setting an optimal dialogue scenario, means for analyzing user input messages in real time using emotion analysis means and dynamically adjusting the dialogue scenario based on the emotions, and means for saving a conversation log between the dialogue agent and the user in real time so that it can be analyzed later. This makes it possible to accurately grasp the user's emotions and provide appropriate and timely dialogue and advice based on them.

[1601] "User authentication information" refers to the identification information (e.g., user ID and password) that a user enters to log in to a system.

[1602] A "database" is an information storage system for systematically storing and managing information such as user authentication information and past interaction logs.

[1603] A "session ID" is a unique identifier issued to a user who has been successfully authenticated and is used to track and manage the session.

[1604] A "conversational agent" is an artificial intelligence model created to converse with users, and has the ability to provide appropriate dialogue based on the user's past data and emotional analysis.

[1605] "Emotion analysis means" is a technology for extracting emotional information from a user's input message and generating appropriate dialogue scenarios and responses based on that information.

[1606] A "dialogue scenario" defines a series of topics and question sequences that a dialogue agent uses in conversation with a user, and is dynamically adjusted according to the user's situation and emotions.

[1607] A "conversation log" is a record of all interactions between a user and a conversational agent, which can be analyzed and referenced later.

[1608] This invention combines an online mental health support system using an AI chatbot that is available 24 hours a day with an emotion engine that recognizes the user's emotions. This system provides immediate and effective mental health support to users by linking the user, terminal, server, and emotion engine components. A detailed explanation of how to implement this system is provided below.

[1609] Server Roles

[1610] The server plays a central role in the system. First, it receives authentication information sent by the user and verifies the user's identity by checking it against a database. If authentication is successful, it generates a session ID and sends it to the terminal to start the session. Next, the server generates a dialogue agent based on the user data. This dialogue agent sets an optimal dialogue scenario based on the user's past stress level and conversation log. Furthermore, it uses emotion analysis means to analyze emotions from the user's input messages and past dialogue logs, and dynamically adjusts the dialogue scenario based on the user's emotions. In addition, the server saves the dialogue logs and emotion data of the user and dialogue agent in real time and manages them as data for later analysis.

[1611] Device Role

[1612] The terminal provides an interface that connects the user and the server. When the user launches an application, an authentication information entry screen appears and the user enters their authentication information. The terminal sends that information to the server, and upon receiving a session ID from the server, initializes the session. Next, the terminal receives the conversation agent data sent from the server and displays a user-friendly chat interface. When the user enters a message, the terminal sends that message to the server and waits for a response. After receiving the response message from the server, the terminal displays it to the user.

[1613] User operations

[1614] Users access the application using a smartphone or PC and log in by entering their authentication information. Once authentication is successful, the user is redirected to a chat interface, where they can enter their stress and worries and receive a response from a conversational agent. An emotion analysis means analyzes the user's emotions, and the conversational agent provides optimal advice and measures based on those emotions. If necessary, the user can be referred to an expert.

[1615] Hardware and software used

[1616] The hardware used will be a high-performance database and a server machine with processing power. Specifically, cloud service providers (e.g., AWS, Google Cloud Platform) can be used. Normal smartphones and PCs are expected to be used as devices. Software used will likely include emotion analysis technology for emotion analysis and a generative AI model (e.g., GPT-3) for the dialogue agent.

[1617] Examples of concrete examples and prompts

[1618] For example, consider a situation where a user types, "Work has been really hard lately." In this case, the user's message is sent from the terminal to the server, and the server uses emotion analysis means to analyze the emotion from the content of the user's message. The emotion analysis means detects that the user is feeling stressed and identifies the emotion "hard." The dialogue agent generates a response based on this emotion. The dialogue agent asks the user, "That must be really hard. What specifically is causing you to feel hard?" and provides specific advice through dialogue. If the user answers, "I'm feeling pressured because the project progress is not going well," the dialogue agent suggests, "Would you like me to introduce you to some tools or support to help you manage the project progress?" This allows the user to obtain a specific solution.

[1619] Below is an example of a prompt sentence to input to the generative AI model.

[1620] "You are a conversational agent. Your role is to understand the message entered by the user and provide an appropriate response based on the user's sentiment. Below is the user's message and the result of sentiment analysis:

[1621] User message: 'Work has been really hard lately'

[1622] Sentiment analysis: 'Stressful, painful'

[1623] Based on this, generate an appropriate response for the user."

