system

Abstract

We provide the system. [Solution] A means of receiving mood and environmental data from users, A means for analyzing received data and generating alternative activities for the user, A means of presenting the generated alternative activity to the user, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] The present invention relates to a system for assisting users in avoiding health hazards caused by alcohol consumption. In particular, it aims to promote a healthy lifestyle by providing beneficial alternative activities and community functions for users who are at risk of alcohol dependence to refrain from drinking. Also, compared with conventional alcohol countermeasure systems, it is an issue that personalized proposals can be made according to individual situations.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides a system that includes the following means: means for receiving mood and environmental data from the user; means for analyzing the received data and generating alternative activities for the user; and means for presenting the generated alternative activities to the user. The system further includes means for providing a community function for collaborating and interacting with other users who have similar concerns, and means for collecting biometric data in conjunction with a smartwatch and generating alternative activities based on that biometric data. In this way, the system helps users suppress their desire to drink alcohol in a healthy manner.

[0006] "User" refers to an individual who uses this system.

[0007] "Mood and environmental data" refers to information about the psychological or physical conditions that users experience in their daily lives. This includes, for example, stress levels and events of the day.

[0008] "Means of receiving" refers to technical methods or devices that acquire information entered by users and store it within the system.

[0009] "Means of analysis" refers to technologies that use algorithms and generative AI models to analyze information based on received data and derive meaningful results.

[0010] "Means for generating alternative activities" refers to technical methods or devices that generate activities or actions to suggest to users based on the results of analysis. Examples include online yoga sessions or suggestions for new hobbies.

[0011] "Means of presentation" refers to the technical methods or devices that communicate the generated alternative activity to the user. This is typically done through a smartphone display or notification mechanism.

[0012] "Community features" refer to online platforms and tools for connecting and interacting with other users who share similar concerns. This includes chat and forums.

[0013] A "smartwatch" is a wearable device that collects and displays the user's biometric information and activity data in real time.

[0014] "Biometric data" refers to physiological data such as the user's heart rate, stress level, and body temperature.

[0015] A "suggestion" refers to a recommendation that outlines feasible alternative activities or measures for users, based on the analysis results. [Brief explanation of the drawing]

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

Mode for Carrying Out the Invention

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

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

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

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

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

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

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

[0024] [First Embodiment]

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

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

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

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

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

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

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

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

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

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

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

[0037] This invention relates to a system that provides users with beneficial alternative activities and community features to help them avoid health problems caused by alcohol consumption. This system is primarily implemented by combining a user terminal (smartphone application), a server, and a generative AI model.

[0038] User device (smartphone app)

[0039] The user device will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[0040] 1. User registration and login function

[0041] Users: When launching the app for the first time, create an account by entering basic information such as your name, email address, and drinking frequency. If you already have an account, access it using the login function.

[0042] 2. Data Input Interface

[0043] User: Uses an interface to input data about daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[0044] 3. Receiving and displaying proposals

[0045] Terminal: Receives suggestions from the generating AI model and displays them to the user. For example, it might suggest specific activities such as "Join an online yoga session" or "Watch a new movie."

[0046] 4. Community Features

[0047] Users can utilize community features that allow them to interact with other users who share similar concerns. Information exchange and support are provided through chat and forums.

[0048] 5. Integration with smartwatches

[0049] Device: It works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current state in real time and suggests appropriate activities.

[0050] Server-side functionality

[0051] The server will be implemented as a cloud-based system with the following functions:

[0052] 1. User data management

[0053] Server: Manages user account information, daily input data, requests to the generated AI model, etc.

[0054] 2. Communication with the Generative AI Model

[0055] Server: Receives data sent from users and sends requests to the generated AI model to perform analysis and make suggestions.

[0056] 3. Managing Community Features

[0057] Server: Manages community functions, including sending and receiving messages and running forums. Also filters spam and inappropriate content.

[0058] Generative AI Models

[0059] The generative AI model will be implemented as an artificial intelligence system with the following functions:

[0060] 1. Data Analysis

[0061] Generative AI Model: Analyzes received user data and generates alternative activities suitable for the user's mood and environment on that day.

[0062] 2. Proposal generation

[0063] Generative AI Model: Based on the results of data analysis, it generates specific activity suggestions for the user. For example, if the user is experiencing high stress, it suggests relaxation methods; if the user has a strong urge to drink, it suggests alternative hobbies.

[0064] Specific example

[0065] 1. User Registration

[0066] User: Users download the app, enter their name, email address, and drinking frequency to register. The server receives this information and stores it in its database.

[0067] 2. Daily data entry

[0068] User: Enters their mood and circumstances for the day into the app. For example, they might enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." The device then sends this information to the server.

[0069] 3. Proposal generation and presentation

[0070] Server: Sends data to the generative AI model and requests suggestions. The generative AI model analyzes the data and generates specific activities such as "Join an online yoga session now" or "Watch a new movie."

[0071] Terminal: Receives suggestions and displays them to the user. The user can select and perform the suggested activities.

[0072] 4. Use of community features

[0073] Users interact with other users through chat and forums, sharing experiences and opinions. The server manages this.

[0074] 5. Integration with smartwatches

[0075] User: Wears a smartwatch and connects it to the app. The device collects heart rate and stress levels and sends them to the server. The generated AI model uses this data to make more specific suggestions.

[0076] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle.

[0077] The following describes the processing flow.

[0078] Step 1: User Registration

[0079] User: Launch the app for the first time and enter basic information such as name, email address, and daily drinking frequency.

[0080] Terminal: Sends the entered information to the server.

[0081] Server: Stores the received information in the database and returns a success message for account creation to the terminal.

[0082] Terminal: Displays a success message to the user.

[0083] Step 2: Data Entry

[0084] User: Enter information about your mood and environment for the day into the app. For example, you might report, "I'm feeling stressed today," or "I have a strong urge to drink."

[0085] Terminal: Sends the entered data to the server.

[0086] Server: Receives data and saves it to the database.

[0087] Step 3: Request analysis from the generative AI model

[0088] Server: Sends the stored data to the generating AI model for analysis. Specifically, it sends a POST request to the generating AI model.

[0089] Generative AI Model: Analyzes received data and generates optimal alternative activities for the user. For example, it can suggest online yoga sessions or movie viewings.

[0090] Generative AI model: Returns the generated suggestions to the server.

[0091] Step 4: Providing and displaying proposals

[0092] Server: Receives suggestions from the generated AI model and sends them to the user's terminal.

[0093] Device: Receives suggestions and displays them to the user. For example, it displays a link to "Online yoga sessions you can join now" on the app's home screen.

[0094] Step 5: Utilizing Community Features

[0095] Users: Utilize community features to interact with other users. For example, share experiences and opinions in chats and forums.

[0096] Terminal: Sends user messages to the server and receives and displays messages from other users.

[0097] Server: Sends messages to other relevant user terminals and manages community features. It also filters spam and inappropriate content.

[0098] Step 6: Connecting with a smartwatch (optional)

[0099] User: Wear the smartwatch and connect it to the app.

[0100] Device: Acquires biometric data such as heart rate and stress level from the smartwatch and sends it to the server.

[0101] Server: Sends the received biometric data to the AI ​​model for generation.

[0102] Generative AI models: These models generate more specific suggestions based on biometric data. For example, they might suggest deep breathing exercises if the heart rate is high.

[0103] Server: Sends the generated proposal to the terminal.

[0104] Terminal: Notifies the user of suggestions. For example, it displays a notification such as, "Take three deep breaths right now."

[0105] In this way, the system helps users control their cravings for alcohol in a healthy manner.

[0106] (Example 1)

[0107] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0108] Traditional alcohol reduction systems lacked the ability to suggest alternative activities tailored to each user's individual circumstances and psychological state. This made it difficult for users to actually refrain from drinking. Furthermore, they lacked features for collaboration with other users through community functions and systems capable of providing personalized suggestions based on real-time biometric data. As a result, it was difficult to motivate users and achieve long-term alcohol reduction.

[0109] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0110] In this invention, the server includes means for receiving mood and environmental data from the user, means for analyzing the received data and generating alternative activities for the user using a generative artificial intelligence model, means for presenting the generated alternative activities to the user, and means for collecting biometric data in conjunction with a corresponding bio-device and generating alternative activities based on the collected biometric data. This makes it possible to suggest alternative activities that are tailored to the individual circumstances and psychology of the user, thereby enabling long-term alcohol suppression.

[0111] "User" refers to an individual who uses the system.

[0112] "Mood" refers to data that indicates the user's emotions and mental state.

[0113] "Environmental data" refers to information about the physical or psychological environment in which a user is placed.

[0114] "Analysis" refers to the process of processing received data to extract useful information.

[0115] A "generative artificial intelligence model" refers to an AI system that generates alternative activities based on received data.

[0116] "Alternative activities" refer to activities or tasks that users can undertake to reduce their alcohol consumption.

[0117] "Presentation" refers to the act of informing the user of the generated alternative activity.

[0118] "Biometric devices" refer to wearable devices and sensors that collect users' biometric data.

[0119] "Biometric data" refers to data that indicates a user's physical condition or health status.

[0120] "Community features" refer to functions that allow users to connect and interact with other users who have similar problems.

[0121] "Suggestions" refer to recommended activities and methods provided to users based on analyzed data.

[0122] "Means of receiving" refers to devices or functions used to receive data from users.

[0123] "Means of transmission" refers to devices or functions used to send data or requests to other systems.

[0124] "Means of generation" refers to devices or functions used to analyze data and produce specific results.

[0125] "Means of collection" refers to the devices or functions used to collect data.

[0126] This invention is a system that provides behavioral support to help users reduce their alcohol consumption, and is primarily implemented by combining a user terminal (smartphone application), a server, and a generative AI model. The specific implementation methods of these components are described in detail below.

[0127] User device (smartphone app)

[0128] The user device will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[0129] 1. User registration and login function

[0130] Users: When launching the app for the first time, create an account by entering basic information such as your name, email address, and drinking frequency. If you already have an account, access it using the login function.

[0131] Terminal: Sends the entered information to the server, which then stores it in the database.

[0132] 2. Data Input Interface

[0133] User: Uses an interface to input data about daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[0134] Terminal: Sends the entered data to the server.

[0135] 3. Receiving and displaying proposals

[0136] Terminal: Receives suggestions from the generating AI model and displays them to the user. For example, it might suggest specific activities such as "Join an online yoga session" or "Watch a new movie."

[0137] 4. Community Features

[0138] Users can utilize community features that allow them to interact with other users who share similar concerns. Information exchange and support are provided through chat and forums.

[0139] 5. Integration with smartwatches

[0140] Device: It works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current state in real time and suggests appropriate activities.

[0141] Server-side functionality

[0142] The server will be implemented as a cloud-based system with the following functions:

[0143] 1. User data management

[0144] Server: Manages user account information, daily input data, requests to generated AI models, etc.

[0145] 2. Communication with the Generative AI Model

[0146] Server: Receives data sent by the user and sends a request to the generative AI model to perform analysis and make suggestions. Specifically, it uses prompt statements to request data analysis from the generative AI model.

[0147] Example prompt: "The user is currently experiencing significant stress and has a strong urge to drink alcohol. What alternative activity would you suggest?"

[0148] 3. Managing Community Features

[0149] Server: Manages community functions, including sending and receiving messages and running forums. Also filters spam and inappropriate content.

[0150] Generative AI Models

[0151] The generative AI model will be implemented as an artificial intelligence system with the following functions:

[0152] 1. Data Analysis

[0153] Generative AI Model: Analyzes user data received from the server and generates alternative activities suitable for the user's mood and environment on that day. Specifically, it performs analysis and makes suggestions based on prompt messages.

[0154] 2. Proposal generation

[0155] Generative AI Model: Based on the results of data analysis, it generates specific activity suggestions for the user. For example, if the user is experiencing high stress, it might suggest relaxation methods; if the user has a strong urge to drink, it might suggest alternative hobbies.

[0156] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle. This makes it possible to suggest alternative activities tailored to each user's individual circumstances and psychology, thereby achieving long-term alcohol reduction.

[0157] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0158] Step 1: User registration and login

[0159] Specific actions:

[0160] User: Download and launch the app.

[0161] Input: Users enter basic information such as their name, email address, and frequency of drinking.

[0162] Terminal: Sends the entered information to the server.

[0163] Server: Saves the received registration information to the database and generates a registration completion message.

[0164] Output: The server sends a registration completion message to the terminal.

[0165] User: Enter your existing account information (email address and password) to log in.

[0166] Terminal: Sends login information to the server.

[0167] Server: The server checks against the database and, if authentication is successful, approves the login.

[0168] Output: Sends the authentication result to the terminal.

[0169] Step 2: Daily data entry

[0170] Specific actions:

[0171] User: Open the app and enter data about your mood and environment for the day (e.g., "I'm feeling stressed today," "I have a strong urge to drink").

[0172] Input: Data about the user's daily mood and environment.

[0173] Terminal: Formats the data and sends it to the server.

[0174] Server: Receives data and saves it to the database.

[0175] Output: Generates a data saving confirmation message and sends it to the terminal.

[0176] Step 3: Send data to the server

[0177] Specific actions:

[0178] Terminal: Once data entry is complete, the terminal sends the data to the server.

[0179] Input: User data sent by the device.

[0180] Server: Stores received data in the database and prepares requests for the generated AI model.

[0181] Output: Generates a data saving confirmation message and sends it to the terminal.

[0182] Step 4: Data analysis and proposal generation using generative AI models

[0183] Specific actions:

[0184] Server: Formats the data sent by the user and generates a request to send to the generated AI model.

[0185] Server: Sends an example prompt message, "The user is currently experiencing significant stress and has a strong urge to drink alcohol. What alternative activities would you suggest?" to the generating AI model.

[0186] Input: Prompt message and user data.

[0187] Generative AI model: Analyzes received data and generates optimal alternative activities for the user.

[0188] Output: The analysis results (e.g., "Participate in an online yoga session," "Watch a new movie") are sent back to the server.

[0189] Step 5: Receiving and displaying proposals

[0190] Specific actions:

[0191] Server: Sends suggestions received from the generated AI model to the user's terminal.

[0192] Input: Suggestions from a generative AI model.

[0193] Terminal: Displays received suggestions to the user.

[0194] Output: Suggestions are displayed on the user's screen (e.g., "Join an online yoga session," "Watch a new movie").

[0195] Step 6: Using Community Features

[0196] Specific actions:

[0197] Users: Interact with other users through chat and forums using the in-app community features.

[0198] Input: User messages or posts.

[0199] Server: Manages community messages and posts, and filters out spam and inappropriate content.

[0200] Output: Messages and posts within the community are displayed.

[0201] Step 7: Collect and transmit smartwatch data

[0202] Specific actions:

[0203] User: Wear the smartwatch and connect it to the app.

[0204] Input: Biometric data collected by the smartwatch (e.g., heart rate, stress level).

[0205] Terminal: Sends collected biometric data to the server.

[0206] Server: Sends received biometric data to a generating AI model and makes a request to generate specific suggestions.

[0207] Output: The suggestions generated by the generative AI model are presented to the user again.

[0208] The above describes the specific processing flow of this system's program.

[0209] (Application Example 1)

[0210] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0211] In modern society, health problems caused by alcohol consumption are on the rise, making prevention crucial. However, many people find it difficult to find alternative activities to avoid alcohol. Furthermore, many people who want to avoid alcohol lack access to helpful information and support. The lack of concrete alternative activity suggestions in physical stores is also a challenge.

[0212] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0213] In this invention, the server includes means for receiving mood and environmental data from the user, means for analyzing the received data and using a generative AI model to generate alternative activities for the user, means for presenting the generated alternative activities to the user, and means for suggesting alternative activities that can be used in physical stores. This makes it possible for users to easily find activities other than alcohol, and further promote a healthier lifestyle by experiencing these activities in physical stores.

[0214] A "user" is someone who uses the system to receive suggestions for alternative activities to reduce alcohol consumption.

[0215] "Mood and environmental data" refers to data that indicates the user's mood, stress level, physical condition, etc., at any given time.

[0216] A "generative AI model" is an artificial intelligence model used to analyze data received from users and generate optimal alternative activities.

[0217] "Alternative activities" refer to activities or behaviors that can be done instead of consuming alcohol.

[0218] A "physical store" refers to a store that is a real physical location, such as a cafe, a gym, or a movie theater.

[0219] "Biometric data" refers to data indicating a person's physical condition, such as heart rate and stress levels, obtained from smartwatches and other wearable devices.

[0220] "Community features" refer to functions that allow users with similar problems to connect and interact with each other.

[0221] This invention relates to a comprehensive support system for users to reduce alcohol consumption and maintain a healthy lifestyle through alternative activities. The entire system consists of a smartphone app, a cloud-based server, a generative AI model, and wearable devices such as smartwatches.

[0222] User device (smartphone app)

[0223] The user device will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[0224] 1. User registration and login function

[0225] When a user first launches the app, they create an account by entering basic information such as their name, email address, and drinking frequency. If they already have an account, they can access it using the login function.

[0226] 2. Data Input Interface

[0227] Users utilize an interface to input data about their daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[0228] 3. Receiving and displaying proposals

[0229] The device receives suggestions from the generated AI model and displays them to the user. For example, it might suggest specific activities such as "Take a break at a nearby cafe" or "Participate in a relaxation session at a gym."

[0230] 4. Community Features

[0231] Users can utilize community features that allow them to interact with other users who share similar concerns. Information exchange and support are provided through chat and forums.

[0232] 5. Integration with smartwatches

[0233] The device works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current status in real time and suggests appropriate activities. Hardware options include Apple Watch and Fitbit.

[0234] Server-side functionality

[0235] The server will be implemented as a cloud-based system with the following functions:

[0236] 1. User data management

[0237] The server manages user account information, daily input data, and requests to the generated AI model. Databases such as PostgreSQL are used.

[0238] 2. Communication with the Generative AI Model

[0239] The server receives data sent by the user and sends a request to the generative AI model to perform analysis and provide suggestions. Generative AI models such as TensorFlow and GPT-4 are used.

[0240] 3. Managing Community Features

[0241] The server manages community functions, including sending and receiving messages and running forums. It also filters spam and inappropriate content.

[0242] Generative AI Models

[0243] The generative AI model will be implemented as an artificial intelligence system with the following functions:

[0244] 1. Data Analysis

[0245] The generative AI model analyzes the received user data and generates alternative activities that are suitable for the user's mood and environment on that day.

[0246] 2. Proposal generation

[0247] The generative AI model generates specific activity suggestions for the user based on the results of data analysis. For example, if the user is experiencing high stress levels, it might suggest relaxation methods; if they have a strong urge to drink, it might suggest alternative hobbies.

[0248] Specific example

[0249] 1. User Registration

[0250] The user downloads the app, enters their name, email address, and drinking frequency to register. The server receives this information and stores it in its database.

[0251] 2. Daily data entry

[0252] The user inputs their mood and circumstances for the day into the app. For example, they might enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." The device then sends this information to the server.

[0253] 3. Proposal generation and presentation

[0254] The server sends data to a generative AI model and requests suggestions. The generative AI model analyzes the data and generates specific activities such as "take a break at a nearby cafe" or "participate in a relaxation session at a gym." The terminal receives the suggestions and displays them to the user. The user can then select and perform one of the suggested activities.

[0255] 4. Use of community features

[0256] Users interact with other users through chat and forums, sharing experiences and opinions. The server manages this.

[0257] 5. Integration with smartwatches

[0258] The user wears a smartwatch and connects it to an app. The device collects heart rate and stress levels and sends them to a server. The generated AI model then uses this data to make more specific suggestions.

[0259] Example of a prompt

[0260] "The user is under a lot of stress and busy at work, so they need relaxation. Their current mood is normal, and they want to avoid alcohol. Please suggest some activities they can enjoy around the store."

[0261] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0262] Step 1:

[0263] Users download a smartphone app, enter their name, email address, and drinking frequency to create an account. The entered information is sent from the device to a cloud server.

[0264] Step 2:

[0265] The server stores the received user registration information in the database and generates a user ID. The server verifies the stored data and sends a registration success message back to the user.

[0266] Step 3:

[0267] Users input data about their daily mood and environment into a smartphone app. For example, they might enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." This data is then sent from the device to a server.

[0268] Step 4:

[0269] The server stores the received mood and environment data in a database. It generates prompts to send the stored data to the AI ​​model and prepares it for transmission to the AI ​​model.

[0270] Step 5:

[0271] The generative AI model receives a prompt message and analyzes the user's mood and environmental data. Based on the analysis, it suggests specific and appropriate alternative activities, such as taking a break at a nearby cafe or a relaxation session at a gym.

[0272] Step 6:

[0273] The server stores the suggestions received from the generated AI model in a database and sends them to the user's terminal. The terminal then displays the received suggestions to the user.

[0274] Step 7:

[0275] The user selects from the proposed activities and performs them. Additionally, the user can utilize the community function to communicate with other users who have the same concerns.

[0276] Step 8:

[0277] Biometric data (such as heart rate and stress level) from the user wearing the smartwatch is transmitted to the terminal in real time. The terminal transmits this data to the server.

[0278] Step 9:

[0279] The server stores the received biometric data in the database and generates a prompt sentence to request new proposals from the generated AI model. The generated AI model analyzes the real-time biometric data and generates new alternative activities.

[0280] Step 10:

[0281] The server transmits the generated new proposals to the user's terminal, and the terminal displays them to the user. The user can select and experience the most interesting activity.

[0282] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion recognition model 59 and perform specific processing using the user's emotion.

[0283] The present invention relates to a system that provides beneficial alternative activities and community functions for refraining from alcohol consumption, as well as an emotion recognition function using an emotion engine, in order for users to avoid health hazards caused by alcohol drinking. This system is mainly implemented by combining a user terminal (smartphone application), a server, a generated AI model, and an emotion engine.

[0284] User terminal (smartphone application)

[0285] The user terminal is implemented as a smartphone app with the following functions. This app is assumed to be used by users on a daily basis.

[0286] 1. User registration and login function

[0287] User: When starting the app for the first time, the user creates an account by entering basic information such as name, email address, and frequency of drinking. If there is an existing account, the user accesses the account using the login function.

[0288] 2. Data input interface

[0289] User: The user uses an interface to input data on daily mood and environment. For example, the user reports situations such as "I'm stressed today" and "I have a strong urge to drink alcohol".

[0290] 3. Receiving and displaying suggestions

[0291] Terminal: The terminal receives suggestions from the generated AI model and the emotion engine and displays them to the user. For example, the terminal presents specific activities such as "Participate in an online yoga session" and "Watch a new movie".

[0292] 4. Community function

[0293] User: The user uses the community function to communicate with other users who have the same concerns. Information exchange and support are carried out through chat and forums.

[0294] 5. Linkage with smartwatch

[0295] Terminal: The terminal collects biometric data in conjunction with a smartwatch. Based on this data, the terminal monitors the user's current state in real time and further proposes appropriate activities.

[0296] 6. Emotional Engine

[0297] Terminal: The emotional engine analyzes voice and facial expression data to recognize the user's emotions. Based on this emotional data, the generative AI model proposes more accurate alternative activities.

[0298] Server-side Functions

[0299] The server is implemented as a cloud-based system with the following functions.

[0300] 1. User Data Management

[0301] Server: Manages the user's account information, daily input data, requests to the generative AI model and the emotional engine, etc.

[0302] 2. Communication with the Generative AI Model and the Emotional Engine

[0303] Server: Receives data sent from the user and sends requests for analysis and proposals to the generative AI model and the emotional engine. <00009s7>

[0304] 3. Community Function Management

[0305] Server: Manages the community function, conducts message sending and receiving and forum operation. Also implements filtering of spam and inappropriate content.

[0306] Generative AI Model and Emotional Engine

[0307] The generative AI model and the emotional engine are implemented as an artificial intelligence system with the following functions.

[0308] 1. Data Analysis and Emotion Recognition

[0309] Generative AI Model: Analyzes the received user data and generates alternative activities suitable for the mood and environment of the day.

[0310] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotional state. This emotional data is then provided to the AI ​​model for generating more personalized suggestions.

[0311] 2. Proposal generation

[0312] Generative AI Model: Based on data analysis and emotion recognition results, it generates specific activity suggestions for the user. For example, if stress levels are high and emotion recognition identifies "irritation," it will suggest relaxation methods.

[0313] Specific example

[0314] 1. User Registration

[0315] User: Users download the app, enter their name, email address, and drinking frequency to register. The server receives this information and stores it in its database.

[0316] 2. Daily data entry

[0317] User: Enters their mood and circumstances for the day into the app. For example, they might enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." The device then sends this information to the server.

[0318] 3. Analysis of voice and facial expressions

[0319] User: Speak to the app using voice commands or turn your face towards the camera.

[0320] Terminal: Acquires voice data and facial expression data and sends it to the emotion engine.

[0321] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotions. For example, it might generate a result such as "irritated."

[0322] 4. Proposal generation and presentation

[0323] Server: Sends data to the generative AI model and emotion engine and requests suggestions. The generative AI model generates specific activities based on data analysis and emotion recognition results.

[0324] Terminal: Receives suggestions and displays them to the user. The user can select and perform the suggested activities (e.g., relaxation methods or hobbies).

[0325] 5. Use of community features

[0326] Users interact with other users through chat and forums, sharing experiences and opinions. The server manages this.

[0327] 6. Integration with smartwatches

[0328] User: Wears a smartwatch and connects it to the app. The device collects heart rate and stress levels and sends them to the server. The generative AI model and emotion engine then use this data to make more specific suggestions.

[0329] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle.

[0330] The following describes the processing flow.

[0331] Step 1: User Registration

[0332] User: Launch the app for the first time and enter basic information such as name, email address, and daily drinking frequency.

[0333] Terminal: Sends the entered information to the server.

[0334] Server: Stores the received information in the database and returns a success message for account creation to the terminal.

[0335] Terminal: Displays a success message to the user.

[0336] Step 2: Data Entry

[0337] User: Enter information about your mood and environment for the day into the app. For example, you might report, "I'm feeling stressed today," or "I have a strong urge to drink."

[0338] Terminal: Sends the entered data to the server.

[0339] Server: Receives data and saves it to the database.

[0340] Step 3: Request analysis from generative AI models and emotion engines.

[0341] Server: Sends stored data to the generative AI model and sentiment engine for analysis. Specifically, it sends POST requests to the generative AI model and sentiment engine.

[0342] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotions. The results of the emotion recognition are then sent to a generating AI model.

[0343] Generative AI Model: Based on received data and emotion recognition results, it generates optimal alternative activities for the user. For example, it suggests relaxation methods or hobby-related activities.

[0344] Generative AI model: Returns the generated suggestions to the server.

[0345] Step 4: Providing and displaying proposals

[0346] Server: Receives suggestions from the generative AI model and emotion engine, and sends them to the user's terminal.

[0347] Device: Receives suggestions and displays them to the user. For example, it displays a link to "Online yoga sessions you can join now" on the app's home screen.

[0348] Step 5: Utilizing Community Features

[0349] Users: Utilize community features to interact with other users. For example, share experiences and opinions in chats and forums.

[0350] Terminal: Sends user messages to the server and receives and displays messages from other users.

[0351] Server: Sends messages to other relevant user terminals and manages community features. It also filters spam and inappropriate content.

[0352] Step 6: Connecting with a smartwatch (optional)

[0353] User: Wear the smartwatch and connect it to the app.

[0354] Device: Acquires biometric data such as heart rate and stress level from the smartwatch and sends it to the server.

[0355] Server: Sends received biometric data to the generating AI model and emotion engine.

[0356] Generative AI Model: Generates more specific suggestions based on biometric data and emotion recognition results. For example, it might suggest deep breathing exercises if the heart rate is high.

[0357] Server: Sends the generated proposal to the terminal.

[0358] Terminal: Notifies the user of suggestions. For example, it displays a notification such as, "Take three deep breaths right now."

[0359] In this way, the system helps users control their cravings for alcohol in a healthy manner.

[0360] (Example 2)

[0361] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0362] In recent years, health problems caused by alcohol consumption have become a social issue. Therefore, effective measures to reduce alcohol consumption are needed. However, conventional technologies struggle to suggest personalized alternative activities tailored to the user's mood and environment, and advanced analysis based on users' emotional states and biometric data is lacking. Furthermore, opportunities for connection and interaction with other users who share similar concerns are insufficient.

[0363] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0364] In this invention, the server includes means for receiving mood and environmental data from the user, means including a generative AI model that analyzes the received data and generates alternative activities for the user, means for presenting the generated alternative activities to the user, means including an emotion engine that analyzes the user's voice and facial expression data and recognizes their emotional state, and means for generating alternative activities based on the analyzed emotional state. As a result, the user can receive personalized alternative activity suggestions that match their mood and emotional state, enabling effective support for reducing alcohol consumption. Furthermore, it is also possible to include a community function for collaborating and interacting with other users who have similar concerns, and to collect biometric data in conjunction with a smartwatch to provide more accurate suggestions.

[0365] A "user" is a person who uses the system, creates an account, and inputs data about their daily mood and environment.

[0366] "Mood and environmental data" refers to information about the user's daily mood and psychological state, as well as the environment and circumstances of that day.

[0367] "Means of receiving data" refers to an interface equipped with the function of collecting data from users and transmitting it to a server or analysis system.

[0368] A "generative AI model" refers to an artificial intelligence system that analyzes received data and generates alternative activities suitable for the user based on the analysis results.

[0369] "Alternative activities" refer to beneficial activities or methods suggested by the system to reduce alcohol consumption, and are generated based on the user's mood and emotional state.

[0370] "Means of presentation" refers to interfaces and devices used to display suggestions from generative AI models and emotion engines to users.

[0371] An "emotion engine" refers to a system that analyzes a user's voice and facial expression data to recognize their emotional state.

[0372] "Voice and facial expression data" refers to biometric data that includes information about the voice and facial expressions emitted by the user, and is the subject of analysis by the emotion engine.

[0373] "Community features" refer to chat and forum functions that allow users to exchange information and support each other with other users who have similar problems.

[0374] A "smartwatch" refers to a wearable device that collects biometric data such as the user's heart rate and stress level, and transmits it to the user's device or a server.

[0375] "Biometric data" refers to information about a user's physical condition, such as heart rate and stress level, collected through devices like smartwatches.

[0376] This invention relates to a system that provides users with beneficial alternative activities and community features to help them avoid health damage caused by alcohol consumption, as well as an emotion recognition function using an emotion engine. This system is mainly implemented by combining a user terminal (smartphone application), a server, a generative AI model, and an emotion engine.

[0377] User device (smartphone app)

[0378] The user terminal will be implemented as a smartphone application for daily use by the user. This application will have the following functions:

[0379] 1. User registration and login function

[0380] Users: When launching the app for the first time, create an account by entering information such as your name, email address, and drinking frequency. If you already have an account, log in by entering your email address and password.

[0381] Terminal: Sends the entered information to the server to create a new account or authenticate login.

[0382] 2. Data Input Interface

[0383] User: Enter data about your daily mood and environment. For example, enter information such as "I'm feeling stressed today" or "I have a strong urge to drink" into the app.

[0384] Terminal: Sends the entered data to the server.

[0385] 3. Receiving and displaying proposals

[0386] Terminal: Receives suggestions from the generative AI model and emotion engine and displays them to the user. For example, specific activities such as "join an online yoga session" or "watch a new movie" may be suggested.

[0387] 4. Community Features

[0388] Users: Utilize community features to interact with other users who share similar concerns. Exchange information and support through chat and forums.

[0389] Server: Manages these community features, including sending and receiving messages and running forums. Also filters spam and inappropriate content.

[0390] 5. Integration with smartwatches

[0391] User: Wear a smartwatch and connect it to the app. The device collects biometric data such as heart rate and stress level.

[0392] Terminal: Sends collected biometric data to the server.

[0393] 6. Emotional Engine

[0394] Device: The emotion engine analyzes voice and facial expression data to recognize the user's emotions. Based on this emotion data, a generative AI model suggests more accurate alternative activities.

[0395] Server-side functionality

[0396] The server has the following functions and will be implemented as a cloud-based system:

[0397] 1. User data management

[0398] Server: Manages user account information, daily input data, and requests to the generative AI model and sentiment engine.

[0399] 2. Communication with generative AI models and emotion engines

[0400] Server: Receives data sent from users and sends requests to the generative AI model and emotion engine to perform analysis and make suggestions.

[0401] 3. Managing Community Features

[0402] Server: Manages community functions, including sending and receiving messages and running forums. Also performs filtering of inappropriate content.

[0403] Generative AI models and emotion engines

[0404] The generative AI model and emotion engine will be implemented as an artificial intelligence system with the following functions:

[0405] 1. Data analysis and sentiment recognition

[0406] Generative AI Model: Analyzes received user data and generates alternative activities suitable for the user's mood and environment on that day.

[0407] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotional state. This emotional data is then provided to the AI ​​model for generating more personalized suggestions.

[0408] 2. Proposal generation

[0409] Generative AI Model: Based on data analysis and emotion recognition results, it generates specific activity suggestions for the user. For example, if stress levels are high and emotion recognition reveals "irritation," it will suggest relaxation methods.

[0410] Specific example

[0411] 1. User Registration

[0412] User: Downloads the app, enters their name, email address, and drinking frequency to register. The server receives this information and stores it in its database.

[0413] 2. Daily data entry

[0414] User: Enters their mood and circumstances for the day into the app. They enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." The device then sends this information to the server.

[0415] 3. Analysis of voice and facial expressions

[0416] User: Speak to the app using voice commands or turn your face towards the camera.

[0417] The device acquires voice and facial expression data and sends it to the emotion engine. The emotion engine analyzes this data and recognizes the user's emotional state. For example, it might generate a result such as "irritated."

[0418] 4. Proposal generation and presentation

[0419] Server: Sends data to the generative AI model and emotion engine and requests suggestions. The generative AI model generates specific activities based on data analysis and emotion recognition results.

[0420] Terminal: Receives suggestions and displays them to the user. The user can select and perform the suggested activities (e.g., "relaxation methods" or "hobby activities").

[0421] 5. Use of community features

[0422] Users interact with other users through chat and forums, sharing experiences and opinions. The server manages this.

[0423] 6. Integration with smartwatches

[0424] User: Wears a smartwatch and connects it to the app. The device collects heart rate and stress levels and sends them to the server. The generative AI model and emotion engine then use this data to make more specific suggestions.

[0425] Examples of prompt statements

[0426] 1. A stressful day

[0427] User: Enter "I'm feeling particularly stressed today, so please tell me some relaxation techniques" as the prompt.

[0428] Generative AI model: Based on the received prompt, it suggests specific relaxation methods (e.g., "Do deep breathing exercises," "Try aromatherapy").

[0429] 2. Days when the urge to drink is strong

[0430] User: Enter the following as the prompt: "I have a strong urge to drink alcohol, so I would like suggestions for alternative hobbies or activities."

[0431] Generative AI model: Based on user sentiment data and daily data analysis results, it suggests hobby activities (e.g., "drawing pictures," "reading books").

[0432] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle.

[0433] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0434] Step 1:

[0435] User Registration / Login

[0436] User: When launching the app for the first time, you will create an account by entering basic information such as your name, email address, and frequency of drinking.

[0437] Terminal: Sends the entered user information to the server.

[0438] Server: Receives user information and stores it in the database. If an existing account exists, it receives the email address and password and verifies them against the database. If authentication is successful, it starts the session.

[0439] Input: The user's basic information is entered here.

[0440] Output: The results of account creation and authentication on the server are output.

[0441] Step 2:

[0442] Daily data entry

[0443] User: Launch the app and enter data about your mood and environment for the day. Specifically, enter information such as "I'm feeling stressed today" or "I have a strong urge to drink."

[0444] Terminal: Sends the entered data to the server.

[0445] Server: Receives data, links it to user information, and saves it to the database.

[0446] Input: Daily data related to mood and environment is entered.

[0447] Output: Daily data stored in the database is output.

[0448] Step 3:

[0449] Collection and analysis of emotional data

[0450] User: Speak to the app using voice commands or turn your face towards the camera.

[0451] Terminal: Collects voice data and facial expression data and sends it to the emotion engine.

[0452] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotional state. For example, it generates results such as "irritated."

[0453] Terminal: Sends analysis results to the server.

[0454] Input: Voice data and facial expression data are input.

[0455] Output: The analysis results of the emotion engine are output.

[0456] Step 4:

[0457] Proposal generation and presentation

[0458] Server: Inputs daily data and sends emotional data to the AI ​​model for analysis and recommendations.

[0459] Generative AI Model: Analyzes received data and generates specific activity suggestions. For example, if it detects high stress levels, it will suggest "relaxation methods."

[0460] Server: Receives suggestions from the generated AI model and sends them to the user's terminal.

[0461] Terminal: Receives suggestions and displays the suggestions to the user. The user can select and perform the suggested activities.

[0462] Input: Daily data and sentiment data are entered.

[0463] Output: Activity suggestions generated by the generative AI model are output.

[0464] Step 5:

[0465] Using community features

[0466] Users: Utilize the app's community features to interact with other users through chat and forums.

[0467] Server: Manages message sending and receiving, forum operation, and filters inappropriate content.

[0468] Input: Messages and posts from the community are entered here.

[0469] Output: Information about community features managed by the server is output.

[0470] Step 6:

[0471] Collection and linkage of biometric data

[0472] User: Wear the smartwatch and connect it to the app.

[0473] Device: Collects biometric data such as heart rate and stress level from the smartwatch and sends it to the server.

[0474] Server and Generative AI Model: Generates more specific suggestions based on received biometric data.

[0475] Terminal: Displays specific activity suggestions to the user from the generated AI model.

[0476] Input: Biometric data from a smartwatch is entered.

[0477] Output: Specific activity suggestions generated by the AI ​​model are output.

[0478] Through these steps, the system provides users with personalized alternative activity suggestions and offers effective support for reducing alcohol consumption.

[0479] (Application Example 2)

[0480] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0481] In modern society, the health risks associated with alcohol consumption are a major problem. In particular, because moderate alternative activities are not readily available, many people try to relieve stress and cravings with alcohol. However, there is a lack of specific and personalized suggestions tailored to individual circumstances. Therefore, there is a need for effective support systems to help users maintain a healthy lifestyle.

[0482] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0483] In this invention, the server includes means for receiving mood and environmental data from the user, means for analyzing the received data and generating alternative activities for the user using a generative AI model, means for presenting the generated alternative activities to the user, means for analyzing the user's voice and facial expression data using an emotion recognition engine and identifying their emotional state, and means for the generative AI model to suggest even more accurate alternative activities based on the emotional state. As a result, the user can receive personalized alternative activity suggestions based on their emotional state and biometric data, making it easier to maintain a healthy lifestyle.

[0484] "User" refers to an individual who uses the system.

[0485] "Mood and environmental data" refers to information about the user's everyday emotions and surrounding circumstances.

[0486] "Means of receiving" refers to methods and devices for securing data transmitted by users.

[0487] "Means of analysis" refers to methods and devices that analyze received data to derive meaningful information.

[0488] A "generative AI model" refers to an artificial intelligence algorithm that generates new suggestions and activities based on received and analyzed data.

[0489] "Alternative activities" refer to beneficial activities or hobbies that help prevent drinking.

[0490] "Means of presentation" refers to the methods or devices used to show the generated activities or suggestions to the user.

[0491] An "emotion recognition engine" refers to a system that analyzes voice and facial expression data to identify the user's emotional state.

[0492] "Voice and facial expression data" refers to information about the user's voice and facial expressions.

[0493] "Biometric data" refers to physical information such as heart rate and stress levels collected using devices like smartwatches.

[0494] "Community features" refer to online platforms that allow users to exchange information and support each other with similar problems.

[0495] The system of the present invention is composed of a user terminal, a server, a generative AI model, an emotion recognition engine, and biosensor devices such as a smartwatch.

[0496] User terminal (smartphone app)

[0497] The user terminal will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[0498] 1. User registration and login function

[0499] Users create an account upon first launch by entering basic information such as their name, email address, and frequency of drinking. If an existing account exists, they can access it using the login function.

[0500] 2. Data Input Interface

[0501] Users utilize an interface to input data about their daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[0502] 3. Receiving and displaying proposals

[0503] The device receives suggestions from the generative AI model and emotion recognition engine and displays them to the user. For example, it may suggest specific activities such as "join an online yoga session" or "watch a new movie."

[0504] 4. Community Features

[0505] Users can utilize community features to interact with other users who share similar concerns. Information exchange and support are provided through chat and forums.

[0506] 5. Integration with smartwatches

[0507] The device works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current state in real time and suggests appropriate activities.

[0508] 6. Emotion Recognition Engine

[0509] The device uses an emotion recognition engine to analyze voice and facial expression data to recognize the user's emotions. Based on this emotion data, a generative AI model suggests more accurate alternative activities.

[0510] Server-side functionality

[0511] The server will be implemented as a cloud-based system with the following functions:

[0512] 1. User data management

[0513] The server manages user account information, daily input data, and requests to the generative AI model and emotion recognition engine.

[0514] 2. Communication with generative AI models and emotion recognition engines

[0515] The server receives data sent by the user and sends requests to the generative AI model and emotion recognition engine to perform analysis and make suggestions.

[0516] 3. Managing Community Features

[0517] The server manages community functions, including sending and receiving messages and running forums. It also filters spam and inappropriate content.

[0518] Generative AI models and emotion recognition engines

[0519] The generative AI model and emotion recognition engine will be implemented as an artificial intelligence system with the following functions:

[0520] 1. Data analysis and sentiment recognition

[0521] The generative AI model analyzes the received user data and generates alternative activities that are suitable for the user's mood and environment on that day.

[0522] The emotion recognition engine analyzes voice and facial expression data to recognize the user's emotional state. This emotional data is then provided to the AI ​​model for generating more personalized suggestions.

[0523] 2. Proposal generation

[0524] The generative AI model generates specific activity suggestions for the user based on data analysis and emotion recognition results. For example, if stress levels are high and emotion recognition identifies "irritation," it will suggest relaxation methods.

[0525] Presentation of specific examples and prompt statements

[0526] For example, the following prompt could represent emotional data when a user is feeling stressed.

[0527] Example of a prompt:

[0528] I'm feeling very stressed today. I have a strong urge to drink, but what can I do to control it?

[0529] Based on this data, the generated AI model and emotion recognition engine work together to suggest specific alternative activities.

[0530] Hardware and software to be used

[0531] User devices: Smartphones, smartwatches

[0532] Server: Cloud service platform (e.g., AWS, Google Cloud)

[0533] Generative AI models and emotion recognition engines: Deep learning frameworks (e.g., TensorFlow, PyTorch)

[0534] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle.

[0535] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0536] Step 1:

[0537] The user launches the smartphone app and uses the user registration / login function to enter basic information such as their name, email address, and frequency of drinking. This input data is received by the device and sent to the server. The server stores this data in a database.

[0538] Input: Name, email address, and basic information about your drinking frequency.

[0539] Output: User information stored in the server's database

[0540] Step 2:

[0541] Users report daily mood and environmental data using the in-app data input interface. For example, they might write, "I'm feeling stressed today" or "I have a strong urge to drink." This input data is then sent back to the server by the device and recorded.

[0542] Input: Data related to mood and environment

[0543] Output: Daily data sent to and recorded on the server

[0544] Step 3:

[0545] Users provide emotional data by speaking aloud or facing the camera. The device acquires the voice and facial expression data and sends it to an emotion recognition engine. The emotion recognition engine analyzes the data and identifies the user's emotional state. This result is then sent to a generative AI model.