[1624] This system allows users to receive effective mental health support in real time, 24 hours a day. By combining it with emotion analysis methods, it is possible to accurately grasp the user's emotions and provide more appropriate responses. This allows for immediate and effective support in the user's mental health care.

[1625] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1626] Step 1:

[1627] Authenticating Users

[1628] The user starts an application and enters authentication information (user ID and password). The entered authentication information is sent from the terminal to the server. The server receives the authentication information and checks it against a database to verify that it is a valid user. For example, if the authentication information "user name: john_doe, password: password123" is entered, the server checks it against the database. If authentication is successful, the server generates a session ID "abc123" and sends it to the terminal.

[1629] Input: User authentication information (user ID, password)

[1630] Output: Session ID

[1631] Specific operation: When the user enters authentication information and authentication is successful, the server generates a session ID and sends it to the terminal.

[1632] Step 2:

[1633] Initializing the session

[1634] The terminal starts a session using the session ID received from the server and displays a chat interface for the user. After receiving the session ID, the terminal displays the chat screen to the user, allowing the user to enter a message.

[1635] Input: Session ID

[1636] Output: Chat interface displayed

[1637] Specific actions: After receiving the session ID, the device will display the chat interface and allow the user to enter a message.

[1638] Step 3:

[1639] Generating a conversational agent

[1640] The server generates a dialogue agent based on user data. This dialogue agent sets up an optimal dialogue scenario based on the user's past stress level and conversation log. For example, a generative AI model can be used to create an optimal dialogue scenario based on the user profile.

[1641] Input: User data (past stress levels, conversation logs)

[1642] Output: A conversational agent

[1643] Specific operation: The server collects the user's past data and generates a dialogue agent using a generative AI model, while also setting the optimal dialogue scenario.

[1644] Step 4:

[1645] Receiving user messages

[1646] The user enters a message into the chat interface and presses the send button. The device then sends the message to the server. For example, the user enters "Work has been really hard lately," and the device sends this to the server.

[1647] Input: User message

[1648] Output: None (forwarding the message)

[1649] Specific operation: The terminal sends the message entered by the user to the server.

[1650] Step 5:

[1651] Emotion analysis

[1652] The server uses emotion analysis means to analyze the received user message and identify the emotion. For example, from the input message "Work has been really hard lately," the server identifies the emotion "stressed, hard."

[1653] Input: User message

[1654] Output: Emotional information

[1655] Specific operation: The server analyzes the input message and extracts emotional information.

[1656] Step 6:

[1657] Response Generation

[1658] Based on the results of emotion analysis, the dialogue agent generates an appropriate response. For example, if the user's emotion is "painful," the dialogue agent will generate a response such as, "That must be really hard. What specifically is causing you pain?"

[1659] Input: Emotion information, user data

[1660] Output: Response of the conversational agent

[1661] Specific operation: Based on the results of emotion analysis, the dialogue agent uses a generative AI model to generate an appropriate response.

[1662] Step 7:

[1663] Sending and Displaying Responses

[1664] The server then sends the generated response message to the terminal, which then displays it to the user. For example, the response generated by the conversational agent is "That's really hard. What specifically is causing you pain?", and the terminal displays it to the user.

[1665] Input: Response message from the conversation agent

[1666] Output: Display a message on the user's screen

[1667] Specific operation: The terminal receives the response message from the server and displays it to the user.

[1668] Step 8:

[1669] Save conversation logs

[1670] The server saves the conversation log between the user and the conversation agent and their emotional data in real time, and manages it as data for later analysis. For example, information such as "User message: Work has been really hard lately," "Emotion analysis: Stress, hard," and "Dialogue agent response: That's really hard. What specifically is causing you hardship?" is recorded in the database.

[1671] Input: Conversation logs and emotion data

[1672] Output: Saved data

[1673] Specific operation: The server stores conversation logs and emotion data in real time and manages them for later analysis.

[1674] (Application example 2)

[1675] 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."

[1676] As the importance of mental health care has increased in recent years, there is a growing need for systems that provide optimal mental health support and relaxation content according to the user's emotional state. Conventional mental health support systems have had the difficulty of analyzing a user's emotions in real time and individually recommending optimal content based on the results, making them unable to meet the diverse needs of users.