[0546] Input: Voice data and facial expression data

[0547] Output: Identification of emotional state by emotion recognition engine

[0548] Step 4:

[0549] The server sends daily mood and environmental data, as well as emotional data from the emotion recognition engine, to a generative AI model. The generative AI model analyzes this data and generates alternative activities based on the user's current state. These activity suggestions are then sent to the server.

[0550] Input: Mood and environmental data, emotional data

[0551] Output: Suggestions for alternative activities using a generative AI model.

[0552] Step 5:

[0553] The server sends alternative activity suggestions received from the generated AI model to the terminal, and the user terminal displays them to the user. The user can then select and perform the displayed activity suggestion.

[0554] Input: Activity suggestions from a generated AI model

[0555] Output: Alternative activities displayed to the user

[0556] Step 6:

[0557] Users utilize the app's community features to interact with other users who share similar concerns through chat and forums. The server manages the community features, handling message sending and receiving, and running the forums.

[0558] Input: Chat messages and forum posts from users

[0559] Output: Information exchange and support with other users

[0560] Step 7:

[0561] Users wear biosensor devices such as smartwatches and connect them to the app. The device collects biometric data such as heart rate and stress levels from the smartwatch and sends it to a server. The server provides this biometric data to a generating AI model and emotion recognition engine, which then suggests more specific activities.

[0562] Input: Biometric data obtained from a smartwatch

[0563] Output: Specific activity suggestions generated by a generative AI model and emotion recognition engine.

[0564] Through these steps, the system provides effective support for reducing alcohol consumption and helps users maintain a healthy lifestyle.

[0565] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0566] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0567] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0568] [Second Embodiment]

[0569] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0570] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0571] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0572] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0573] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0574] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0575] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0576] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0577] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0578] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0579] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0580] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0581] This invention relates to a system that provides users with beneficial alternative activities and community features to help them avoid health problems caused by alcohol consumption. This system is primarily implemented by combining a user terminal (smartphone application), a server, and a generative AI model.

[0582] User device (smartphone app)

[0583] The user device will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[0584] 1. User registration and login function

[0585] Users: When launching the app for the first time, create an account by entering basic information such as your name, email address, and drinking frequency. If you already have an account, access it using the login function.

[0586] 2. Data Input Interface

[0587] User: Uses an interface to input data about daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[0588] 3. Receiving and displaying proposals

[0589] Terminal: Receives suggestions from the generating AI model and displays them to the user. For example, it might suggest specific activities such as "Join an online yoga session" or "Watch a new movie."

[0590] 4. Community Features

[0591] Users can utilize community features that allow them to interact with other users who share similar concerns. Information exchange and support are provided through chat and forums.

[0592] 5. Integration with smartwatches

[0593] Device: It works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current state in real time and suggests appropriate activities.

[0594] Server-side functionality

[0595] The server will be implemented as a cloud-based system with the following functions:

[0596] 1. User data management

[0597] Server: Manages user account information, daily input data, requests to the generated AI model, etc.

[0598] 2. Communication with the Generative AI Model

[0599] Server: Receives data sent from users and sends requests to the generated AI model to perform analysis and make suggestions.

[0600] 3. Managing Community Features

[0601] Server: Manages community functions, including sending and receiving messages and running forums. Also filters spam and inappropriate content.

[0602] Generative AI Models

[0603] The generative AI model will be implemented as an artificial intelligence system with the following functions:

[0604] 1. Data Analysis

[0605] Generative AI Model: Analyzes received user data and generates alternative activities suitable for the user's mood and environment on that day.

[0606] 2. Proposal generation

[0607] Generative AI Model: Based on the results of data analysis, it generates specific activity suggestions for the user. For example, if the user is experiencing high stress, it suggests relaxation methods; if the user has a strong urge to drink, it suggests alternative hobbies.

[0608] Specific example

[0609] 1. User Registration

[0610] User: Users download the app, enter their name, email address, and drinking frequency to register. The server receives this information and stores it in its database.

[0611] 2. Daily data entry

[0612] User: Enters their mood and circumstances for the day into the app. For example, they might enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." The device then sends this information to the server.

[0613] 3. Proposal generation and presentation

[0614] Server: Sends data to the generative AI model and requests suggestions. The generative AI model analyzes the data and generates specific activities such as "Join an online yoga session now" or "Watch a new movie."

[0615] Terminal: Receives suggestions and displays them to the user. The user can select and perform the suggested activities.

[0616] 4. Use of community features

[0617] Users interact with other users through chat and forums, sharing experiences and opinions. The server manages this.

[0618] 5. Integration with smartwatches

[0619] User: Wears a smartwatch and connects it to the app. The device collects heart rate and stress levels and sends them to the server. The generated AI model uses this data to make more specific suggestions.

[0620] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle.

[0621] The following describes the processing flow.

[0622] Step 1: User Registration

[0623] User: Launch the app for the first time and enter basic information such as name, email address, and daily drinking frequency.

[0624] Terminal: Sends the entered information to the server.

[0625] Server: Stores the received information in the database and returns a success message for account creation to the terminal.

[0626] Terminal: Displays a success message to the user.

[0627] Step 2: Data Entry

[0628] User: Enter information about your mood and environment for the day into the app. For example, you might report, "I'm feeling stressed today," or "I have a strong urge to drink."

[0629] Terminal: Sends the entered data to the server.

[0630] Server: Receives data and saves it to the database.

[0631] Step 3: Request analysis from the generative AI model

[0632] Server: Sends the stored data to the generating AI model for analysis. Specifically, it sends a POST request to the generating AI model.

[0633] Generative AI Model: Analyzes received data and generates optimal alternative activities for the user. For example, it can suggest online yoga sessions or movie viewings.

[0634] Generative AI model: Returns the generated suggestions to the server.

[0635] Step 4: Providing and displaying proposals

[0636] Server: Receives suggestions from the generated AI model and sends them to the user's terminal.

[0637] Device: Receives suggestions and displays them to the user. For example, it displays a link to "Online yoga sessions you can join now" on the app's home screen.

[0638] Step 5: Utilizing Community Features

[0639] Users: Utilize community features to interact with other users. For example, share experiences and opinions in chats and forums.

[0640] Terminal: Sends user messages to the server and receives and displays messages from other users.

[0641] Server: Sends messages to other relevant user terminals and manages community features. It also filters spam and inappropriate content.

[0642] Step 6: Connecting with a smartwatch (optional)

[0643] User: Wear the smartwatch and connect it to the app.

[0644] Device: Acquires biometric data such as heart rate and stress level from the smartwatch and sends it to the server.

[0645] Server: Sends the received biometric data to the AI ​​model for generation.

[0646] Generative AI models: These models generate more specific suggestions based on biometric data. For example, they might suggest deep breathing exercises if the heart rate is high.

[0647] Server: Sends the generated proposal to the terminal.

[0648] Terminal: Notifies the user of suggestions. For example, it displays a notification such as, "Take three deep breaths right now."

[0649] In this way, the system helps users control their cravings for alcohol in a healthy manner.

[0650] (Example 1)

[0651] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0652] Traditional alcohol reduction systems lacked the ability to suggest alternative activities tailored to each user's individual circumstances and psychological state. This made it difficult for users to actually refrain from drinking. Furthermore, they lacked features for collaboration with other users through community functions and systems capable of providing personalized suggestions based on real-time biometric data. As a result, it was difficult to motivate users and achieve long-term alcohol reduction.

[0653] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0654] In this invention, the server includes means for receiving mood and environmental data from the user, means for analyzing the received data and generating alternative activities for the user using a generative artificial intelligence model, means for presenting the generated alternative activities to the user, and means for collecting biometric data in conjunction with a corresponding bio-device and generating alternative activities based on the collected biometric data. This makes it possible to suggest alternative activities that are tailored to the individual circumstances and psychology of the user, thereby enabling long-term alcohol suppression.

[0655] "User" refers to an individual who uses the system.

[0656] "Mood" refers to data that indicates the user's emotions and mental state.

[0657] "Environmental data" refers to information about the physical or psychological environment in which a user is placed.

[0658] "Analysis" refers to the process of processing received data to extract useful information.

[0659] A "generative artificial intelligence model" refers to an AI system that generates alternative activities based on received data.

[0660] "Alternative activities" refer to activities or tasks that users can undertake to reduce their alcohol consumption.

[0661] "Presentation" refers to the act of informing the user of the generated alternative activity.

[0662] "Biometric devices" refer to wearable devices and sensors that collect users' biometric data.

[0663] "Biometric data" refers to data that indicates a user's physical condition or health status.

[0664] "Community features" refer to functions that allow users to connect and interact with other users who have similar problems.

[0665] "Suggestions" refer to recommended activities and methods provided to users based on analyzed data.

[0666] "Means of receiving" refers to devices or functions used to receive data from users.

[0667] "Means of transmission" refers to devices or functions used to send data or requests to other systems.

[0668] "Means of generation" refers to devices or functions used to analyze data and produce specific results.

[0669] "Means of collection" refers to the devices or functions used to collect data.

[0670] This invention is a system that provides behavioral support to help users reduce their alcohol consumption, and is primarily implemented by combining a user terminal (smartphone application), a server, and a generative AI model. The specific implementation methods of these components are described in detail below.

[0671] User device (smartphone app)

[0672] The user device will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[0673] 1. User registration and login function

[0674] Users: When launching the app for the first time, create an account by entering basic information such as your name, email address, and drinking frequency. If you already have an account, access it using the login function.

[0675] Terminal: Sends the entered information to the server, which then stores it in the database.

[0676] 2. Data Input Interface

[0677] User: Uses an interface to input data about daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[0678] Terminal: Sends the entered data to the server.

[0679] 3. Receiving and displaying proposals

[0680] Terminal: Receives suggestions from the generating AI model and displays them to the user. For example, it might suggest specific activities such as "Join an online yoga session" or "Watch a new movie."

[0681] 4. Community Features

[0682] Users can utilize community features that allow them to interact with other users who share similar concerns. Information exchange and support are provided through chat and forums.

[0683] 5. Integration with smartwatches

[0684] Device: It works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current state in real time and suggests appropriate activities.

[0685] Server-side functionality

[0686] The server will be implemented as a cloud-based system with the following functions:

[0687] 1. User data management

[0688] Server: Manages user account information, daily input data, requests to generated AI models, etc.

[0689] 2. Communication with the Generative AI Model

[0690] Server: Receives data sent by the user and sends a request to the generative AI model to perform analysis and make suggestions. Specifically, it uses prompt statements to request data analysis from the generative AI model.

[0691] Example prompt: "The user is currently experiencing significant stress and has a strong urge to drink alcohol. What alternative activity would you suggest?"

[0692] 3. Managing Community Features

[0693] Server: Manages community functions, including sending and receiving messages and running forums. Also filters spam and inappropriate content.

[0694] Generative AI Models

[0695] The generative AI model will be implemented as an artificial intelligence system with the following functions:

[0696] 1. Data Analysis

[0697] Generative AI Model: Analyzes user data received from the server and generates alternative activities suitable for the user's mood and environment on that day. Specifically, it performs analysis and makes suggestions based on prompt messages.

[0698] 2. Proposal generation

[0699] Generative AI Model: Based on the results of data analysis, it generates specific activity suggestions for the user. For example, if the user is experiencing high stress, it might suggest relaxation methods; if the user has a strong urge to drink, it might suggest alternative hobbies.

[0700] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle. This makes it possible to suggest alternative activities tailored to each user's individual circumstances and psychology, thereby achieving long-term alcohol reduction.

[0701] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0702] Step 1: User registration and login

[0703] Specific actions:

[0704] User: Download and launch the app.

[0705] Input: Users enter basic information such as their name, email address, and frequency of drinking.

[0706] Terminal: Sends the entered information to the server.

[0707] Server: Saves the received registration information to the database and generates a registration completion message.

[0708] Output: The server sends a registration completion message to the terminal.

[0709] User: Enter your existing account information (email address and password) to log in.

[0710] Terminal: Sends login information to the server.

[0711] Server: The server checks against the database and, if authentication is successful, approves the login.

[0712] Output: Sends the authentication result to the terminal.

[0713] Step 2: Daily data entry

[0714] Specific actions:

[0715] User: Open the app and enter data about your mood and environment for the day (e.g., "I'm feeling stressed today," "I have a strong urge to drink").

[0716] Input: Data about the user's daily mood and environment.

[0717] Terminal: Formats the data and sends it to the server.

[0718] Server: Receives data and saves it to the database.

[0719] Output: Generates a data saving confirmation message and sends it to the terminal.

[0720] Step 3: Send data to the server

[0721] Specific actions:

[0722] Terminal: Once data entry is complete, the terminal sends the data to the server.

[0723] Input: User data sent by the device.

[0724] Server: Stores received data in the database and prepares requests for the generated AI model.

[0725] Output: Generates a data saving confirmation message and sends it to the terminal.

[0726] Step 4: Data analysis and proposal generation using generative AI models

[0727] Specific actions:

[0728] Server: Formats the data sent by the user and generates a request to send to the generated AI model.

[0729] Server: Sends an example prompt message, "The user is currently experiencing significant stress and has a strong urge to drink alcohol. What alternative activities would you suggest?" to the generating AI model.

[0730] Input: Prompt message and user data.

[0731] Generative AI model: Analyzes received data and generates optimal alternative activities for the user.

[0732] Output: The analysis results (e.g., "Participate in an online yoga session," "Watch a new movie") are sent back to the server.

[0733] Step 5: Receiving and displaying proposals

[0734] Specific actions:

[0735] Server: Sends suggestions received from the generated AI model to the user's terminal.

[0736] Input: Suggestions from a generative AI model.

[0737] Terminal: Displays received suggestions to the user.

[0738] Output: Suggestions are displayed on the user's screen (e.g., "Join an online yoga session," "Watch a new movie").

[0739] Step 6: Using Community Features

[0740] Specific actions:

[0741] Users: Interact with other users through chat and forums using the in-app community features.

[0742] Input: User messages or posts.

[0743] Server: Manages community messages and posts, and filters out spam and inappropriate content.

[0744] Output: Messages and posts within the community are displayed.

[0745] Step 7: Collect and transmit smartwatch data

[0746] Specific actions:

[0747] User: Wear the smartwatch and connect it to the app.

[0748] Input: Biometric data collected by the smartwatch (e.g., heart rate, stress level).

[0749] Terminal: Sends collected biometric data to the server.

[0750] Server: Sends received biometric data to a generating AI model and makes a request to generate specific suggestions.

[0751] Output: The suggestions generated by the generative AI model are presented to the user again.

[0752] The above describes the specific processing flow of this system's program.

[0753] (Application Example 1)

[0754] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0755] In modern society, health problems caused by alcohol consumption are on the rise, making prevention crucial. However, many people find it difficult to find alternative activities to avoid alcohol. Furthermore, many people who want to avoid alcohol lack access to helpful information and support. The lack of concrete alternative activity suggestions in physical stores is also a challenge.

[0756] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0757] In this invention, the server includes means for receiving mood and environmental data from the user, means for analyzing the received data and using a generative AI model to generate alternative activities for the user, means for presenting the generated alternative activities to the user, and means for suggesting alternative activities that can be used in physical stores. This makes it possible for users to easily find activities other than alcohol, and further promote a healthier lifestyle by experiencing these activities in physical stores.

[0758] A "user" is someone who uses the system to receive suggestions for alternative activities to reduce alcohol consumption.

[0759] "Mood and environmental data" refers to data that indicates the user's mood, stress level, physical condition, etc., at any given time.

[0760] A "generative AI model" is an artificial intelligence model used to analyze data received from users and generate optimal alternative activities.

[0761] "Alternative activities" refer to activities or behaviors that can be done instead of consuming alcohol.

[0762] A "physical store" refers to a store that is a real physical location, such as a cafe, a gym, or a movie theater.

[0763] "Biometric data" refers to data indicating a person's physical condition, such as heart rate and stress levels, obtained from smartwatches and other wearable devices.

[0764] "Community features" refer to functions that allow users with similar problems to connect and interact with each other.

[0765] This invention relates to a comprehensive support system for users to reduce alcohol consumption and maintain a healthy lifestyle through alternative activities. The entire system consists of a smartphone app, a cloud-based server, a generative AI model, and wearable devices such as smartwatches.

[0766] User device (smartphone app)

[0767] The user device will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[0768] 1. User registration and login function

[0769] When a user first launches the app, they create an account by entering basic information such as their name, email address, and drinking frequency. If they already have an account, they can access it using the login function.

[0770] 2. Data Input Interface

[0771] Users utilize an interface to input data about their daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[0772] 3. Receiving and displaying proposals

[0773] The device receives suggestions from the generated AI model and displays them to the user. For example, it might suggest specific activities such as "Take a break at a nearby cafe" or "Participate in a relaxation session at a gym."

[0774] 4. Community Features

[0775] Users can utilize community features that allow them to interact with other users who share similar concerns. Information exchange and support are provided through chat and forums.

[0776] 5. Integration with smartwatches

[0777] The device works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current status in real time and suggests appropriate activities. Hardware options include Apple Watch and Fitbit.

[0778] Server-side functionality

[0779] The server will be implemented as a cloud-based system with the following functions:

[0780] 1. User data management

[0781] The server manages user account information, daily input data, and requests to the generated AI model. Databases such as PostgreSQL are used.

[0782] 2. Communication with the Generative AI Model

[0783] The server receives data sent by the user and sends a request to the generative AI model to perform analysis and provide suggestions. Generative AI models such as TensorFlow and GPT-4 are used.

[0784] 3. Managing Community Features

[0785] The server manages community functions, including sending and receiving messages and running forums. It also filters spam and inappropriate content.

[0786] Generative AI Models

[0787] The generative AI model will be implemented as an artificial intelligence system with the following functions:

[0788] 1. Data Analysis

[0789] The generative AI model analyzes the received user data and generates alternative activities that are suitable for the user's mood and environment on that day.

[0790] 2. Proposal generation

[0791] The generative AI model generates specific activity suggestions for the user based on the results of data analysis. For example, if the user is experiencing high stress levels, it might suggest relaxation methods; if they have a strong urge to drink, it might suggest alternative hobbies.

[0792] Specific example

[0793] 1. User Registration

[0794] The user downloads the app, enters their name, email address, and drinking frequency to register. The server receives this information and stores it in its database.

[0795] 2. Daily data entry

[0796] The user inputs their mood and circumstances for the day into the app. For example, they might enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." The device then sends this information to the server.

[0797] 3. Proposal generation and presentation

[0798] The server sends data to a generative AI model and requests suggestions. The generative AI model analyzes the data and generates specific activities such as "take a break at a nearby cafe" or "participate in a relaxation session at a gym." The terminal receives the suggestions and displays them to the user. The user can then select and perform one of the suggested activities.

[0799] 4. Use of community features

[0800] Users interact with other users through chat and forums, sharing experiences and opinions. The server manages this.

[0801] 5. Integration with smartwatches

[0802] The user wears a smartwatch and connects it to an app. The device collects heart rate and stress levels and sends them to a server. The generated AI model then uses this data to make more specific suggestions.

[0803] Example of a prompt

[0804] "The user is under a lot of stress and busy at work, so they need relaxation. Their current mood is normal, and they want to avoid alcohol. Please suggest some activities they can enjoy around the store."

[0805] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0806] Step 1:

[0807] Users download a smartphone app, enter their name, email address, and drinking frequency to create an account. The entered information is sent from the device to a cloud server.

[0808] Step 2:

[0809] The server stores the received user registration information in the database and generates a user ID. The server verifies the stored data and sends a registration success message back to the user.

[0810] Step 3:

[0811] Users input data about their daily mood and environment into a smartphone app. For example, they might enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." This data is then sent from the device to a server.

[0812] Step 4:

[0813] The server stores the received mood and environment data in a database. It generates prompts to send the stored data to the AI ​​model and prepares it for transmission to the AI ​​model.

[0814] Step 5:

[0815] The generative AI model receives a prompt message and analyzes the user's mood and environmental data. Based on the analysis, it suggests specific and appropriate alternative activities, such as taking a break at a nearby cafe or a relaxation session at a gym.

[0816] Step 6:

[0817] The server stores the suggestions received from the generated AI model in a database and sends them to the user's terminal. The terminal then displays the received suggestions to the user.

[0818] Step 7:

[0819] Users select and perform activities from the suggested options. Furthermore, they can utilize community features to interact with other users who share similar concerns.

[0820] Step 8:

[0821] Biometric data (such as heart rate and stress level) from the user wearing the smartwatch is transmitted to the device in real time. The device then sends this data to the server.

[0822] Step 9:

[0823] The server stores the received biometric data in a database and generates prompts based on this data to request new suggestions from the generative AI model. The generative AI model analyzes the biometric data in real time and generates new alternative activities.

[0824] Step 10:

[0825] The server sends the generated new suggestions to the user's device, which then displays them to the user. The user can then select and experience the activities that interest them most.

[0826] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0827] This invention relates to a system that provides users with beneficial alternative activities and community features to help them avoid health damage caused by alcohol consumption, as well as an emotion recognition function using an emotion engine. This system is mainly implemented by combining a user terminal (smartphone application), a server, a generative AI model, and an emotion engine.

[0828] User device (smartphone app)

[0829] The user device will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[0830] 1. User registration and login function

[0831] Users: When launching the app for the first time, create an account by entering basic information such as your name, email address, and drinking frequency. If you already have an account, access it using the login function.

[0832] 2. Data Input Interface

[0833] User: Uses an interface to input data about daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[0834] 3. Receiving and displaying proposals

[0835] Terminal: Receives suggestions from the generative AI model and emotion engine and displays them to the user. For example, it may suggest specific activities such as "Join an online yoga session" or "Watch a new movie."

[0836] 4. Community Features

[0837] Users can utilize community features to interact with other users who share similar concerns. They can exchange information and provide support through chat and forums.

[0838] 5. Integration with smartwatches

[0839] Device: It works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current state in real time and suggests appropriate activities.

[0840] 6. Emotional Engine

[0841] Device: The emotion engine analyzes voice and facial expression data to recognize the user's emotions. Based on this emotion data, a generative AI model suggests more accurate alternative activities.

[0842] Server-side functionality

[0843] The server will be implemented as a cloud-based system with the following functions:

[0844] 1. User data management

[0845] Server: Manages user account information, daily input data, requests to generative AI models and emotion engines, etc.

[0846] 2. Communication with generative AI models and emotion engines

[0847] Server: Receives data sent from users and sends requests to the generative AI model and emotion engine to perform analysis and make suggestions.

[0848] 3. Managing Community Features

[0849] Server: Manages community functions, including sending and receiving messages and running forums. Also filters spam and inappropriate content.

[0850] Generative AI models and emotion engines

[0851] The generative AI model and emotion engine will be implemented as an artificial intelligence system with the following functions:

[0852] 1. Data analysis and sentiment recognition

[0853] Generative AI Model: Analyzes received user data and generates alternative activities suitable for the user's mood and environment on that day.

[0854] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotional state. This emotional data is then provided to the AI ​​model for generating more personalized suggestions.

[0855] 2. Proposal generation

[0856] Generative AI Model: Based on data analysis and emotion recognition results, it generates specific activity suggestions for the user. For example, if stress levels are high and emotion recognition identifies "irritation," it will suggest relaxation methods.

[0857] Specific example

[0858] 1. User Registration

[0859] User: Users download the app, enter their name, email address, and drinking frequency to register. The server receives this information and stores it in its database.

[0860] 2. Daily data entry

[0861] User: Enters their mood and circumstances for the day into the app. For example, they might enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." The device then sends this information to the server.

[0862] 3. Analysis of voice and facial expressions

[0863] User: Speak to the app using voice commands or turn your face towards the camera.

[0864] Terminal: Acquires voice data and facial expression data and sends it to the emotion engine.

[0865] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotions. For example, it might generate a result such as "irritated."

[0866] 4. Proposal generation and presentation

[0867] Server: Sends data to the generative AI model and emotion engine and requests suggestions. The generative AI model generates specific activities based on data analysis and emotion recognition results.

[0868] Terminal: Receives suggestions and displays them to the user. The user can select and perform the suggested activities (e.g., relaxation methods or hobbies).

[0869] 5. Use of community features

[0870] Users interact with other users through chat and forums, sharing experiences and opinions. The server manages this.

[0871] 6. Integration with smartwatches

[0872] User: Wears a smartwatch and connects it to the app. The device collects heart rate and stress levels and sends them to the server. The generative AI model and emotion engine then use this data to make more specific suggestions.

[0873] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle.

[0874] The following describes the processing flow.

[0875] Step 1: User Registration

[0876] User: Launch the app for the first time and enter basic information such as name, email address, and daily drinking frequency.

[0877] Terminal: Sends the entered information to the server.

[0878] Server: Stores the received information in the database and returns a success message for account creation to the terminal.

[0879] Terminal: Displays a success message to the user.

[0880] Step 2: Data Entry

[0881] User: Enter information about your mood and environment for the day into the app. For example, you might report, "I'm feeling stressed today," or "I have a strong urge to drink."

[0882] Terminal: Sends the entered data to the server.

[0883] Server: Receives data and saves it to the database.

[0884] Step 3: Request analysis from generative AI models and emotion engines.

[0885] Server: Sends stored data to the generative AI model and sentiment engine for analysis. Specifically, it sends POST requests to the generative AI model and sentiment engine.

[0886] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotions. The results of the emotion recognition are then sent to a generating AI model.

[0887] Generative AI Model: Based on received data and emotion recognition results, it generates optimal alternative activities for the user. For example, it suggests relaxation methods or hobby-related activities.

[0888] Generative AI model: Returns the generated suggestions to the server.

[0889] Step 4: Providing and displaying proposals

[0890] Server: Receives suggestions from the generative AI model and emotion engine, and sends them to the user's terminal.

[0891] Device: Receives suggestions and displays them to the user. For example, it displays a link to "Online yoga sessions you can join now" on the app's home screen.

[0892] Step 5: Utilizing Community Features

[0893] Users: Utilize community features to interact with other users. For example, share experiences and opinions in chats and forums.

[0894] Terminal: Sends user messages to the server and receives and displays messages from other users.

[0895] Server: Sends messages to other relevant user terminals and manages community features. It also filters spam and inappropriate content.

[0896] Step 6: Connecting with a smartwatch (optional)

[0897] User: Wear the smartwatch and connect it to the app.

[0898] Device: Acquires biometric data such as heart rate and stress level from the smartwatch and sends it to the server.

[0899] Server: Sends received biometric data to the generating AI model and emotion engine.

[0900] Generative AI Model: Generates more specific suggestions based on biometric data and emotion recognition results. For example, it might suggest deep breathing exercises if the heart rate is high.

[0901] Server: Sends the generated proposal to the terminal.

[0902] Terminal: Notifies the user of suggestions. For example, it displays a notification such as, "Take three deep breaths right now."

[0903] In this way, the system helps users control their cravings for alcohol in a healthy manner.

[0904] (Example 2)

[0905] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0906] In recent years, health problems caused by alcohol consumption have become a social issue. Therefore, effective measures to reduce alcohol consumption are needed. However, conventional technologies struggle to suggest personalized alternative activities tailored to the user's mood and environment, and advanced analysis based on users' emotional states and biometric data is lacking. Furthermore, opportunities for connection and interaction with other users who share similar concerns are insufficient.

[0907] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0908] In this invention, the server includes means for receiving mood and environmental data from the user, means including a generative AI model that analyzes the received data and generates alternative activities for the user, means for presenting the generated alternative activities to the user, means including an emotion engine that analyzes the user's voice and facial expression data and recognizes their emotional state, and means for generating alternative activities based on the analyzed emotional state. As a result, the user can receive personalized alternative activity suggestions that match their mood and emotional state, enabling effective support for reducing alcohol consumption. Furthermore, it is also possible to include a community function for collaborating and interacting with other users who have similar concerns, and to collect biometric data in conjunction with a smartwatch to provide more accurate suggestions.

[0909] A "user" is a person who uses the system, creates an account, and inputs data about their daily mood and environment.

[0910] "Mood and environmental data" refers to information about the user's daily mood and psychological state, as well as the environment and circumstances of that day.

[0911] "Means of receiving data" refers to an interface equipped with the function of collecting data from users and transmitting it to a server or analysis system.

[0912] A "generative AI model" refers to an artificial intelligence system that analyzes received data and generates alternative activities suitable for the user based on the analysis results.

[0913] "Alternative activities" refer to beneficial activities or methods suggested by the system to reduce alcohol consumption, and are generated based on the user's mood and emotional state.

[0914] "Means of presentation" refers to interfaces and devices used to display suggestions from generative AI models and emotion engines to users.

[0915] An "emotion engine" refers to a system that analyzes a user's voice and facial expression data to recognize their emotional state.

[0916] "Voice and facial expression data" refers to biometric data that includes information about the voice and facial expressions emitted by the user, and is the subject of analysis by the emotion engine.

[0917] "Community features" refer to chat and forum functions that allow users to exchange information and support each other with other users who have similar problems.

[0918] A "smartwatch" refers to a wearable device that collects biometric data such as the user's heart rate and stress level, and transmits it to the user's device or a server.

[0919] "Biometric data" refers to information about a user's physical condition, such as heart rate and stress level, collected through devices like smartwatches.

[0920] This invention relates to a system that provides users with beneficial alternative activities and community features to help them avoid health damage caused by alcohol consumption, as well as an emotion recognition function using an emotion engine. This system is mainly implemented by combining a user terminal (smartphone application), a server, a generative AI model, and an emotion engine.

[0921] User device (smartphone app)

[0922] The user terminal will be implemented as a smartphone application for daily use by the user. This application will have the following functions:

[0923] 1. User registration and login function

[0924] Users: When launching the app for the first time, create an account by entering information such as your name, email address, and drinking frequency. If you already have an account, log in by entering your email address and password.

[0925] Terminal: Sends the entered information to the server to create a new account or authenticate login.

[0926] 2. Data Input Interface

[0927] User: Enter data about your daily mood and environment. For example, enter information such as "I'm feeling stressed today" or "I have a strong urge to drink" into the app.

[0928] Terminal: Sends the entered data to the server.

[0929] 3. Receiving and displaying proposals

[0930] Terminal: Receives suggestions from the generative AI model and emotion engine and displays them to the user. For example, specific activities such as "join an online yoga session" or "watch a new movie" may be suggested.

[0931] 4. Community Features

[0932] Users: Utilize community features to interact with other users who share similar concerns. Exchange information and support through chat and forums.

[0933] Server: Manages these community features, including sending and receiving messages and running forums. Also filters spam and inappropriate content.

[0934] 5. Integration with smartwatches

[0935] User: Wear a smartwatch and connect it to the app. The device collects biometric data such as heart rate and stress level.

[0936] Terminal: Sends collected biometric data to the server.

[0937] 6. Emotional Engine

[0938] Device: The emotion engine analyzes voice and facial expression data to recognize the user's emotions. Based on this emotion data, a generative AI model suggests more accurate alternative activities.

[0939] Server-side functionality

[0940] The server has the following functions and will be implemented as a cloud-based system:

[0941] 1. User data management

[0942] Server: Manages user account information, daily input data, and requests to the generative AI model and sentiment engine.

[0943] 2. Communication with generative AI models and emotion engines

[0944] Server: Receives data sent from users and sends requests to the generative AI model and emotion engine to perform analysis and make suggestions.

[0945] 3. Managing Community Features

[0946] Server: Manages community functions, including sending and receiving messages and running forums. Also performs filtering of inappropriate content.

[0947] Generative AI models and emotion engines

[0948] The generative AI model and emotion engine will be implemented as an artificial intelligence system with the following functions:

[0949] 1. Data analysis and sentiment recognition

[0950] Generative AI Model: Analyzes received user data and generates alternative activities suitable for the user's mood and environment on that day.

[0951] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotional state. This emotional data is then provided to the AI ​​model for generating more personalized suggestions.

[0952] 2. Proposal generation

[0953] Generative AI Model: Based on data analysis and emotion recognition results, it generates specific activity suggestions for the user. For example, if stress levels are high and emotion recognition reveals "irritation," it will suggest relaxation methods.

[0954] Specific example

[0955] 1. User Registration

[0956] User: Downloads the app, enters their name, email address, and drinking frequency to register. The server receives this information and stores it in its database.

[0957] 2. Daily data entry

[0958] User: Enters their mood and circumstances for the day into the app. They enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." The device then sends this information to the server.

[0959] 3. Analysis of voice and facial expressions

[0960] User: Speak to the app using voice commands or turn your face towards the camera.

[0961] The device acquires voice and facial expression data and sends it to the emotion engine. The emotion engine analyzes this data and recognizes the user's emotional state. For example, it might generate a result such as "irritated."

[0962] 4. Proposal generation and presentation

[0963] Server: Sends data to the generative AI model and emotion engine and requests suggestions. The generative AI model generates specific activities based on data analysis and emotion recognition results.

[0964] Terminal: Receives suggestions and displays them to the user. The user can select and perform the suggested activities (e.g., "relaxation methods" or "hobby activities").

[0965] 5. Use of community features

[0966] Users interact with other users through chat and forums, sharing experiences and opinions. The server manages this.

[0967] 6. Integration with smartwatches

[0968] User: Wears a smartwatch and connects it to the app. The device collects heart rate and stress levels and sends them to the server. The generative AI model and emotion engine then use this data to make more specific suggestions.

[0969] Examples of prompt statements

[0970] 1. A stressful day

[0971] User: Enter "I'm feeling particularly stressed today, so please tell me some relaxation techniques" as the prompt.

[0972] Generative AI model: Based on the received prompt, it suggests specific relaxation methods (e.g., "Do deep breathing exercises," "Try aromatherapy").

[0973] 2. Days when the urge to drink is strong

[0974] User: Enter the following as the prompt: "I have a strong urge to drink alcohol, so I would like suggestions for alternative hobbies or activities."

[0975] Generative AI model: Based on user sentiment data and daily data analysis results, it suggests hobby activities (e.g., "drawing pictures," "reading books").

[0976] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle.

[0977] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0978] Step 1:

[0979] User Registration / Login

[0980] User: When launching the app for the first time, you will create an account by entering basic information such as your name, email address, and frequency of drinking.

[0981] Terminal: Sends the entered user information to the server.

[0982] Server: Receives user information and stores it in the database. If an existing account exists, it receives the email address and password and verifies them against the database. If authentication is successful, it starts the session.

[0983] Input: The user's basic information is entered here.

[0984] Output: The results of account creation and authentication on the server are output.

[0985] Step 2:

[0986] Daily data entry

[0987] User: Launch the app and enter data about your mood and environment for the day. Specifically, enter information such as "I'm feeling stressed today" or "I have a strong urge to drink."

[0988] Terminal: Sends the entered data to the server.

[0989] Server: Receives data, links it to user information, and saves it to the database.

[0990] Input: Daily data related to mood and environment is entered.

[0991] Output: Daily data stored in the database is output.

[0992] Step 3:

[0993] Collection and analysis of emotional data

[0994] User: Speak to the app using voice commands or turn your face towards the camera.

[0995] Terminal: Collects voice data and facial expression data and sends it to the emotion engine.

[0996] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotional state. For example, it generates results such as "irritated."

[0997] Terminal: Sends analysis results to the server.

[0998] Input: Voice data and facial expression data are input.

[0999] Output: The analysis results of the emotion engine are output.

[1000] Step 4:

[1001] Proposal generation and presentation

[1002] Server: Inputs daily data and sends emotional data to the AI ​​model for analysis and recommendations.

[1003] Generative AI Model: Analyzes received data and generates specific activity suggestions. For example, if it detects high stress levels, it will suggest "relaxation methods."

[1004] Server: Receives suggestions from the generated AI model and sends them to the user's terminal.

[1005] Terminal: Receives suggestions and displays the suggestions to the user. The user can select and perform the suggested activities.

[1006] Input: Daily data and sentiment data are entered.

[1007] Output: Activity suggestions generated by the generative AI model are output.

[1008] Step 5:

[1009] Using community features

[1010] Users: Utilize the app's community features to interact with other users through chat and forums.

[1011] Server: Manages message sending and receiving, forum operation, and filters inappropriate content.

[1012] Input: Messages and posts from the community are entered here.

[1013] Output: Information about community features managed by the server is output.

[1014] Step 6:

[1015] Collection and linkage of biometric data

[1016] User: Wear the smartwatch and connect it to the app.

[1017] Device: Collects biometric data such as heart rate and stress level from the smartwatch and sends it to the server.

[1018] Server and Generative AI Model: Generates more specific suggestions based on received biometric data.

[1019] Terminal: Displays specific activity suggestions to the user from the generated AI model.

[1020] Input: Biometric data from a smartwatch is entered.

[1021] Output: Specific activity suggestions generated by the AI ​​model are output.

[1022] Through these steps, the system provides users with personalized alternative activity suggestions and offers effective support for reducing alcohol consumption.

[1023] (Application Example 2)

[1024] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1025] In modern society, the health risks associated with alcohol consumption are a major problem. In particular, because moderate alternative activities are not readily available, many people try to relieve stress and cravings with alcohol. However, there is a lack of specific and personalized suggestions tailored to individual circumstances. Therefore, there is a need for effective support systems to help users maintain a healthy lifestyle.

[1026] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1027] In this invention, the server includes means for receiving mood and environmental data from the user, means for analyzing the received data and generating alternative activities for the user using a generative AI model, means for presenting the generated alternative activities to the user, means for analyzing the user's voice and facial expression data using an emotion recognition engine and identifying their emotional state, and means for the generative AI model to suggest even more accurate alternative activities based on the emotional state. As a result, the user can receive personalized alternative activity suggestions based on their emotional state and biometric data, making it easier to maintain a healthy lifestyle.

[1028] "User" refers to an individual who uses the system.

[1029] "Mood and environmental data" refers to information about the user's everyday emotions and surrounding circumstances.

[1030] "Means of receiving" refers to methods and devices for securing data transmitted by users.

[1031] "Means of analysis" refers to methods and devices that analyze received data to derive meaningful information.

[1032] A "generative AI model" refers to an artificial intelligence algorithm that generates new suggestions and activities based on received and analyzed data.

[1033] "Alternative activities" refer to beneficial activities or hobbies that help prevent drinking.

[1034] "Means of presentation" refers to the methods or devices used to show the generated activities or suggestions to the user.

[1035] An "emotion recognition engine" refers to a system that analyzes voice and facial expression data to identify the user's emotional state.

[1036] "Voice and facial expression data" refers to information about the user's voice and facial expressions.

[1037] "Biometric data" refers to physical information such as heart rate and stress levels collected using devices like smartwatches.

[1038] "Community features" refer to online platforms that allow users to exchange information and support each other with similar problems.

[1039] The system of the present invention is composed of a user terminal, a server, a generative AI model, an emotion recognition engine, and biosensor devices such as a smartwatch.

[1040] User terminal (smartphone app)

[1041] The user terminal will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[1042] 1. User registration and login function

[1043] Users create an account upon first launch by entering basic information such as their name, email address, and frequency of drinking. If an existing account exists, they can access it using the login function.

[1044] 2. Data Input Interface

[1045] Users utilize an interface to input data about their daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[1046] 3. Receiving and displaying proposals

[1047] The device receives suggestions from the generative AI model and emotion recognition engine and displays them to the user. For example, it may suggest specific activities such as "join an online yoga session" or "watch a new movie."

[1048] 4. Community Features

[1049] Users can utilize community features to interact with other users who share similar concerns. Information exchange and support are provided through chat and forums.

[1050] 5. Integration with smartwatches

[1051] The device works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current state in real time and suggests appropriate activities.

[1052] 6. Emotion Recognition Engine

[1053] The device uses an emotion recognition engine to analyze voice and facial expression data to recognize the user's emotions. Based on this emotion data, a generative AI model suggests more accurate alternative activities.

[1054] Server-side functionality

[1055] The server will be implemented as a cloud-based system with the following functions:

[1056] 1. User data management

[1057] The server manages user account information, daily input data, and requests to the generative AI model and emotion recognition engine.

[1058] 2. Communication with generative AI models and emotion recognition engines

[1059] The server receives data sent by the user and sends requests to the generative AI model and emotion recognition engine to perform analysis and make suggestions.

[1060] 3. Managing Community Features

[1061] The server manages community functions, including sending and receiving messages and running forums. It also filters spam and inappropriate content.

[1062] Generative AI models and emotion recognition engines

[1063] The generative AI model and emotion recognition engine will be implemented as an artificial intelligence system with the following functions:

[1064] 1. Data analysis and sentiment recognition

[1065] The generative AI model analyzes the received user data and generates alternative activities that are suitable for the user's mood and environment on that day.

[1066] The emotion recognition engine analyzes voice and facial expression data to recognize the user's emotional state. This emotional data is then provided to the AI ​​model for generating more personalized suggestions.

[1067] 2. Proposal generation

[1068] The generative AI model generates specific activity suggestions for the user based on data analysis and emotion recognition results. For example, if stress levels are high and emotion recognition identifies "irritation," it will suggest relaxation methods.

[1069] Presentation of specific examples and prompt statements

[1070] For example, the following prompt could represent emotional data when a user is feeling stressed.

[1071] Example of a prompt:

[1072] I'm feeling very stressed today. I have a strong urge to drink, but what can I do to control it?

[1073] Based on this data, the generated AI model and emotion recognition engine work together to suggest specific alternative activities.

[1074] Hardware and software to be used

[1075] User devices: Smartphones, smartwatches

[1076] Server: Cloud service platform (e.g., AWS, Google Cloud)

[1077] Generative AI models and emotion recognition engines: Deep learning frameworks (e.g., TensorFlow, PyTorch)

[1078] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle.

[1079] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1080] Step 1:

[1081] The user launches the smartphone app and uses the user registration / login function to enter basic information such as their name, email address, and frequency of drinking. This input data is received by the device and sent to the server. The server stores this data in a database.

[1082] Input: Name, email address, and basic information about your drinking frequency.

[1083] Output: User information stored in the server's database

[1084] Step 2:

[1085] Users report daily mood and environmental data using the in-app data input interface. For example, they might write, "I'm feeling stressed today" or "I have a strong urge to drink." This input data is then sent back to the server by the device and recorded.

[1086] Input: Data related to mood and environment

[1087] Output: Daily data sent to and recorded on the server

[1088] Step 3:

[1089] Users provide emotional data by speaking aloud or facing the camera. The device acquires the voice and facial expression data and sends it to an emotion recognition engine. The emotion recognition engine analyzes the data and identifies the user's emotional state. This result is then sent to a generative AI model.

[1090] Input: Voice data and facial expression data

[1091] Output: Identification of emotional state by emotion recognition engine

[1092] Step 4:

[1093] The server sends daily mood and environmental data, as well as emotional data from the emotion recognition engine, to a generative AI model. The generative AI model analyzes this data and generates alternative activities based on the user's current state. These activity suggestions are then sent to the server.

[1094] Input: Mood and environmental data, emotional data

[1095] Output: Suggestions for alternative activities using a generative AI model.

[1096] Step 5:

[1097] The server sends alternative activity suggestions received from the generated AI model to the terminal, and the user terminal displays them to the user. The user can then select and perform the displayed activity suggestion.

[1098] Input: Activity suggestions from a generated AI model

[1099] Output: Alternative activities displayed to the user

[1100] Step 6:

[1101] Users utilize the app's community features to interact with other users who share similar concerns through chat and forums. The server manages the community features, handling message sending and receiving, and running the forums.