[1677] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user authentication information and verifying it based on a database, means for generating a session ID and notifying the user if user authentication is successful, means for generating an AI chatbot based on user data and setting an optimal dialogue scenario, means for saving a conversation log between the chatbot and the user in real time so that it can be analyzed later, and means for analyzing the user's emotional information and recommending optimal content based on the analysis results. This makes it possible to provide mental health support and relaxation content in real time that is tailored to the user's emotional state.

[1678] "User authentication information" is data used to identify a particular user and verify that the user is authorized to access a system.

[1679] A "database" is a system for efficiently storing, managing, and retrieving structured information.

[1680] A "session ID" is a unique identifier generated to identify a user's individual session.

[1681] An "AI chatbot" is a program that uses artificial intelligence to automate conversations with users.

[1682] A "dialogue scenario" is a plan that sets the flow and content of a dialogue with a user in advance.

[1683] A "conversation log" is data that records the interactions between a user and a chatbot.

[1684] "Emotion information" is data that expresses the user's emotional state.

[1685] "Emotion analysis" is the process of identifying a user's emotional state from words, facial expressions, etc.

[1686] "Content recommendation" is the act of suggesting optimal content based on a user's interests and emotional state.

[1687] An "input message" is text or voice data that a user sends to the system.

[1688] A "response message" is response data sent from a server or chatbot to a user.

[1689] A "viewing history" is a record of content that a user has viewed in the past.

[1690] "Analysis results" are the conclusions and findings obtained after conducting data analysis.

[1691] This invention is a 24-hour online mental health support system using an AI chatbot, combined with an emotion engine that recognizes and analyzes the user's emotions. This system is also capable of recommending optimal content in real time according to the user's emotional state. Below, we will explain how this system is implemented in detail.

[1692] Overall system structure

[1693] This system consists of a device used by the user, a central processing server, and an emotion engine that analyzes emotions. The device can be a smartphone, PC, tablet, etc., and is responsible for interacting with the user. The server processes data, generates AI chatbots, and sets up dialogue scenarios. The emotion engine then analyzes emotions from user input and provides optimal responses and content recommendations.

[1694] Program processing explanation

[1695] Authenticating a User and Starting a Session

[1696] 1. Device: The user accesses the application using a smartphone or PC and enters authentication information (user ID and password).

[1697] 2. Server: Receives the authentication information sent from the device and checks the database to verify the user's authenticity. If authentication is successful, generates a session ID and sends it to the device.

[1698] Creating an AI chatbot and setting up dialogue scenarios

[1699] 1. Server: Generates an AI chatbot based on user data and sets up optimal conversation scenarios. Individual scenarios are constructed taking into account data such as past conversation logs and stress levels.

[1700] Message sending and receiving and sentiment analysis

[1701] 1. Terminal: Receives input messages from the user and sends them to the server. For example, the user might input a message such as "Work has been really hard lately."

[1702] 2. Server: Passes the received message to the emotion engine for analysis. The emotion engine analyzes the user's emotion from the input message and identifies the emotional state, such as "stress" or "sadness."

[1703] Recommending content and continuing the conversation

[1704] 1. Server: Based on the sentiment analysis, the recommendation engine selects the most suitable content, such as relaxing music or a guided meditation video.

[1705] 2. Terminal: Displays the content recommendation list sent from the server to the user and plays the content selected by the user.

[1706] Examples of concrete examples and prompts

[1707] Specific examples

[1708] If the user types "Work has been really hard lately," the system will do the following:

[1709] 1. The user's message is sent from the device to the server.

[1710] 2. The server uses the emotion engine to identify the user's emotional state as "stress."

[1711] 3. Based on the results of the emotion analysis, the AI ​​chatbot asks, "That must be really tough. What specifically is causing you distress?"

[1712] 4. At the same time, it also recommends music playlists that have a relaxing effect.

[1713] Prompt Sentence Examples

[1714] The prompt to analyze the sentiment of the input "tired" is as follows:

[1715] User Input: I'm tired

[1716] Emotional state: stress, fatigue

[1717] Recommended content: Relaxation music, meditation videos

[1718] In this way, mental health support and content recommendations can be provided that are tailored to the user's emotional state, enhancing the user's experience.