[1102] Input: Chat messages and forum posts from users

[1103] Output: Information exchange and support with other users

[1104] Step 7:

[1105] Users wear biosensor devices such as smartwatches and connect them to the app. The device collects biometric data such as heart rate and stress levels from the smartwatch and sends it to a server. The server provides this biometric data to a generating AI model and emotion recognition engine, which then suggests more specific activities.

[1106] Input: Biometric data obtained from a smartwatch

[1107] Output: Specific activity suggestions generated by a generative AI model and emotion recognition engine.

[1108] Through these steps, the system provides effective support for reducing alcohol consumption and helps users maintain a healthy lifestyle.

[1109] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1110] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1111] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1112] [Third Embodiment]

[1113] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1114] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1115] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1116] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1117] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1118] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1119] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1120] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1121] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1122] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1123] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1124] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1125] This invention relates to a system that provides users with beneficial alternative activities and community features to help them avoid health problems caused by alcohol consumption. This system is primarily implemented by combining a user terminal (smartphone application), a server, and a generative AI model.

[1126] User device (smartphone app)

[1127] The user device will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[1128] 1. User registration and login function

[1129] Users: When launching the app for the first time, create an account by entering basic information such as your name, email address, and drinking frequency. If you already have an account, access it using the login function.

[1130] 2. Data Input Interface

[1131] User: Uses an interface to input data about daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[1132] 3. Receiving and displaying proposals

[1133] Terminal: Receives suggestions from the generating AI model and displays them to the user. For example, it might suggest specific activities such as "Join an online yoga session" or "Watch a new movie."

[1134] 4. Community Features

[1135] Users can utilize community features that allow them to interact with other users who share similar concerns. Information exchange and support are provided through chat and forums.

[1136] 5. Integration with smartwatches

[1137] Device: It works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current state in real time and suggests appropriate activities.

[1138] Server-side functionality

[1139] The server will be implemented as a cloud-based system with the following functions:

[1140] 1. User data management

[1141] Server: Manages user account information, daily input data, requests to the generated AI model, etc.

[1142] 2. Communication with the Generative AI Model

[1143] Server: Receives data sent from users and sends requests to the generated AI model to perform analysis and make suggestions.

[1144] 3. Managing Community Features

[1145] Server: Manages community functions, including sending and receiving messages and running forums. Also filters spam and inappropriate content.

[1146] Generative AI Models

[1147] The generative AI model will be implemented as an artificial intelligence system with the following functions:

[1148] 1. Data Analysis

[1149] Generative AI Model: Analyzes received user data and generates alternative activities suitable for the user's mood and environment on that day.

[1150] 2. Proposal generation

[1151] Generative AI Model: Based on the results of data analysis, it generates specific activity suggestions for the user. For example, if the user is experiencing high stress, it suggests relaxation methods; if the user has a strong urge to drink, it suggests alternative hobby activities.

[1152] Specific example

[1153] 1. User Registration

[1154] User: Users download the app, enter their name, email address, and drinking frequency to register. The server receives this information and stores it in its database.

[1155] 2. Daily data entry

[1156] User: Enters their mood and circumstances for the day into the app. For example, they might enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." The device then sends this information to the server.

[1157] 3. Proposal generation and presentation

[1158] Server: Sends data to the generative AI model and requests suggestions. The generative AI model analyzes the data and generates specific activities such as "Join an online yoga session now" or "Watch a new movie."

[1159] Terminal: Receives suggestions and displays them to the user. The user can select and perform the suggested activities.

[1160] 4. Use of community features

[1161] Users interact with other users through chat and forums, sharing experiences and opinions. The server manages this.

[1162] 5. Integration with smartwatches

[1163] User: Wears a smartwatch and connects it to the app. The device collects heart rate and stress levels and sends them to the server. The generated AI model uses this data to make more specific suggestions.

[1164] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle.

[1165] The following describes the processing flow.

[1166] Step 1: User Registration

[1167] User: Launch the app for the first time and enter basic information such as name, email address, and daily drinking frequency.

[1168] Terminal: Sends the entered information to the server.

[1169] Server: Stores the received information in the database and returns a success message for account creation to the terminal.

[1170] Terminal: Displays a success message to the user.

[1171] Step 2: Data Entry

[1172] User: Enter information about your mood and environment for the day into the app. For example, you might report, "I'm feeling stressed today," or "I have a strong urge to drink."

[1173] Terminal: Sends the entered data to the server.

[1174] Server: Receives data and saves it to the database.

[1175] Step 3: Request analysis from the generative AI model

[1176] Server: Sends the stored data to the generating AI model for analysis. Specifically, it sends a POST request to the generating AI model.

[1177] Generative AI Model: Analyzes received data and generates optimal alternative activities for the user. For example, it can suggest online yoga sessions or movie viewings.

[1178] Generative AI model: Returns the generated suggestions to the server.

[1179] Step 4: Providing and displaying proposals

[1180] Server: Receives suggestions from the generated AI model and sends them to the user's terminal.

[1181] Device: Receives suggestions and displays them to the user. For example, it displays a link to "Online yoga sessions you can join now" on the app's home screen.

[1182] Step 5: Utilizing Community Features

[1183] Users: Utilize community features to interact with other users. For example, share experiences and opinions in chats and forums.

[1184] Terminal: Sends user messages to the server and receives and displays messages from other users.

[1185] Server: Sends messages to other relevant user terminals and manages community features. It also filters spam and inappropriate content.

[1186] Step 6: Connecting with a smartwatch (optional)

[1187] User: Wear the smartwatch and connect it to the app.

[1188] Device: Acquires biometric data such as heart rate and stress level from the smartwatch and sends it to the server.

[1189] Server: Sends the received biometric data to the AI ​​model for generation.

[1190] Generative AI models: These models generate more specific suggestions based on biometric data. For example, they might suggest deep breathing exercises if the heart rate is high.

[1191] Server: Sends the generated proposal to the terminal.

[1192] Terminal: Notifies the user of suggestions. For example, it displays a notification such as, "Take three deep breaths right now."

[1193] In this way, the system helps users control their cravings for alcohol in a healthy manner.

[1194] (Example 1)

[1195] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1196] Traditional alcohol reduction systems lacked the ability to suggest alternative activities tailored to each user's individual circumstances and psychological state. This made it difficult for users to actually refrain from drinking. Furthermore, they lacked features for collaboration with other users through community functions and systems capable of providing personalized suggestions based on real-time biometric data. As a result, it was difficult to motivate users and achieve long-term alcohol reduction.

[1197] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1198] In this invention, the server includes means for receiving mood and environmental data from the user, means for analyzing the received data and generating alternative activities for the user using a generative artificial intelligence model, means for presenting the generated alternative activities to the user, and means for collecting biometric data in conjunction with a corresponding bio-device and generating alternative activities based on the collected biometric data. This makes it possible to suggest alternative activities that are tailored to the individual circumstances and psychology of the user, thereby enabling long-term alcohol suppression.

[1199] "User" refers to an individual who uses the system.

[1200] "Mood" refers to data that indicates the user's emotions and mental state.

[1201] "Environmental data" refers to information about the physical or psychological environment in which a user is placed.

[1202] "Analysis" refers to the process of processing received data to extract useful information.

[1203] A "generative artificial intelligence model" refers to an AI system that generates alternative activities based on received data.

[1204] "Alternative activities" refer to activities or tasks that users can undertake to reduce their alcohol consumption.

[1205] "Presentation" refers to the act of informing the user of the generated alternative activity.

[1206] "Biometric devices" refer to wearable devices and sensors that collect users' biometric data.

[1207] "Biometric data" refers to data that indicates a user's physical condition or health status.

[1208] "Community features" refer to functions that allow users to connect and interact with other users who have similar problems.

[1209] "Suggestions" refer to recommended activities and methods provided to users based on analyzed data.

[1210] "Means of receiving" refers to devices or functions used to receive data from users.

[1211] "Means of transmission" refers to devices or functions used to send data or requests to other systems.

[1212] "Means of generation" refers to devices or functions used to analyze data and produce specific results.

[1213] "Means of collection" refers to the devices or functions used to collect data.

[1214] This invention is a system that provides behavioral support to help users reduce their alcohol consumption, and is primarily implemented by combining a user terminal (smartphone application), a server, and a generative AI model. The specific implementation methods of these components are described in detail below.

[1215] User device (smartphone app)

[1216] The user device will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[1217] 1. User registration and login function

[1218] Users: When launching the app for the first time, create an account by entering basic information such as your name, email address, and drinking frequency. If you already have an account, access it using the login function.

[1219] Terminal: Sends the entered information to the server, which then stores it in the database.

[1220] 2. Data Input Interface

[1221] User: Uses an interface to input data about daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[1222] Terminal: Sends the entered data to the server.

[1223] 3. Receiving and displaying proposals

[1224] Terminal: Receives suggestions from the generating AI model and displays them to the user. For example, it might suggest specific activities such as "Join an online yoga session" or "Watch a new movie."

[1225] 4. Community Features

[1226] Users can utilize community features that allow them to interact with other users who share similar concerns. Information exchange and support are provided through chat and forums.

[1227] 5. Integration with smartwatches

[1228] Device: It works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current state in real time and suggests appropriate activities.

[1229] Server-side functionality

[1230] The server will be implemented as a cloud-based system with the following functions:

[1231] 1. User data management

[1232] Server: Manages user account information, daily input data, requests to generated AI models, etc.

[1233] 2. Communication with the Generative AI Model

[1234] Server: Receives data sent by the user and sends a request to the generative AI model to perform analysis and make suggestions. Specifically, it uses prompt statements to request data analysis from the generative AI model.

[1235] Example prompt: "The user is currently experiencing significant stress and has a strong urge to drink alcohol. What alternative activity would you suggest?"

[1236] 3. Managing Community Features

[1237] Server: Manages community functions, including sending and receiving messages and running forums. Also filters spam and inappropriate content.

[1238] Generative AI Models

[1239] The generative AI model will be implemented as an artificial intelligence system with the following functions:

[1240] 1. Data Analysis

[1241] Generative AI Model: Analyzes user data received from the server and generates alternative activities suitable for the user's mood and environment on that day. Specifically, it performs analysis and makes suggestions based on prompt messages.

[1242] 2. Proposal generation

[1243] Generative AI Model: Based on the results of data analysis, it generates specific activity suggestions for the user. For example, if the user is experiencing high stress, it suggests relaxation methods; if the user has a strong urge to drink, it suggests alternative hobbies.

[1244] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle. This makes it possible to suggest alternative activities tailored to each user's individual circumstances and psychology, thereby achieving long-term alcohol reduction.

[1245] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1246] Step 1: User registration and login

[1247] Specific actions:

[1248] User: Download and launch the app.

[1249] Input: Users enter basic information such as their name, email address, and frequency of drinking.

[1250] Terminal: Sends the entered information to the server.

[1251] Server: Saves the received registration information to the database and generates a registration completion message.

[1252] Output: The server sends a registration completion message to the terminal.

[1253] User: Enter your existing account information (email address and password) to log in.

[1254] Terminal: Sends login information to the server.

[1255] Server: The server checks against the database and, if authentication is successful, approves the login.

[1256] Output: Sends the authentication result to the terminal.

[1257] Step 2: Daily data entry

[1258] Specific actions:

[1259] User: Open the app and enter data about your mood and environment for the day (e.g., "I'm feeling stressed today," "I have a strong urge to drink").

[1260] Input: Data about the user's daily mood and environment.

[1261] Terminal: Formats the data and sends it to the server.

[1262] Server: Receives data and saves it to the database.

[1263] Output: Generates a data saving confirmation message and sends it to the terminal.

[1264] Step 3: Send data to the server

[1265] Specific actions:

[1266] Terminal: Once data entry is complete, the terminal sends the data to the server.

[1267] Input: User data sent by the device.

[1268] Server: Stores received data in the database and prepares requests for the generated AI model.

[1269] Output: Generates a data saving confirmation message and sends it to the terminal.

[1270] Step 4: Data analysis and proposal generation using generative AI models

[1271] Specific actions:

[1272] Server: Formats the data sent by the user and generates a request to send to the generated AI model.

[1273] Server: Sends an example prompt message, "The user is currently experiencing significant stress and has a strong urge to drink alcohol. What alternative activities would you suggest?" to the generating AI model.

[1274] Input: Prompt message and user data.

[1275] Generative AI model: Analyzes received data and generates optimal alternative activities for the user.

[1276] Output: The analysis results (e.g., "Participate in an online yoga session," "Watch a new movie") are sent back to the server.

[1277] Step 5: Receiving and displaying proposals

[1278] Specific actions:

[1279] Server: Sends suggestions received from the generated AI model to the user's terminal.

[1280] Input: Suggestions from a generative AI model.

[1281] Terminal: Displays received suggestions to the user.

[1282] Output: Suggestions are displayed on the user's screen (e.g., "Join an online yoga session," "Watch a new movie").

[1283] Step 6: Using Community Features

[1284] Specific actions:

[1285] Users: Interact with other users through chat and forums using the in-app community features.

[1286] Input: User messages or posts.

[1287] Server: Manages community messages and posts, and filters out spam and inappropriate content.

[1288] Output: Messages and posts within the community are displayed.

[1289] Step 7: Collect and transmit smartwatch data

[1290] Specific actions:

[1291] User: Wear the smartwatch and connect it to the app.

[1292] Input: Biometric data collected by the smartwatch (e.g., heart rate, stress level).

[1293] Terminal: Sends collected biometric data to the server.

[1294] Server: Sends received biometric data to a generating AI model and makes a request to generate specific suggestions.

[1295] Output: The suggestions generated by the generative AI model are presented to the user again.

[1296] The above describes the specific processing flow of this system's program.

[1297] (Application Example 1)

[1298] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1299] In modern society, health problems caused by alcohol consumption are on the rise, making prevention crucial. However, many people find it difficult to find alternative activities to avoid alcohol. Furthermore, many people who want to avoid alcohol lack access to helpful information and support. The lack of concrete alternative activity suggestions in physical stores is also a challenge.

[1300] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1301] In this invention, the server includes means for receiving mood and environmental data from the user, means for analyzing the received data and using a generative AI model to generate alternative activities for the user, means for presenting the generated alternative activities to the user, and means for suggesting alternative activities that can be used in physical stores. This makes it possible for users to easily find activities other than alcohol, and further promote a healthier lifestyle by experiencing these activities in physical stores.

[1302] A "user" is someone who uses the system to receive suggestions for alternative activities to reduce alcohol consumption.

[1303] "Mood and environmental data" refers to data that indicates the user's mood, stress level, physical condition, etc., at any given time.

[1304] A "generative AI model" is an artificial intelligence model used to analyze data received from users and generate optimal alternative activities.

[1305] "Alternative activities" refer to activities or behaviors that can be done instead of consuming alcohol.

[1306] A "physical store" refers to a store that is a real physical location, such as a cafe, a gym, or a movie theater.

[1307] "Biometric data" refers to data indicating a person's physical condition, such as heart rate and stress levels, obtained from smartwatches and other wearable devices.

[1308] "Community features" refer to functions that allow users with similar problems to connect and interact with each other.

[1309] This invention relates to a comprehensive support system for users to reduce alcohol consumption and maintain a healthy lifestyle through alternative activities. The entire system consists of a smartphone app, a cloud-based server, a generative AI model, and wearable devices such as smartwatches.

[1310] User device (smartphone app)

[1311] The user device will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[1312] 1. User registration and login function

[1313] When a user first launches the app, they create an account by entering basic information such as their name, email address, and drinking frequency. If they already have an account, they can access it using the login function.

[1314] 2. Data Input Interface

[1315] Users utilize an interface to input data about their daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[1316] 3. Receiving and displaying proposals

[1317] The device receives suggestions from the generated AI model and displays them to the user. For example, it might suggest specific activities such as "Take a break at a nearby cafe" or "Participate in a relaxation session at a gym."

[1318] 4. Community Features

[1319] Users can utilize community features to interact with other users who share similar concerns. Information exchange and support are provided through chat and forums.

[1320] 5. Integration with smartwatches

[1321] The device works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current status in real time and suggests appropriate activities. Hardware options include Apple Watch and Fitbit.

[1322] Server-side functionality

[1323] The server will be implemented as a cloud-based system with the following functions:

[1324] 1. User data management

[1325] The server manages user account information, daily input data, and requests to the generated AI model. Databases such as PostgreSQL are used.

[1326] 2. Communication with the Generative AI Model

[1327] The server receives data sent by the user and sends a request to the generative AI model to perform analysis and provide suggestions. Generative AI models such as TensorFlow and GPT-4 are used.

[1328] 3. Managing Community Features

[1329] The server manages community functions, including sending and receiving messages and running forums. It also filters spam and inappropriate content.

[1330] Generative AI Models

[1331] The generative AI model will be implemented as an artificial intelligence system with the following functions:

[1332] 1. Data Analysis

[1333] The generative AI model analyzes the received user data and generates alternative activities that are suitable for the user's mood and environment on that day.

[1334] 2. Proposal generation

[1335] The generative AI model generates specific activity suggestions for the user based on the results of data analysis. For example, if the user is experiencing high stress levels, it might suggest relaxation methods; if they have a strong urge to drink, it might suggest alternative hobbies.

[1336] Specific example

[1337] 1. User Registration

[1338] The user downloads the app, enters their name, email address, and drinking frequency to register. The server receives this information and stores it in its database.

[1339] 2. Daily data entry

[1340] The user inputs their mood and circumstances for the day into the app. For example, they might enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." The device then sends this information to the server.

[1341] 3. Proposal generation and presentation

[1342] The server sends data to a generative AI model and requests suggestions. The generative AI model analyzes the data and generates specific activities such as "take a break at a nearby cafe" or "participate in a relaxation session at a gym." The terminal receives the suggestions and displays them to the user. The user can then select and perform one of the suggested activities.

[1343] 4. Use of community features

[1344] Users interact with other users through chat and forums, sharing experiences and opinions. The server manages this.

[1345] 5. Integration with smartwatches

[1346] The user wears a smartwatch and connects it to an app. The device collects heart rate and stress levels and sends them to a server. The generated AI model then uses this data to make more specific suggestions.

[1347] Example of a prompt

[1348] "The user is under a lot of stress and busy at work, so they need relaxation. Their current mood is normal, and they want to avoid alcohol. Please suggest some activities they can enjoy around the store."

[1349] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1350] Step 1:

[1351] Users download a smartphone app, enter their name, email address, and drinking frequency to create an account. The entered information is sent from the device to a cloud server.

[1352] Step 2:

[1353] The server stores the received user registration information in the database and generates a user ID. The server verifies the stored data and sends a registration success message back to the user.

[1354] Step 3:

[1355] Users input data about their daily mood and environment into a smartphone app. For example, they might enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." This data is then sent from the device to a server.

[1356] Step 4:

[1357] The server stores the received mood and environment data in a database. It generates prompts to send the stored data to the AI ​​model and prepares it for transmission to the AI ​​model.

[1358] Step 5:

[1359] The generative AI model receives a prompt message and analyzes the user's mood and environmental data. Based on the analysis, it suggests specific and appropriate alternative activities, such as taking a break at a nearby cafe or a relaxation session at a gym.

[1360] Step 6:

[1361] The server stores the suggestions received from the generated AI model in a database and sends them to the user's terminal. The terminal then displays the received suggestions to the user.

[1362] Step 7:

[1363] Users select and perform activities from the suggested options. Furthermore, they can utilize community features to interact with other users who share similar concerns.

[1364] Step 8:

[1365] Biometric data (such as heart rate and stress level) from the user wearing the smartwatch is transmitted to the device in real time. The device then sends this data to the server.

[1366] Step 9:

[1367] The server stores the received biometric data in a database and generates prompts based on this data to request new suggestions from the generative AI model. The generative AI model analyzes the biometric data in real time and generates new alternative activities.

[1368] Step 10:

[1369] The server sends the generated new suggestions to the user's device, which then displays them to the user. The user can then select and experience the activities that interest them most.

[1370] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1371] This invention relates to a system that provides users with beneficial alternative activities and community features to help them avoid health damage caused by alcohol consumption, as well as an emotion recognition function using an emotion engine. This system is mainly implemented by combining a user terminal (smartphone application), a server, a generative AI model, and an emotion engine.

[1372] User device (smartphone app)

[1373] The user device will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[1374] 1. User registration and login function

[1375] Users: When launching the app for the first time, create an account by entering basic information such as your name, email address, and drinking frequency. If you already have an account, access it using the login function.

[1376] 2. Data Input Interface

[1377] User: Uses an interface to input data about daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[1378] 3. Receiving and displaying proposals

[1379] Terminal: Receives suggestions from the generative AI model and emotion engine and displays them to the user. For example, it may suggest specific activities such as "Join an online yoga session" or "Watch a new movie."

[1380] 4. Community Features

[1381] Users can utilize community features to interact with other users who share similar concerns. They can exchange information and provide support through chat and forums.

[1382] 5. Integration with smartwatches

[1383] Device: It works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current state in real time and suggests appropriate activities.

[1384] 6. Emotional Engine

[1385] Device: The emotion engine analyzes voice and facial expression data to recognize the user's emotions. Based on this emotion data, a generative AI model suggests more accurate alternative activities.

[1386] Server-side functionality

[1387] The server will be implemented as a cloud-based system with the following functions:

[1388] 1. User data management

[1389] Server: Manages user account information, daily input data, requests to generative AI models and emotion engines, etc.

[1390] 2. Communication with generative AI models and emotion engines

[1391] Server: Receives data sent from users and sends requests to the generative AI model and emotion engine to perform analysis and make suggestions.

[1392] 3. Managing Community Features

[1393] Server: Manages community functions, including sending and receiving messages and running forums. Also filters spam and inappropriate content.

[1394] Generative AI models and emotion engines

[1395] The generative AI model and emotion engine will be implemented as an artificial intelligence system with the following functions:

[1396] 1. Data analysis and sentiment recognition

[1397] Generative AI Model: Analyzes received user data and generates alternative activities suitable for the user's mood and environment on that day.

[1398] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotional state. This emotional data is then provided to the AI ​​model for generating more personalized suggestions.

[1399] 2. Proposal generation

[1400] Generative AI Model: Based on data analysis and emotion recognition results, it generates specific activity suggestions for the user. For example, if stress levels are high and emotion recognition identifies "irritation," it will suggest relaxation methods.

[1401] Specific example

[1402] 1. User Registration

[1403] User: Users download the app, enter their name, email address, and drinking frequency to register. The server receives this information and stores it in its database.

[1404] 2. Daily data entry

[1405] User: Enters their mood and circumstances for the day into the app. For example, they might enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." The device then sends this information to the server.

[1406] 3. Analysis of voice and facial expressions

[1407] User: Speak to the app using voice commands or turn your face towards the camera.

[1408] Terminal: Acquires voice data and facial expression data and sends it to the emotion engine.

[1409] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotions. For example, it might generate a result such as "irritated."

[1410] 4. Proposal generation and presentation

[1411] Server: Sends data to the generative AI model and emotion engine and requests suggestions. The generative AI model generates specific activities based on data analysis and emotion recognition results.

[1412] Terminal: Receives suggestions and displays them to the user. The user can select and perform the suggested activities (e.g., relaxation methods or hobbies).

[1413] 5. Use of community features

[1414] Users interact with other users through chat and forums, sharing experiences and opinions. The server manages this.

[1415] 6. Integration with smartwatches

[1416] User: Wears a smartwatch and connects it to the app. The device collects heart rate and stress levels and sends them to the server. The generative AI model and emotion engine then use this data to make more specific suggestions.

[1417] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle.

[1418] The following describes the processing flow.

[1419] Step 1: User Registration

[1420] User: Launch the app for the first time and enter basic information such as name, email address, and daily drinking frequency.

[1421] Terminal: Sends the entered information to the server.

[1422] Server: Stores the received information in the database and returns a success message for account creation to the terminal.

[1423] Terminal: Displays a success message to the user.

[1424] Step 2: Data Entry

[1425] User: Enter information about your mood and environment for the day into the app. For example, you might report, "I'm feeling stressed today," or "I have a strong urge to drink."

[1426] Terminal: Sends the entered data to the server.

[1427] Server: Receives data and saves it to the database.

[1428] Step 3: Request analysis from generative AI models and emotion engines.

[1429] Server: Sends stored data to the generative AI model and sentiment engine for analysis. Specifically, it sends POST requests to the generative AI model and sentiment engine.

[1430] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotions. The results of the emotion recognition are then sent to a generating AI model.

[1431] Generative AI Model: Based on received data and emotion recognition results, it generates optimal alternative activities for the user. For example, it suggests relaxation methods or hobby-related activities.

[1432] Generative AI model: Returns the generated suggestions to the server.

[1433] Step 4: Providing and displaying proposals

[1434] Server: Receives suggestions from the generative AI model and emotion engine, and sends them to the user's terminal.

[1435] Device: Receives suggestions and displays them to the user. For example, it displays a link to "Online yoga sessions you can join now" on the app's home screen.

[1436] Step 5: Utilizing Community Features

[1437] Users: Utilize community features to interact with other users. For example, share experiences and opinions in chats and forums.

[1438] Terminal: Sends user messages to the server and receives and displays messages from other users.

[1439] Server: Sends messages to other relevant user terminals and manages community features. It also filters spam and inappropriate content.

[1440] Step 6: Connecting with a smartwatch (optional)

[1441] User: Wear the smartwatch and connect it to the app.

[1442] Device: Acquires biometric data such as heart rate and stress level from the smartwatch and sends it to the server.

[1443] Server: Sends received biometric data to the generating AI model and emotion engine.

[1444] Generative AI Model: Generates more specific suggestions based on biometric data and emotion recognition results. For example, it might suggest deep breathing exercises if the heart rate is high.

[1445] Server: Sends the generated proposal to the terminal.

[1446] Terminal: Notifies the user of suggestions. For example, it displays a notification such as, "Take three deep breaths right now."

[1447] In this way, the system helps users control their cravings for alcohol in a healthy manner.

[1448] (Example 2)

[1449] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1450] In recent years, health problems caused by alcohol consumption have become a social issue. Therefore, effective measures to reduce alcohol consumption are needed. However, conventional technologies struggle to suggest personalized alternative activities tailored to the user's mood and environment, and advanced analysis based on users' emotional states and biometric data is lacking. Furthermore, opportunities for connection and interaction with other users who share similar concerns are insufficient.

[1451] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1452] In this invention, the server includes means for receiving mood and environmental data from the user, means including a generative AI model that analyzes the received data and generates alternative activities for the user, means for presenting the generated alternative activities to the user, means including an emotion engine that analyzes the user's voice and facial expression data and recognizes their emotional state, and means for generating alternative activities based on the analyzed emotional state. As a result, the user can receive personalized alternative activity suggestions that match their mood and emotional state, enabling effective support for reducing alcohol consumption. Furthermore, it is also possible to include a community function for collaborating and interacting with other users who have similar concerns, and to collect biometric data in conjunction with a smartwatch to provide more accurate suggestions.

[1453] A "user" is a person who uses the system, creates an account, and inputs data about their daily mood and environment.

[1454] "Mood and environmental data" refers to information about the user's daily mood and psychological state, as well as the environment and circumstances of that day.

[1455] "Means of receiving data" refers to an interface equipped with the function of collecting data from users and transmitting it to a server or analysis system.

[1456] A "generative AI model" refers to an artificial intelligence system that analyzes received data and generates alternative activities suitable for the user based on the analysis results.

[1457] "Alternative activities" refer to beneficial activities or methods suggested by the system to reduce alcohol consumption, and are generated based on the user's mood and emotional state.

[1458] "Means of presentation" refers to interfaces and devices used to display suggestions from generative AI models and emotion engines to users.

[1459] An "emotion engine" refers to a system that analyzes a user's voice and facial expression data to recognize their emotional state.

[1460] "Voice and facial expression data" refers to biometric data that includes information about the voice and facial expressions emitted by the user, and is the subject of analysis by the emotion engine.

[1461] "Community features" refer to chat and forum functions that allow users to exchange information and support each other with other users who have similar problems.

[1462] A "smartwatch" refers to a wearable device that collects biometric data such as the user's heart rate and stress level, and transmits it to the user's device or a server.

[1463] "Biometric data" refers to information about a user's physical condition, such as heart rate and stress level, collected through devices like smartwatches.

[1464] This invention relates to a system that provides users with beneficial alternative activities and community features to help them avoid health damage caused by alcohol consumption, as well as an emotion recognition function using an emotion engine. This system is mainly implemented by combining a user terminal (smartphone application), a server, a generative AI model, and an emotion engine.

[1465] User device (smartphone app)

[1466] The user terminal will be implemented as a smartphone application for daily use by the user. This application will have the following functions:

[1467] 1. User registration and login function

[1468] Users: When launching the app for the first time, create an account by entering information such as your name, email address, and drinking frequency. If you already have an account, log in by entering your email address and password.

[1469] Terminal: Sends the entered information to the server to create a new account or authenticate login.

[1470] 2. Data Input Interface

[1471] User: Enter data about your daily mood and environment. For example, enter information such as "I'm feeling stressed today" or "I have a strong urge to drink" into the app.

[1472] Terminal: Sends the entered data to the server.

[1473] 3. Receiving and displaying proposals

[1474] Terminal: Receives suggestions from the generative AI model and emotion engine and displays them to the user. For example, specific activities such as "join an online yoga session" or "watch a new movie" may be suggested.

[1475] 4. Community Features

[1476] Users: Utilize community features to interact with other users who share similar concerns. Exchange information and support through chat and forums.

[1477] Server: Manages these community features, including sending and receiving messages and running forums. Also filters spam and inappropriate content.

[1478] 5. Integration with smartwatches

[1479] User: Wear a smartwatch and connect it to the app. The device collects biometric data such as heart rate and stress level.

[1480] Terminal: Sends collected biometric data to the server.

[1481] 6. Emotional Engine

[1482] Device: The emotion engine analyzes voice and facial expression data to recognize the user's emotions. Based on this emotion data, a generative AI model suggests more accurate alternative activities.

[1483] Server-side functionality

[1484] The server has the following functions and will be implemented as a cloud-based system:

[1485] 1. User data management

[1486] Server: Manages user account information, daily input data, and requests to the generative AI model and sentiment engine.

[1487] 2. Communication with generative AI models and emotion engines

[1488] Server: Receives data sent from users and sends requests to the generative AI model and emotion engine to perform analysis and make suggestions.

[1489] 3. Managing Community Features

[1490] Server: Manages community functions, including sending and receiving messages and running forums. Also performs filtering of inappropriate content.

[1491] Generative AI models and emotion engines

[1492] The generative AI model and emotion engine will be implemented as an artificial intelligence system with the following functions:

[1493] 1. Data analysis and sentiment recognition

[1494] Generative AI Model: Analyzes received user data and generates alternative activities suitable for the user's mood and environment on that day.

[1495] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotional state. This emotional data is then provided to the AI ​​model for generating more personalized suggestions.

[1496] 2. Proposal generation

[1497] Generative AI Model: Based on data analysis and emotion recognition results, it generates specific activity suggestions for the user. For example, if stress levels are high and emotion recognition reveals "irritation," it will suggest relaxation methods.

[1498] Specific example

[1499] 1. User Registration

[1500] User: Downloads the app, enters their name, email address, and drinking frequency to register. The server receives this information and stores it in its database.

[1501] 2. Daily data entry

[1502] User: Enters their mood and circumstances for the day into the app. They enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." The device then sends this information to the server.

[1503] 3. Analysis of voice and facial expressions

[1504] User: Speak to the app using voice commands or turn your face towards the camera.

[1505] The device acquires voice and facial expression data and sends it to the emotion engine. The emotion engine analyzes this data and recognizes the user's emotional state. For example, it might generate a result such as "irritated."

[1506] 4. Proposal generation and presentation

[1507] Server: Sends data to the generative AI model and emotion engine and requests suggestions. The generative AI model generates specific activities based on data analysis and emotion recognition results.

[1508] Terminal: Receives suggestions and displays them to the user. The user can select and perform the suggested activities (e.g., "relaxation methods" or "hobby activities").

[1509] 5. Use of community features

[1510] Users interact with other users through chat and forums, sharing experiences and opinions. The server manages this.

[1511] 6. Integration with smartwatches

[1512] User: Wears a smartwatch and connects it to the app. The device collects heart rate and stress levels and sends them to the server. The generative AI model and emotion engine then use this data to make more specific suggestions.

[1513] Examples of prompt statements

[1514] 1. A stressful day

[1515] User: Enter "I'm feeling particularly stressed today, so please tell me some relaxation techniques" as the prompt.

[1516] Generative AI model: Based on the received prompt, it suggests specific relaxation methods (e.g., "Do deep breathing exercises," "Try aromatherapy").

[1517] 2. Days when the urge to drink is strong

[1518] User: Enter the following as the prompt: "I have a strong urge to drink alcohol, so I would like suggestions for alternative hobbies or activities."

[1519] Generative AI model: Based on user sentiment data and daily data analysis results, it suggests hobby activities (e.g., "drawing pictures," "reading books").

[1520] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle.

[1521] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1522] Step 1:

[1523] User Registration / Login

[1524] User: When launching the app for the first time, you will create an account by entering basic information such as your name, email address, and frequency of drinking.

[1525] Terminal: Sends the entered user information to the server.

[1526] Server: Receives user information and stores it in the database. If an existing account exists, it receives the email address and password and verifies them against the database. If authentication is successful, it starts the session.

[1527] Input: The user's basic information is entered here.

[1528] Output: The results of account creation and authentication on the server are output.

[1529] Step 2:

[1530] Daily data entry

[1531] User: Launch the app and enter data about your mood and environment for the day. Specifically, enter information such as "I'm feeling stressed today" or "I have a strong urge to drink."

[1532] Terminal: Sends the entered data to the server.

[1533] Server: Receives data, links it to user information, and saves it to the database.

[1534] Input: Daily data related to mood and environment is entered.

[1535] Output: Daily data stored in the database is output.

[1536] Step 3:

[1537] Collection and analysis of emotional data

[1538] User: Speak to the app using voice commands or turn your face towards the camera.

[1539] Terminal: Collects voice data and facial expression data and sends it to the emotion engine.

[1540] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotional state. For example, it generates results such as "irritated."

[1541] Terminal: Sends analysis results to the server.

[1542] Input: Voice data and facial expression data are input.

[1543] Output: The analysis results of the emotion engine are output.

[1544] Step 4:

[1545] Proposal generation and presentation

[1546] Server: Inputs daily data and sends emotional data to the AI ​​model for analysis and recommendations.

[1547] Generative AI Model: Analyzes received data and generates specific activity suggestions. For example, if it detects high stress levels, it will suggest "relaxation methods."

[1548] Server: Receives suggestions from the generated AI model and sends them to the user's terminal.

[1549] Terminal: Receives suggestions and displays the suggestions to the user. The user can select and perform the suggested activities.

[1550] Input: Daily data and sentiment data are entered.

[1551] Output: Activity suggestions generated by the generative AI model are output.

[1552] Step 5:

[1553] Using community features

[1554] Users: Utilize the app's community features to interact with other users through chat and forums.

[1555] Server: Manages message sending and receiving, forum operation, and filters inappropriate content.

[1556] Input: Messages and posts from the community are entered here.

[1557] Output: Information about community features managed by the server is output.

[1558] Step 6:

[1559] Collection and linkage of biometric data

[1560] User: Wear the smartwatch and connect it to the app.

[1561] Device: Collects biometric data such as heart rate and stress level from the smartwatch and sends it to the server.

[1562] Server and Generative AI Model: Generates more specific suggestions based on received biometric data.

[1563] Terminal: Displays specific activity suggestions to the user from the generated AI model.

[1564] Input: Biometric data from a smartwatch is entered.

[1565] Output: Specific activity suggestions generated by the AI ​​model are output.

[1566] Through these steps, the system provides users with personalized alternative activity suggestions and offers effective support for reducing alcohol consumption.

[1567] (Application Example 2)

[1568] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1569] In modern society, the health risks associated with alcohol consumption are a major problem. In particular, because moderate alternative activities are not readily available, many people try to relieve stress and cravings with alcohol. However, there is a lack of specific and personalized suggestions tailored to individual circumstances. Therefore, there is a need for effective support systems to help users maintain a healthy lifestyle.

[1570] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1571] In this invention, the server includes means for receiving mood and environmental data from the user, means for analyzing the received data and generating alternative activities for the user using a generative AI model, means for presenting the generated alternative activities to the user, means for analyzing the user's voice and facial expression data using an emotion recognition engine and identifying their emotional state, and means for the generative AI model to suggest even more accurate alternative activities based on the emotional state. As a result, the user can receive personalized alternative activity suggestions based on their emotional state and biometric data, making it easier to maintain a healthy lifestyle.

[1572] "User" refers to an individual who uses the system.

[1573] "Mood and environmental data" refers to information about the user's everyday emotions and surrounding circumstances.

[1574] "Means of receiving" refers to methods and devices for securing data transmitted by users.

[1575] "Means of analysis" refers to methods and devices that analyze received data to derive meaningful information.

[1576] A "generative AI model" refers to an artificial intelligence algorithm that generates new suggestions and activities based on received and analyzed data.

[1577] "Alternative activities" refer to beneficial activities or hobbies that help prevent drinking.

[1578] "Means of presentation" refers to the methods or devices used to show the generated activities or suggestions to the user.

[1579] An "emotion recognition engine" refers to a system that analyzes voice and facial expression data to identify the user's emotional state.

[1580] "Voice and facial expression data" refers to information about the user's voice and facial expressions.

[1581] "Biometric data" refers to physical information such as heart rate and stress levels collected using devices like smartwatches.

[1582] "Community features" refer to online platforms that allow users to exchange information and support each other with similar problems.

[1583] The system of the present invention is composed of a user terminal, a server, a generative AI model, an emotion recognition engine, and biosensor devices such as a smartwatch.

[1584] User terminal (smartphone app)

[1585] The user terminal will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[1586] 1. User registration and login function

[1587] Users create an account upon first launch by entering basic information such as their name, email address, and frequency of drinking. If an existing account exists, they can access it using the login function.

[1588] 2. Data Input Interface

[1589] Users utilize an interface to input data about their daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[1590] 3. Receiving and displaying proposals

[1591] The device receives suggestions from the generative AI model and emotion recognition engine and displays them to the user. For example, it may suggest specific activities such as "join an online yoga session" or "watch a new movie."

[1592] 4. Community Features

[1593] Users can utilize community features to interact with other users who share similar concerns. Information exchange and support are provided through chat and forums.

[1594] 5. Integration with smartwatches

[1595] The device works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current state in real time and suggests appropriate activities.

[1596] 6. Emotion Recognition Engine

[1597] The device uses an emotion recognition engine to analyze voice and facial expression data to recognize the user's emotions. Based on this emotion data, a generative AI model suggests more accurate alternative activities.

[1598] Server-side functionality

[1599] The server will be implemented as a cloud-based system with the following functions:

[1600] 1. User data management

[1601] The server manages user account information, daily input data, and requests to the generative AI model and emotion recognition engine.

[1602] 2. Communication with generative AI models and emotion recognition engines

[1603] The server receives data sent by the user and sends requests to the generative AI model and emotion recognition engine to perform analysis and make suggestions.

[1604] 3. Managing Community Features

[1605] The server manages community functions, including sending and receiving messages and running forums. It also filters spam and inappropriate content.

[1606] Generative AI models and emotion recognition engines

[1607] The generative AI model and emotion recognition engine will be implemented as an artificial intelligence system with the following functions:

[1608] 1. Data analysis and sentiment recognition

[1609] The generative AI model analyzes the received user data and generates alternative activities that are suitable for the user's mood and environment on that day.

[1610] The emotion recognition engine analyzes voice and facial expression data to recognize the user's emotional state. This emotional data is then provided to the AI ​​model for generating more personalized suggestions.

[1611] 2. Proposal generation

[1612] The generative AI model generates specific activity suggestions for the user based on data analysis and emotion recognition results. For example, if stress levels are high and emotion recognition identifies "irritation," it will suggest relaxation methods.

[1613] Presentation of specific examples and prompt statements

[1614] For example, the following prompt could represent emotional data when a user is feeling stressed.

[1615] Example of a prompt:

[1616] I'm feeling very stressed today. I have a strong urge to drink, but what can I do to control it?

[1617] Based on this data, the generated AI model and emotion recognition engine work together to suggest specific alternative activities.

[1618] Hardware and software to be used

[1619] User devices: Smartphones, smartwatches

[1620] Server: Cloud service platform (e.g., AWS, Google Cloud)

[1621] Generative AI models and emotion recognition engines: Deep learning frameworks (e.g., TensorFlow, PyTorch)

[1622] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle.

[1623] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1624] Step 1:

[1625] The user launches the smartphone app and uses the user registration / login function to enter basic information such as their name, email address, and frequency of drinking. This input data is received by the device and sent to the server. The server stores this data in a database.

[1626] Input: Name, email address, and basic information about your drinking frequency.

[1627] Output: User information stored in the server's database

[1628] Step 2:

[1629] Users report daily mood and environmental data using the in-app data input interface. For example, they might write, "I'm feeling stressed today" or "I have a strong urge to drink." This input data is then sent back to the server by the device and recorded.

[1630] Input: Data related to mood and environment

[1631] Output: Daily data sent to and recorded on the server

[1632] Step 3:

[1633] Users provide emotional data by speaking aloud or facing the camera. The device acquires the voice and facial expression data and sends it to an emotion recognition engine. The emotion recognition engine analyzes the data and identifies the user's emotional state. This result is then sent to a generative AI model.

[1634] Input: Voice data and facial expression data

[1635] Output: Identification of emotional state by emotion recognition engine

[1636] Step 4:

[1637] The server sends daily mood and environmental data, as well as emotional data from the emotion recognition engine, to a generative AI model. The generative AI model analyzes this data and generates alternative activities based on the user's current state. These activity suggestions are then sent to the server.

[1638] Input: Mood and environmental data, emotional data

[1639] Output: Suggestions for alternative activities using a generative AI model.

[1640] Step 5:

[1641] The server sends alternative activity suggestions received from the generated AI model to the terminal, and the user terminal displays them to the user. The user can then select and perform the displayed activity suggestion.

[1642] Input: Activity suggestions from a generated AI model

[1643] Output: Alternative activities displayed to the user

[1644] Step 6:

[1645] Users utilize the app's community features to interact with other users who share similar concerns through chat and forums. The server manages the community features, handling message sending and receiving, and running the forums.

[1646] Input: Chat messages and forum posts from users

[1647] Output: Information exchange and support with other users

[1648] Step 7:

[1649] Users wear biosensor devices such as smartwatches and connect them to the app. The device collects biometric data such as heart rate and stress levels from the smartwatch and sends it to a server. The server provides this biometric data to a generating AI model and emotion recognition engine, which then suggests more specific activities.

[1650] Input: Biometric data obtained from a smartwatch

[1651] Output: Specific activity suggestions generated by a generative AI model and emotion recognition engine.

[1652] Through these steps, the system provides effective support for reducing alcohol consumption and helps users maintain a healthy lifestyle.

[1653] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1654] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1655] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1656] [Fourth Embodiment]

[1657] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1658] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1659] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1660] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1661] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1662] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1663] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1664] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1665] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1666] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1667] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1668] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1669] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1670] This invention relates to a system that provides users with beneficial alternative activities and community features to help them avoid health problems caused by alcohol consumption. This system is primarily implemented by combining a user terminal (smartphone application), a server, and a generative AI model.