[1719] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1720] Step 1:

[1721] A user accesses an application using a smartphone or PC and enters authentication information (user ID and password). The authentication information is obtained as input data. This authentication information is then sent from the device to the server.

[1722] Step 2:

[1723] The server compares the authentication information received from the terminal with a database to confirm whether the user is a legitimate user. The data processing performed here is to compare the authentication information, and the output is the result of authentication success or failure. If authentication is successful, the server generates a session ID and sends it to the terminal.

[1724] Step 3:

[1725] If the user is successfully authenticated, the terminal initializes the session using the session ID received from the server, allowing the user to log in to the system and prepare for the next operation.

[1726] Step 4:

[1727] The user inputs a message related to stress or emotion and sends it from the terminal to the server. The input data here is the user's message, and the output is the data sent to the server.

[1728] Step 5:

[1729] The server passes the user's input message to the emotion engine for emotion analysis. The emotion engine uses a generative AI model to analyze the emotional state (e.g., stress, fatigue) from the input message. The input is the user's message, and the output is the analyzed emotion data.

[1730] Step 6:

[1731] The server sets the optimal dialogue scenario based on the analysis results of the emotion engine and generates an AI chatbot. Here, data processing is performed to set the dialogue scenario using emotion data, and the optimized dialogue scenario is obtained as the output.

[1732] Step 7:

[1733] The server generates content recommendation results according to the user's emotional state. Specifically, the recommendation engine uses the emotion analysis results as prompts to suggest appropriate content (music, videos, guided meditations, etc.). The input is the emotion analysis results, and the output is a list of recommended content.

[1734] Step 8:

[1735] The terminal displays the content recommendation results received from the server to the user and plays the content selected by the user. Here, the content recommendation results are obtained as input, and the output is content information displayed to the user. The user can select content and start playing it.

[1736] Step 9:

[1737] The server stores the conversation log between the chatbot and the user, as well as the user's viewing history, in real time. It then performs big data analysis and manages the data to provide more accurate support in the future. The input is the conversation log and viewing history, and the output is an analyzable database entry.

[1738] 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.

[1739] 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.

[1740] 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.

[1741] 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.

[1742] 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.

[1743] 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.

[1744] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1745] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1746] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1747] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1748] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1749] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1750] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1751] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1752] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1753] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1754] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1755] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1756] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1757] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1758] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1759] The following is further disclosed regarding the above embodiment.

[1760] (Claim 1)

[1761] means for receiving and verifying user authentication information against a database;

[1762] A means for generating a session ID and notifying the user if the user is successfully authenticated;

[1763] A means to generate an AI chatbot based on user data and set the optimal dialogue scenario,

[1764] A means for saving conversation logs between the chatbot and the user in real time and enabling later analysis;

[1765] A system including:

[1766] (Claim 2)

[1767] means for receiving input messages from a user and sending them to a server;

[1768] means for receiving a response message from the server and displaying it to the user;

[1769] means for transmitting the authentication information entered by the user to a server;

[1770] a means for initializing a session after receiving a session ID;

[1771] 10. The system of claim 1, comprising:

[1772] (Claim 3)

[1773] The AI ​​chatbot analyzes the stress and worries entered by the user and provides the most appropriate advice and response.

[1774] A means to suggest specialist referrals when necessary;

[1775] 10. The system of claim 1, comprising:

[1776] "Example 1"

[1777] (Claim 1)

[1778] means for receiving and verifying user authentication information against a database;

[1779] A means for generating a session ID and notifying the user if the user is successfully authenticated;

[1780] A means for generating a conversational bot using a generative AI model based on user data and setting the optimal conversation scenario;

[1781] A means for saving a conversation log between a conversation bot and a user in real time for later analysis;

[1782] A means to analyze conversation logs and suggest referrals to experts if necessary,

[1783] A system including:

[1784] (Claim 2)

[1785] means for receiving input messages from a user and sending them to a server;

[1786] means for receiving a response message from the server and displaying it to the user;

[1787] means for transmitting the authentication information entered by the user to a server;

[1788] a means for initializing a session after receiving a session ID;

[1789] 10. The system of claim 1, comprising:

[1790] (Claim 3)

[1791] The AI ​​model analyzes the stress and worries entered by the user and provides optimal advice and responses.

[1792] [The system of claim 1].