[1671] User device (smartphone app)

[1672] The user device will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[1673] 1. User registration and login function

[1674] Users: When launching the app for the first time, create an account by entering basic information such as your name, email address, and drinking frequency. If you already have an account, access it using the login function.

[1675] 2. Data Input Interface

[1676] User: Uses an interface to input data about daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[1677] 3. Receiving and displaying proposals

[1678] Terminal: Receives suggestions from the generating AI model and displays them to the user. For example, it might suggest specific activities such as "Join an online yoga session" or "Watch a new movie."

[1679] 4. Community Features

[1680] Users can utilize community features that allow them to interact with other users who share similar concerns. Information exchange and support are provided through chat and forums.

[1681] 5. Integration with smartwatches

[1682] Device: It works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current state in real time and suggests appropriate activities.

[1683] Server-side functionality

[1684] The server will be implemented as a cloud-based system with the following functions:

[1685] 1. User data management

[1686] Server: Manages user account information, daily input data, requests to the generated AI model, etc.

[1687] 2. Communication with the Generative AI Model

[1688] Server: Receives data sent from users and sends requests to the generated AI model to perform analysis and make suggestions.

[1689] 3. Managing Community Features

[1690] Server: Manages community functions, including sending and receiving messages and running forums. Also filters spam and inappropriate content.

[1691] Generative AI Models

[1692] The generative AI model will be implemented as an artificial intelligence system with the following functions:

[1693] 1. Data Analysis

[1694] Generative AI Model: Analyzes received user data and generates alternative activities suitable for the user's mood and environment on that day.

[1695] 2. Proposal generation

[1696] Generative AI Model: Based on the results of data analysis, it generates specific activity suggestions for the user. For example, if the user is experiencing high stress, it suggests relaxation methods; if the user has a strong urge to drink, it suggests alternative hobby activities.

[1697] Specific example

[1698] 1. User Registration

[1699] User: Users download the app, enter their name, email address, and drinking frequency to register. The server receives this information and stores it in its database.

[1700] 2. Daily data entry

[1701] User: Enters their mood and circumstances for the day into the app. For example, they might enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." The device then sends this information to the server.

[1702] 3. Proposal generation and presentation

[1703] Server: Sends data to the generative AI model and requests suggestions. The generative AI model analyzes the data and generates specific activities such as "Join an online yoga session now" or "Watch a new movie."

[1704] Terminal: Receives suggestions and displays them to the user. The user can select and perform the suggested activities.

[1705] 4. Use of community features

[1706] Users interact with other users through chat and forums, sharing experiences and opinions. The server manages this.

[1707] 5. Integration with smartwatches

[1708] User: Wears a smartwatch and connects it to the app. The device collects heart rate and stress levels and sends them to the server. The generated AI model uses this data to make more specific suggestions.

[1709] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle.

[1710] The following describes the processing flow.

[1711] Step 1: User Registration

[1712] User: Launch the app for the first time and enter basic information such as name, email address, and daily drinking frequency.

[1713] Terminal: Sends the entered information to the server.

[1714] Server: Stores the received information in the database and returns a success message for account creation to the terminal.

[1715] Terminal: Displays a success message to the user.

[1716] Step 2: Data Entry

[1717] User: Enter information about your mood and environment for the day into the app. For example, you might report, "I'm feeling stressed today," or "I have a strong urge to drink."

[1718] Terminal: Sends the entered data to the server.

[1719] Server: Receives data and saves it to the database.

[1720] Step 3: Request analysis from the generative AI model

[1721] Server: Sends the stored data to the generating AI model for analysis. Specifically, it sends a POST request to the generating AI model.

[1722] Generative AI Model: Analyzes received data and generates optimal alternative activities for the user. For example, it can suggest online yoga sessions or movie viewings.

[1723] Generative AI model: Returns the generated suggestions to the server.

[1724] Step 4: Providing and displaying proposals

[1725] Server: Receives suggestions from the generated AI model and sends them to the user's terminal.

[1726] Device: Receives suggestions and displays them to the user. For example, it displays a link to "Online yoga sessions you can join now" on the app's home screen.

[1727] Step 5: Utilizing Community Features

[1728] Users: Utilize community features to interact with other users. For example, share experiences and opinions in chats and forums.

[1729] Terminal: Sends user messages to the server and receives and displays messages from other users.

[1730] Server: Sends messages to other relevant user terminals and manages community features. It also filters spam and inappropriate content.

[1731] Step 6: Connecting with a smartwatch (optional)

[1732] User: Wear the smartwatch and connect it to the app.

[1733] Device: Acquires biometric data such as heart rate and stress level from the smartwatch and sends it to the server.

[1734] Server: Sends the received biometric data to the AI ​​model for generation.

[1735] Generative AI models: These models generate more specific suggestions based on biometric data. For example, they might suggest deep breathing exercises if the heart rate is high.

[1736] Server: Sends the generated proposal to the terminal.

[1737] Terminal: Notifies the user of suggestions. For example, it displays a notification such as, "Take three deep breaths right now."

[1738] In this way, the system helps users control their cravings for alcohol in a healthy manner.

[1739] (Example 1)

[1740] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1741] Traditional alcohol reduction systems lacked the ability to suggest alternative activities tailored to each user's individual circumstances and psychological state. This made it difficult for users to actually refrain from drinking. Furthermore, they lacked features for collaboration with other users through community functions and systems capable of providing personalized suggestions based on real-time biometric data. As a result, it was difficult to motivate users and achieve long-term alcohol reduction.

[1742] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1743] In this invention, the server includes means for receiving mood and environmental data from the user, means for analyzing the received data and generating alternative activities for the user using a generative artificial intelligence model, means for presenting the generated alternative activities to the user, and means for collecting biometric data in conjunction with a corresponding bio-device and generating alternative activities based on the collected biometric data. This makes it possible to suggest alternative activities that are tailored to the individual circumstances and psychology of the user, thereby enabling long-term alcohol suppression.

[1744] "User" refers to an individual who uses the system.

[1745] "Mood" refers to data that indicates the user's emotions and mental state.

[1746] "Environmental data" refers to information about the physical or psychological environment in which a user is placed.

[1747] "Analysis" refers to the process of processing received data to extract useful information.

[1748] A "generative artificial intelligence model" refers to an AI system that generates alternative activities based on received data.

[1749] "Alternative activities" refer to activities or tasks that users can undertake to reduce their alcohol consumption.

[1750] "Presentation" refers to the act of informing the user of the generated alternative activity.

[1751] "Biometric devices" refer to wearable devices and sensors that collect users' biometric data.

[1752] "Biometric data" refers to data that indicates a user's physical condition or health status.

[1753] "Community features" refer to functions that allow users to connect and interact with other users who have similar problems.

[1754] "Suggestions" refer to recommended activities and methods provided to users based on analyzed data.

[1755] "Means of receiving" refers to devices or functions used to receive data from users.

[1756] "Means of transmission" refers to devices or functions used to send data or requests to other systems.

[1757] "Means of generation" refers to devices or functions used to analyze data and produce specific results.

[1758] "Means of collection" refers to the devices or functions used to collect data.

[1759] This invention is a system that provides behavioral support to help users reduce their alcohol consumption, and is primarily implemented by combining a user terminal (smartphone application), a server, and a generative AI model. The specific implementation methods of these components are described in detail below.

[1760] User device (smartphone app)

[1761] The user device will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[1762] 1. User registration and login function

[1763] Users: When launching the app for the first time, create an account by entering basic information such as your name, email address, and drinking frequency. If you already have an account, access it using the login function.

[1764] Terminal: Sends the entered information to the server, which then stores it in the database.

[1765] 2. Data Input Interface

[1766] User: Uses an interface to input data about daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[1767] Terminal: Sends the entered data to the server.

[1768] 3. Receiving and displaying proposals

[1769] Terminal: Receives suggestions from the generating AI model and displays them to the user. For example, it might suggest specific activities such as "Join an online yoga session" or "Watch a new movie."

[1770] 4. Community Features

[1771] Users can utilize community features that allow them to interact with other users who share similar concerns. Information exchange and support are provided through chat and forums.

[1772] 5. Integration with smartwatches

[1773] Device: It works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current state in real time and suggests appropriate activities.

[1774] Server-side functionality

[1775] The server will be implemented as a cloud-based system with the following functions:

[1776] 1. User data management

[1777] Server: Manages user account information, daily input data, requests to generated AI models, etc.

[1778] 2. Communication with the Generative AI Model

[1779] Server: Receives data sent by the user and sends a request to the generative AI model to perform analysis and make suggestions. Specifically, it uses prompt statements to request data analysis from the generative AI model.

[1780] Example prompt: "The user is currently experiencing significant stress and has a strong urge to drink alcohol. What alternative activity would you suggest?"

[1781] 3. Managing Community Features

[1782] Server: Manages community functions, including sending and receiving messages and running forums. Also filters spam and inappropriate content.

[1783] Generative AI Models

[1784] The generative AI model will be implemented as an artificial intelligence system with the following functions:

[1785] 1. Data Analysis

[1786] Generative AI Model: Analyzes user data received from the server and generates alternative activities suitable for the user's mood and environment on that day. Specifically, it performs analysis and makes suggestions based on prompt messages.

[1787] 2. Proposal generation

[1788] Generative AI Model: Based on the results of data analysis, it generates specific activity suggestions for the user. For example, if the user is experiencing high stress, it suggests relaxation methods; if the user has a strong urge to drink, it suggests alternative hobbies.

[1789] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle. This makes it possible to suggest alternative activities tailored to each user's individual circumstances and psychology, thereby achieving long-term alcohol reduction.

[1790] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1791] Step 1: User registration and login

[1792] Specific actions:

[1793] User: Download and launch the app.

[1794] Input: Users enter basic information such as their name, email address, and frequency of drinking.

[1795] Terminal: Sends the entered information to the server.

[1796] Server: Saves the received registration information to the database and generates a registration completion message.

[1797] Output: The server sends a registration completion message to the terminal.

[1798] User: Enter your existing account information (email address and password) to log in.

[1799] Terminal: Sends login information to the server.

[1800] Server: The server checks against the database and, if authentication is successful, approves the login.

[1801] Output: Sends the authentication result to the terminal.

[1802] Step 2: Daily data entry

[1803] Specific actions:

[1804] User: Open the app and enter data about your mood and environment for the day (e.g., "I'm feeling stressed today," "I have a strong urge to drink").

[1805] Input: Data about the user's daily mood and environment.

[1806] Terminal: Formats the data and sends it to the server.

[1807] Server: Receives data and saves it to the database.

[1808] Output: Generates a data saving confirmation message and sends it to the terminal.

[1809] Step 3: Send data to the server

[1810] Specific actions:

[1811] Terminal: Once data entry is complete, the terminal sends the data to the server.

[1812] Input: User data sent by the device.

[1813] Server: Stores received data in the database and prepares requests for the generated AI model.

[1814] Output: Generates a data saving confirmation message and sends it to the terminal.

[1815] Step 4: Data analysis and proposal generation using generative AI models

[1816] Specific actions:

[1817] Server: Formats the data sent by the user and generates a request to send to the generated AI model.

[1818] Server: Sends an example prompt message, "The user is currently experiencing significant stress and has a strong urge to drink alcohol. What alternative activities would you suggest?" to the generating AI model.

[1819] Input: Prompt message and user data.

[1820] Generative AI model: Analyzes received data and generates optimal alternative activities for the user.

[1821] Output: The analysis results (e.g., "Participate in an online yoga session," "Watch a new movie") are sent back to the server.

[1822] Step 5: Receiving and displaying proposals

[1823] Specific actions:

[1824] Server: Sends suggestions received from the generated AI model to the user's terminal.

[1825] Input: Suggestions from a generative AI model.

[1826] Terminal: Displays received suggestions to the user.

[1827] Output: Suggestions are displayed on the user's screen (e.g., "Join an online yoga session," "Watch a new movie").

[1828] Step 6: Using Community Features

[1829] Specific actions:

[1830] Users: Interact with other users through chat and forums using the in-app community features.

[1831] Input: User messages or posts.

[1832] Server: Manages community messages and posts, and filters out spam and inappropriate content.

[1833] Output: Messages and posts within the community are displayed.

[1834] Step 7: Collect and transmit smartwatch data

[1835] Specific actions:

[1836] User: Wear the smartwatch and connect it to the app.

[1837] Input: Biometric data collected by the smartwatch (e.g., heart rate, stress level).

[1838] Terminal: Sends collected biometric data to the server.

[1839] Server: Sends received biometric data to a generating AI model and makes a request to generate specific suggestions.

[1840] Output: The suggestions generated by the generative AI model are presented to the user again.

[1841] The above describes the specific processing flow of this system's program.

[1842] (Application Example 1)

[1843] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1844] In modern society, health problems caused by alcohol consumption are on the rise, making prevention crucial. However, many people find it difficult to find alternative activities to avoid alcohol. Furthermore, many people who want to avoid alcohol lack access to helpful information and support. The lack of concrete alternative activity suggestions in physical stores is also a challenge.

[1845] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1846] In this invention, the server includes means for receiving mood and environmental data from the user, means for analyzing the received data and using a generative AI model to generate alternative activities for the user, means for presenting the generated alternative activities to the user, and means for suggesting alternative activities that can be used in physical stores. This makes it possible for users to easily find activities other than alcohol, and further promote a healthier lifestyle by experiencing these activities in physical stores.

[1847] A "user" is someone who uses the system to receive suggestions for alternative activities to reduce alcohol consumption.

[1848] "Mood and environmental data" refers to data that indicates the user's mood, stress level, physical condition, etc., at any given time.

[1849] A "generative AI model" is an artificial intelligence model used to analyze data received from users and generate optimal alternative activities.

[1850] "Alternative activities" refer to activities or behaviors that can be done instead of consuming alcohol.

[1851] A "physical store" refers to a store that is a real physical location, such as a cafe, a gym, or a movie theater.

[1852] "Biometric data" refers to data indicating a person's physical condition, such as heart rate and stress levels, obtained from smartwatches and other wearable devices.

[1853] "Community features" refer to functions that allow users with similar problems to connect and interact with each other.

[1854] This invention relates to a comprehensive support system for users to reduce alcohol consumption and maintain a healthy lifestyle through alternative activities. The entire system consists of a smartphone app, a cloud-based server, a generative AI model, and wearable devices such as smartwatches.

[1855] User device (smartphone app)

[1856] The user device will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[1857] 1. User registration and login function

[1858] When a user first launches the app, they create an account by entering basic information such as their name, email address, and drinking frequency. If they already have an account, they can access it using the login function.

[1859] 2. Data Input Interface

[1860] Users utilize an interface to input data about their daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[1861] 3. Receiving and displaying proposals

[1862] The device receives suggestions from the generated AI model and displays them to the user. For example, it might suggest specific activities such as "Take a break at a nearby cafe" or "Participate in a relaxation session at a gym."

[1863] 4. Community Features

[1864] Users can utilize community features to interact with other users who share similar concerns. Information exchange and support are provided through chat and forums.

[1865] 5. Integration with smartwatches

[1866] The device works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current status in real time and suggests appropriate activities. Hardware options include Apple Watch and Fitbit.

[1867] Server-side functionality

[1868] The server will be implemented as a cloud-based system with the following functions:

[1869] 1. User data management

[1870] The server manages user account information, daily input data, and requests to the generated AI model. Databases such as PostgreSQL are used.

[1871] 2. Communication with the Generative AI Model

[1872] The server receives data sent by the user and sends a request to the generative AI model to perform analysis and provide suggestions. Generative AI models such as TensorFlow and GPT-4 are used.

[1873] 3. Managing Community Features

[1874] The server manages community functions, including sending and receiving messages and running forums. It also filters spam and inappropriate content.

[1875] Generative AI Models

[1876] The generative AI model will be implemented as an artificial intelligence system with the following functions:

[1877] 1. Data Analysis

[1878] The generative AI model analyzes the received user data and generates alternative activities that are suitable for the user's mood and environment on that day.

[1879] 2. Proposal generation

[1880] The generative AI model generates specific activity suggestions for the user based on the results of data analysis. For example, if the user is experiencing high stress levels, it might suggest relaxation methods; if they have a strong urge to drink, it might suggest alternative hobbies.

[1881] Specific example

[1882] 1. User Registration

[1883] The user downloads the app, enters their name, email address, and drinking frequency to register. The server receives this information and stores it in its database.

[1884] 2. Daily data entry

[1885] The user inputs their mood and circumstances for the day into the app. For example, they might enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." The device then sends this information to the server.

[1886] 3. Proposal generation and presentation

[1887] The server sends data to a generative AI model and requests suggestions. The generative AI model analyzes the data and generates specific activities such as "take a break at a nearby cafe" or "participate in a relaxation session at a gym." The terminal receives the suggestions and displays them to the user. The user can then select and perform one of the suggested activities.

[1888] 4. Use of community features

[1889] Users interact with other users through chat and forums, sharing experiences and opinions. The server manages this.

[1890] 5. Integration with smartwatches

[1891] The user wears a smartwatch and connects it to an app. The device collects heart rate and stress levels and sends them to a server. The generated AI model then uses this data to make more specific suggestions.

[1892] Example of a prompt

[1893] "The user is under a lot of stress and busy at work, so they need relaxation. Their current mood is normal, and they want to avoid alcohol. Please suggest some activities they can enjoy around the store."

[1894] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1895] Step 1:

[1896] Users download a smartphone app, enter their name, email address, and drinking frequency to create an account. The entered information is sent from the device to a cloud server.

[1897] Step 2:

[1898] The server stores the received user registration information in the database and generates a user ID. The server verifies the stored data and sends a registration success message back to the user.

[1899] Step 3:

[1900] Users input data about their daily mood and environment into a smartphone app. For example, they might enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." This data is then sent from the device to a server.

[1901] Step 4:

[1902] The server stores the received mood and environment data in a database. It generates prompts to send the stored data to the AI ​​model and prepares it for transmission to the AI ​​model.

[1903] Step 5:

[1904] The generative AI model receives a prompt message and analyzes the user's mood and environmental data. Based on the analysis, it suggests specific and appropriate alternative activities, such as taking a break at a nearby cafe or a relaxation session at a gym.

[1905] Step 6:

[1906] The server stores the suggestions received from the generated AI model in a database and sends them to the user's terminal. The terminal then displays the received suggestions to the user.

[1907] Step 7:

[1908] Users select and perform activities from the suggested options. Furthermore, they can utilize community features to interact with other users who share similar concerns.

[1909] Step 8:

[1910] Biometric data (such as heart rate and stress level) from the user wearing the smartwatch is transmitted to the device in real time. The device then sends this data to the server.

[1911] Step 9:

[1912] The server stores the received biometric data in a database and generates prompts based on this data to request new suggestions from the generative AI model. The generative AI model analyzes the biometric data in real time and generates new alternative activities.

[1913] Step 10:

[1914] The server sends the generated new suggestions to the user's device, which then displays them to the user. The user can then select and experience the activities that interest them most.

[1915] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1916] This invention relates to a system that provides users with beneficial alternative activities and community features to help them avoid health damage caused by alcohol consumption, as well as an emotion recognition function using an emotion engine. This system is mainly implemented by combining a user terminal (smartphone application), a server, a generative AI model, and an emotion engine.

[1917] User device (smartphone app)

[1918] The user device will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[1919] 1. User registration and login function

[1920] Users: When launching the app for the first time, create an account by entering basic information such as your name, email address, and drinking frequency. If you already have an account, access it using the login function.

[1921] 2. Data Input Interface

[1922] User: Uses an interface to input data about daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[1923] 3. Receiving and displaying proposals

[1924] Terminal: Receives suggestions from the generative AI model and emotion engine and displays them to the user. For example, it may suggest specific activities such as "Join an online yoga session" or "Watch a new movie."

[1925] 4. Community Features

[1926] Users can utilize community features to interact with other users who share similar concerns. They can exchange information and provide support through chat and forums.

[1927] 5. Integration with smartwatches

[1928] Device: It works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current state in real time and suggests appropriate activities.

[1929] 6. Emotional Engine

[1930] Device: The emotion engine analyzes voice and facial expression data to recognize the user's emotions. Based on this emotion data, a generative AI model suggests more accurate alternative activities.

[1931] Server-side functionality

[1932] The server will be implemented as a cloud-based system with the following functions:

[1933] 1. User data management

[1934] Server: Manages user account information, daily input data, requests to generative AI models and emotion engines, etc.

[1935] 2. Communication with generative AI models and emotion engines

[1936] Server: Receives data sent from users and sends requests to the generative AI model and emotion engine to perform analysis and make suggestions.

[1937] 3. Managing Community Features

[1938] Server: Manages community functions, including sending and receiving messages and running forums. Also filters spam and inappropriate content.

[1939] Generative AI models and emotion engines

[1940] The generative AI model and emotion engine will be implemented as an artificial intelligence system with the following functions:

[1941] 1. Data analysis and sentiment recognition

[1942] Generative AI Model: Analyzes received user data and generates alternative activities suitable for the user's mood and environment on that day.

[1943] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotional state. This emotional data is then provided to the AI ​​model for generating more personalized suggestions.

[1944] 2. Proposal generation

[1945] Generative AI Model: Based on data analysis and emotion recognition results, it generates specific activity suggestions for the user. For example, if stress levels are high and emotion recognition identifies "irritation," it will suggest relaxation methods.

[1946] Specific example

[1947] 1. User Registration

[1948] User: Users download the app, enter their name, email address, and drinking frequency to register. The server receives this information and stores it in its database.

[1949] 2. Daily data entry

[1950] User: Enters their mood and circumstances for the day into the app. For example, they might enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." The device then sends this information to the server.

[1951] 3. Analysis of voice and facial expressions

[1952] User: Speak to the app using voice commands or turn your face towards the camera.

[1953] Terminal: Acquires voice data and facial expression data and sends it to the emotion engine.

[1954] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotions. For example, it might generate a result such as "irritated."

[1955] 4. Proposal generation and presentation

[1956] Server: Sends data to the generative AI model and emotion engine and requests suggestions. The generative AI model generates specific activities based on data analysis and emotion recognition results.

[1957] Terminal: Receives suggestions and displays them to the user. The user can select and perform the suggested activities (e.g., relaxation methods or hobbies).

[1958] 5. Use of community features

[1959] Users interact with other users through chat and forums, sharing experiences and opinions. The server manages this.

[1960] 6. Integration with smartwatches

[1961] User: Wears a smartwatch and connects it to the app. The device collects heart rate and stress levels and sends them to the server. The generative AI model and emotion engine then use this data to make more specific suggestions.

[1962] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle.

[1963] The following describes the processing flow.

[1964] Step 1: User Registration

[1965] User: Launch the app for the first time and enter basic information such as name, email address, and daily drinking frequency.

[1966] Terminal: Sends the entered information to the server.

[1967] Server: Stores the received information in the database and returns a success message for account creation to the terminal.

[1968] Terminal: Displays a success message to the user.

[1969] Step 2: Data Entry

[1970] User: Enter information about your mood and environment for the day into the app. For example, you might report, "I'm feeling stressed today," or "I have a strong urge to drink."

[1971] Terminal: Sends the entered data to the server.

[1972] Server: Receives data and saves it to the database.

[1973] Step 3: Request analysis from generative AI models and emotion engines.

[1974] Server: Sends stored data to the generative AI model and sentiment engine for analysis. Specifically, it sends POST requests to the generative AI model and sentiment engine.

[1975] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotions. The results of the emotion recognition are then sent to a generating AI model.

[1976] Generative AI Model: Based on received data and emotion recognition results, it generates optimal alternative activities for the user. For example, it suggests relaxation methods or hobby-related activities.

[1977] Generative AI model: Returns the generated suggestions to the server.

[1978] Step 4: Providing and displaying proposals

[1979] Server: Receives suggestions from the generative AI model and emotion engine, and sends them to the user's terminal.

[1980] Device: Receives suggestions and displays them to the user. For example, it displays a link to "Online yoga sessions you can join now" on the app's home screen.

[1981] Step 5: Utilizing Community Features

[1982] Users: Utilize community features to interact with other users. For example, share experiences and opinions in chats and forums.

[1983] Terminal: Sends user messages to the server and receives and displays messages from other users.

[1984] Server: Sends messages to other relevant user terminals and manages community features. It also filters spam and inappropriate content.

[1985] Step 6: Connecting with a smartwatch (optional)

[1986] User: Wear the smartwatch and connect it to the app.

[1987] Device: Acquires biometric data such as heart rate and stress level from the smartwatch and sends it to the server.

[1988] Server: Sends received biometric data to the generating AI model and emotion engine.

[1989] Generative AI model: Generates more specific suggestions based on biometric data and emotion recognition results. For example, it might suggest deep breathing exercises if the heart rate is high.

[1990] Server: Sends the generated proposal to the terminal.

[1991] Terminal: Notifies the user of suggestions. For example, it displays a notification such as, "Take three deep breaths right now."

[1992] In this way, the system helps users control their cravings for alcohol in a healthy manner.

[1993] (Example 2)

[1994] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1995] In recent years, health problems caused by alcohol consumption have become a social issue. Therefore, effective measures to reduce alcohol consumption are needed. However, conventional technologies struggle to suggest personalized alternative activities tailored to the user's mood and environment, and advanced analysis based on users' emotional states and biometric data is lacking. Furthermore, opportunities for connection and interaction with other users who share similar concerns are insufficient.

[1996] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1997] In this invention, the server includes means for receiving mood and environmental data from the user, means including a generative AI model that analyzes the received data and generates alternative activities for the user, means for presenting the generated alternative activities to the user, means including an emotion engine that analyzes the user's voice and facial expression data and recognizes their emotional state, and means for generating alternative activities based on the analyzed emotional state. As a result, the user can receive personalized alternative activity suggestions that match their mood and emotional state, enabling effective support for reducing alcohol consumption. Furthermore, it is also possible to include a community function for collaborating and interacting with other users who have similar concerns, and to collect biometric data in conjunction with a smartwatch to provide more accurate suggestions.

[1998] A "user" is a person who uses the system, creates an account, and inputs data about their daily mood and environment.

[1999] "Mood and environmental data" refers to information about the user's daily mood and psychological state, as well as the environment and circumstances of that day.

[2000] "Means of receiving data" refers to an interface equipped with the function of collecting data from users and transmitting it to a server or analysis system.

[2001] A "generative AI model" refers to an artificial intelligence system that analyzes received data and generates alternative activities suitable for the user based on the analysis results.

[2002] "Alternative activities" refer to beneficial activities or methods suggested by the system to reduce alcohol consumption, and are generated based on the user's mood and emotional state.

[2003] "Means of presentation" refers to interfaces and devices used to display suggestions from generative AI models and emotion engines to users.

[2004] An "emotion engine" refers to a system that analyzes a user's voice and facial expression data to recognize their emotional state.

[2005] "Voice and facial expression data" refers to biometric data that includes information about the voice and facial expressions emitted by the user, and is the subject of analysis by the emotion engine.

[2006] "Community features" refer to chat and forum functions that allow users to exchange information and support each other with other users who have similar problems.

[2007] A "smartwatch" refers to a wearable device that collects biometric data such as the user's heart rate and stress level, and transmits it to the user's device or a server.

[2008] "Biometric data" refers to information about a user's physical condition, such as heart rate and stress level, collected through devices like smartwatches.

[2009] This invention relates to a system that provides users with beneficial alternative activities and community features to help them avoid health damage caused by alcohol consumption, as well as an emotion recognition function using an emotion engine. This system is mainly implemented by combining a user terminal (smartphone application), a server, a generative AI model, and an emotion engine.

[2010] User device (smartphone app)

[2011] The user terminal will be implemented as a smartphone application for daily use by the user. This application will have the following functions:

[2012] 1. User registration and login function

[2013] Users: When launching the app for the first time, create an account by entering information such as your name, email address, and drinking frequency. If you already have an account, log in by entering your email address and password.

[2014] Terminal: Sends the entered information to the server to create a new account or authenticate login.

[2015] 2. Data Input Interface

[2016] User: Enter data about your daily mood and environment. For example, enter information such as "I'm feeling stressed today" or "I have a strong urge to drink" into the app.

[2017] Terminal: Sends the entered data to the server.

[2018] 3. Receiving and displaying proposals

[2019] Terminal: Receives suggestions from the generative AI model and emotion engine and displays them to the user. For example, specific activities such as "join an online yoga session" or "watch a new movie" may be suggested.

[2020] 4. Community Features

[2021] Users: Utilize community features to interact with other users who share similar concerns. Exchange information and support through chat and forums.

[2022] Server: Manages these community features, including sending and receiving messages and running forums. Also filters spam and inappropriate content.

[2023] 5. Integration with smartwatches

[2024] User: Wear a smartwatch and connect it to the app. The device collects biometric data such as heart rate and stress level.

[2025] Terminal: Sends collected biometric data to the server.

[2026] 6. Emotional Engine

[2027] Device: The emotion engine analyzes voice and facial expression data to recognize the user's emotions. Based on this emotion data, a generative AI model suggests more accurate alternative activities.

[2028] Server-side functionality

[2029] The server has the following functions and will be implemented as a cloud-based system:

[2030] 1. User data management

[2031] Server: Manages user account information, daily input data, and requests to the generative AI model and sentiment engine.

[2032] 2. Communication with generative AI models and emotion engines

[2033] Server: Receives data sent from users and sends requests to the generative AI model and emotion engine to perform analysis and make suggestions.

[2034] 3. Managing Community Features

[2035] Server: Manages community functions, including sending and receiving messages and running forums. Also performs filtering of inappropriate content.

[2036] Generative AI models and emotion engines

[2037] The generative AI model and emotion engine will be implemented as an artificial intelligence system with the following functions:

[2038] 1. Data analysis and sentiment recognition

[2039] Generative AI Model: Analyzes received user data and generates alternative activities suitable for the user's mood and environment on that day.

[2040] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotional state. This emotional data is then provided to the AI ​​model for generating more personalized suggestions.

[2041] 2. Proposal generation

[2042] Generative AI Model: Based on data analysis and emotion recognition results, it generates specific activity suggestions for the user. For example, if stress levels are high and emotion recognition reveals "irritation," it will suggest relaxation methods.

[2043] Specific example

[2044] 1. User Registration

[2045] User: Downloads the app, enters their name, email address, and drinking frequency to register. The server receives this information and stores it in its database.

[2046] 2. Daily data entry

[2047] User: Enters their mood and circumstances for the day into the app. They enter information such as "I'm feeling stressed today" or "I have a strong urge to drink." The device then sends this information to the server.

[2048] 3. Analysis of voice and facial expressions

[2049] User: Speak to the app using voice commands or turn your face towards the camera.

[2050] The device acquires voice and facial expression data and sends it to the emotion engine. The emotion engine analyzes this data and recognizes the user's emotional state. For example, it might generate a result such as "irritated."

[2051] 4. Proposal generation and presentation

[2052] Server: Sends data to the generative AI model and emotion engine and requests suggestions. The generative AI model generates specific activities based on data analysis and emotion recognition results.

[2053] Terminal: Receives suggestions and displays them to the user. The user can select and perform the suggested activities (e.g., "relaxation methods" or "hobby activities").

[2054] 5. Use of community features

[2055] Users interact with other users through chat and forums, sharing experiences and opinions. The server manages this.

[2056] 6. Integration with smartwatches

[2057] User: Wears a smartwatch and connects it to the app. The device collects heart rate and stress levels and sends them to the server. The generative AI model and emotion engine then use this data to make more specific suggestions.

[2058] Examples of prompt statements

[2059] 1. A stressful day

[2060] User: Enter "I'm feeling particularly stressed today, so please tell me some relaxation techniques" as the prompt.

[2061] Generative AI model: Based on the received prompt, it suggests specific relaxation methods (e.g., "Do deep breathing exercises," "Try aromatherapy").

[2062] 2. Days when the urge to drink is strong

[2063] User: Enter the following as the prompt: "I have a strong urge to drink alcohol, so I would like suggestions for alternative hobbies or activities."

[2064] Generative AI model: Based on user sentiment data and daily data analysis results, it suggests hobby activities (e.g., "drawing pictures," "reading books").

[2065] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle.

[2066] The flow of the specific processing in Example 2 will be explained using Figure 13.

[2067] Step 1:

[2068] User Registration / Login

[2069] User: When launching the app for the first time, you will create an account by entering basic information such as your name, email address, and frequency of drinking.

[2070] Terminal: Sends the entered user information to the server.

[2071] Server: Receives user information and stores it in the database. If an existing account exists, it receives the email address and password and verifies them against the database. If authentication is successful, it starts the session.

[2072] Input: The user's basic information is entered here.

[2073] Output: The results of account creation and authentication on the server are output.

[2074] Step 2:

[2075] Daily data entry

[2076] User: Launch the app and enter data about your mood and environment for the day. Specifically, enter information such as "I'm feeling stressed today" or "I have a strong urge to drink."

[2077] Terminal: Sends the entered data to the server.

[2078] Server: Receives data, links it to user information, and saves it to the database.

[2079] Input: Daily data related to mood and environment is entered.

[2080] Output: Daily data stored in the database is output.

[2081] Step 3:

[2082] Collection and analysis of emotional data

[2083] User: Speak to the app using voice commands or turn your face towards the camera.

[2084] Terminal: Collects voice data and facial expression data and sends it to the emotion engine.

[2085] Emotion Engine: Analyzes voice and facial expression data to recognize the user's emotional state. For example, it generates results such as "irritated."

[2086] Terminal: Sends analysis results to the server.

[2087] Input: Voice data and facial expression data are input.

[2088] Output: The analysis results of the emotion engine are output.

[2089] Step 4:

[2090] Proposal generation and presentation

[2091] Server: Inputs daily data and sends emotional data to the AI ​​model for analysis and recommendations.

[2092] Generative AI Model: Analyzes received data and generates specific activity suggestions. For example, if it detects high stress levels, it will suggest "relaxation methods."

[2093] Server: Receives suggestions from the generated AI model and sends them to the user's terminal.

[2094] Terminal: Receives suggestions and displays the suggestions to the user. The user can select and perform the suggested activities.

[2095] Input: Daily data and sentiment data are entered.

[2096] Output: Activity suggestions generated by the generative AI model are output.

[2097] Step 5:

[2098] Using community features

[2099] Users: Utilize the app's community features to interact with other users through chat and forums.

[2100] Server: Manages message sending and receiving, forum operation, and filters inappropriate content.

[2101] Input: Messages and posts from the community are entered here.

[2102] Output: Information about community features managed by the server is output.

[2103] Step 6:

[2104] Collection and linkage of biometric data

[2105] User: Wear the smartwatch and connect it to the app.

[2106] Device: Collects biometric data such as heart rate and stress level from the smartwatch and sends it to the server.

[2107] Server and Generative AI Model: Generates more specific suggestions based on received biometric data.

[2108] Terminal: Displays specific activity suggestions to the user from the generated AI model.

[2109] Input: Biometric data from a smartwatch is entered.

[2110] Output: Specific activity suggestions generated by the AI ​​model are output.

[2111] Through these steps, the system provides users with personalized alternative activity suggestions and offers effective support for reducing alcohol consumption.

[2112] (Application Example 2)

[2113] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2114] In modern society, the health risks associated with alcohol consumption are a major problem. In particular, because moderate alternative activities are not readily available, many people try to relieve stress and cravings with alcohol. However, there is a lack of specific and personalized suggestions tailored to individual circumstances. Therefore, there is a need for effective support systems to help users maintain a healthy lifestyle.

[2115] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[2116] In this invention, the server includes means for receiving mood and environmental data from the user, means for analyzing the received data and generating alternative activities for the user using a generative AI model, means for presenting the generated alternative activities to the user, means for analyzing the user's voice and facial expression data using an emotion recognition engine and identifying their emotional state, and means for the generative AI model to suggest even more accurate alternative activities based on the emotional state. As a result, the user can receive personalized alternative activity suggestions based on their emotional state and biometric data, making it easier to maintain a healthy lifestyle.

[2117] "User" refers to an individual who uses the system.

[2118] "Mood and environmental data" refers to information about the user's everyday emotions and surrounding circumstances.

[2119] "Means of receiving" refers to methods and devices for securing data transmitted by users.

[2120] "Means of analysis" refers to methods and devices that analyze received data to derive meaningful information.

[2121] A "generative AI model" refers to an artificial intelligence algorithm that generates new suggestions and activities based on received and analyzed data.

[2122] "Alternative activities" refer to beneficial activities or hobbies that help prevent drinking.

[2123] "Means of presentation" refers to the methods or devices used to show the generated activities or suggestions to the user.

[2124] An "emotion recognition engine" refers to a system that analyzes voice and facial expression data to identify the user's emotional state.

[2125] "Voice and facial expression data" refers to information about the user's voice and facial expressions.

[2126] "Biometric data" refers to physical information such as heart rate and stress levels collected using devices like smartwatches.

[2127] "Community features" refer to online platforms that allow users to exchange information and support each other with similar problems.

[2128] The system of the present invention is composed of a user terminal, a server, a generative AI model, an emotion recognition engine, and biosensor devices such as a smartwatch.

[2129] User terminal (smartphone app)

[2130] The user terminal will be implemented as a smartphone application with the following functions. This application is intended for daily use by the user.

[2131] 1. User registration and login function

[2132] Users create an account upon first launch by entering basic information such as their name, email address, and frequency of drinking. If an existing account exists, they can access it using the login function.

[2133] 2. Data Input Interface

[2134] Users utilize an interface to input data about their daily mood and environment. For example, they might report situations such as "I'm feeling stressed today" or "I have a strong urge to drink."

[2135] 3. Receiving and displaying proposals

[2136] The device receives suggestions from the generative AI model and emotion recognition engine and displays them to the user. For example, it might suggest specific activities such as "join an online yoga session" or "watch a new movie."

[2137] 4. Community Features

[2138] Users can utilize community features to interact with other users who share similar concerns. Information exchange and support are provided through chat and forums.

[2139] 5. Integration with smartwatches

[2140] The device works in conjunction with a smartwatch to collect biometric data. Based on this data, it monitors the user's current state in real time and suggests appropriate activities.

[2141] 6. Emotion Recognition Engine

[2142] The device uses an emotion recognition engine to analyze voice and facial expression data to recognize the user's emotions. Based on this emotion data, a generative AI model suggests more accurate alternative activities.

[2143] Server-side functionality

[2144] The server will be implemented as a cloud-based system with the following functions:

[2145] 1. User data management

[2146] The server manages user account information, daily input data, and requests to the generative AI model and emotion recognition engine.

[2147] 2. Communication with generative AI models and emotion recognition engines

[2148] The server receives data sent by the user and sends requests to the generative AI model and emotion recognition engine to perform analysis and make suggestions.

[2149] 3. Managing Community Features

[2150] The server manages community functions, including sending and receiving messages and running forums. It also filters spam and inappropriate content.

[2151] Generative AI models and emotion recognition engines

[2152] The generative AI model and emotion recognition engine will be implemented as an artificial intelligence system with the following functions:

[2153] 1. Data analysis and sentiment recognition

[2154] The generative AI model analyzes the received user data and generates alternative activities that are suitable for the user's mood and environment on that day.

[2155] The emotion recognition engine analyzes voice and facial expression data to recognize the user's emotional state. This emotional data is then provided to the AI ​​model for generating more personalized suggestions.

[2156] 2. Proposal generation

[2157] The generative AI model generates specific activity suggestions for the user based on data analysis and emotion recognition results. For example, if stress levels are high and emotion recognition identifies "irritation," it will suggest relaxation methods.

[2158] Presentation of specific examples and prompt statements

[2159] For example, the following prompt could represent emotional data when a user is feeling stressed.

[2160] Example of a prompt:

[2161] I'm feeling very stressed today. I have a strong urge to drink, but what can I do to control it?

[2162] Based on this data, the generated AI model and emotion recognition engine work together to suggest specific alternative activities.

[2163] Hardware and software to be used

[2164] User devices: Smartphones, smartwatches

[2165] Server: Cloud service platform (e.g., AWS, Google Cloud)

[2166] Generative AI models and emotion recognition engines: Deep learning frameworks (e.g., TensorFlow, PyTorch)

[2167] As described above, the system of the present invention comprehensively provides support to users in reducing alcohol consumption and maintaining a healthy lifestyle.

[2168] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2169] Step 1:

[2170] The user launches the smartphone app and uses the user registration / login function to enter basic information such as their name, email address, and frequency of drinking. This input data is received by the device and sent to the server. The server stores this data in a database.

[2171] Input: Name, email address, and basic information about your drinking frequency.

[2172] Output: User information stored in the server's database

[2173] Step 2:

[2174] Users report daily mood and environmental data using the in-app data input interface. For example, they might write, "I'm feeling stressed today" or "I have a strong urge to drink." This input data is then sent back to the server by the device and recorded.

[2175] Input: Data related to mood and environment

[2176] Output: Daily data sent to and recorded on the server

[2177] Step 3:

[2178] Users provide emotional data by speaking aloud or facing the camera. The device acquires the voice and facial expression data and sends it to an emotion recognition engine. The emotion recognition engine analyzes the data and identifies the user's emotional state. This result is then sent to a generative AI model.

[2179] Input: Voice data and facial expression data

[2180] Output: Identification of emotional state by emotion recognition engine

[2181] Step 4:

[2182] The server sends daily mood and environmental data, as well as emotional data from the emotion recognition engine, to a generative AI model. The generative AI model analyzes this data and generates alternative activities based on the user's current state. These activity suggestions are then sent to the server.

[2183] Input: Mood and environmental data, emotional data

[2184] Output: Suggestions for alternative activities using a generative AI model.

[2185] Step 5:

[2186] The server sends alternative activity suggestions received from the generated AI model to the terminal, and the user terminal displays them to the user. The user can then select and perform the displayed activity suggestion.

[2187] Input: Activity suggestions from a generated AI model

[2188] Output: Alternative activities displayed to the user

[2189] Step 6:

[2190] Users utilize the app's community features to interact with other users who share similar concerns through chat and forums. The server manages the community features, handling message sending and receiving, and running the forums.

[2191] Input: Chat messages and forum posts from users

[2192] Output: Information exchange and support with other users

[2193] Step 7:

[2194] Users wear biosensor devices such as smartwatches and connect them to the app. The device collects biometric data such as heart rate and stress levels from the smartwatch and sends it to a server. The server provides this biometric data to a generating AI model and emotion recognition engine, which then suggests more specific activities.

[2195] Input: Biometric data obtained from a smartwatch

[2196] Output: Specific activity suggestions generated by a generative AI model and emotion recognition engine.

[2197] Through these steps, the system provides effective support for reducing alcohol consumption and helps users maintain a healthy lifestyle.

[2198] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[2199] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2200] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[2201] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2202] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[2203] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[2204] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[2205] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[2206] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[2207] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[2208] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[2209] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[2210] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[2211] 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.

[2212] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[2213] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Ar...

Claims

1. A means of receiving mood and environmental data from users, A means for analyzing received data and generating alternative activities for the user, A means of presenting the generated alternative activity to the user, A system that includes this.

2. In the system described in claim 1, A system that further includes means to provide community features for users who have similar problems to collaborate and interact with each other.

3. In the system described in claim 1, A system that further includes means for collecting biometric data in conjunction with a smartwatch and generating alternative activities based on the collected biometric data.

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