[1793] "Application Example 1"

[1794] (Claim 1)

[1795] means for receiving and verifying user authentication information against a database;

[1796] A means for generating a session ID and notifying the user if the user is successfully authenticated;

[1797] A means for generating an AI chatbot using a generative AI model based on user data and setting up optimal dialogue scenarios;

[1798] A means for saving conversation logs between the chatbot and the user in real time and enabling later analysis;

[1799] A means for generating a dialogue scenario including a response generated based on a prompt sentence intended to support customers in a physical store;

[1800] A system including:

[1801] (Claim 2)

[1802] means for receiving input messages from a user and sending them to a server;

[1803] means for receiving a response message from the server and displaying it to the user;

[1804] means for transmitting the authentication information entered by the user to a server;

[1805] a means for initializing a session after receiving a session ID;

[1806] A means of providing customer support in a physical store on a device such as a smartphone;

[1807] 10. The system of claim 1, comprising:

[1808] (Claim 3)

[1809] The AI ​​chatbot analyzes the stress and worries entered by the user and provides the most appropriate advice and response.

[1810] A means to suggest specialist referrals when necessary;

[1811] A way to quickly respond to customer questions in-store and connect them to expert staff when needed;

[1812] 10. The system of claim 1, comprising:

[1813] "Example 2: Combining Emotion Engines"

[1814] (Claim 1)

[1815] means for receiving and verifying user authentication information against a database;

[1816] A means for generating a session ID and notifying the user if the user is successfully authenticated;

[1817] A means for generating a dialogue agent based on user data and setting an optimal dialogue scenario;

[1818] a means for analyzing a user's input message in real time using an emotion analysis means and dynamically adjusting a dialogue scenario based on the emotion;

[1819] a means for saving a conversation log between the dialogue agent and the user in real time for later analysis;

[1820] A system including:

[1821] (Claim 2)

[1822] means for receiving input messages from a user and sending them to a server;

[1823] means for receiving a response message from the server and displaying it to the user;

[1824] means for transmitting the authentication information entered by the user to a server;

[1825] a means for initializing a session after receiving a session ID;

[1826] 10. The system of claim 1, comprising:

[1827] (Claim 3)

[1828] A conversational agent analyzes the stress and worries entered by the user and provides optimal advice and responses.

[1829] A means to suggest specialist referrals when necessary;

[1830] 10. The system of claim 1, comprising:

[1831] "Application example 2 when combining emotion engines"

[1832] (Claim 1)

[1833] means for receiving and verifying user authentication information against a database;

[1834] A means for generating a session ID and notifying the user if the user is successfully authenticated;

[1835] A means to generate an AI chatbot based on user data and set the optimal dialogue scenario,

[1836] A means for saving conversation logs between the chatbot and the user in real time and enabling later analysis;

[1837] A means for analyzing user emotional information and recommending optimal content based on the analysis results;

[1838] A system including:

[1839] (Claim 2)

[1840] means for receiving input messages from a user and sending them to a server;

[1841] means for receiving a response message from the server and displaying it to the user;

[1842] means for transmitting the authentication information entered by the user to a server;

[1843] a means for initializing a session after receiving a session ID;

[1844] means for displaying content recommendation results to a user and playing content selected by the user;

[1845] 10. The system of claim 1, comprising:

[1846] (Claim 3)

[1847] The AI ​​chatbot analyzes the stress and worries entered by the user and provides the most appropriate advice and response.

[1848] A means to suggest specialist referrals when necessary;

[1849] means for storing a viewing history of content recommended based on the user's emotional state for later analysis;

[1850] 10. The system of claim 1, comprising: [Explanation of symbols]

[1851] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving and verifying user authentication information against a database; A means for generating a session ID and notifying the user if the user is successfully authenticated; A means to generate an AI chatbot based on user data and set the optimal dialogue scenario, A means for saving conversation logs between the chatbot and the user in real time and enabling later analysis; A system including:

2. means for receiving input messages from a user and sending them to a server; means for receiving a response message from the server and displaying it to the user; means for transmitting the authentication information entered by the user to a server; a means for initializing a session after receiving a session ID; The system of claim 1 , comprising:

3. The AI ​​chatbot analyzes the stress and worries entered by the user and provides the most appropriate advice and response. A means to suggest specialist referrals when necessary; The system of claim 1 , comprising:

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