system

Abstract

Provide a system. [Solution] means for performing user authentication; means for collecting user input information; a means for analyzing the collected information; and A means of generating a list of appropriate foods, nutrients, and supplements based on the analysis results; A means of assessing the safety of processed foods and food additives; means for providing the generated list and rating information to a user; means for generating and providing health advice and prevention methods; A means of reminding people to check their health regularly, A system including:

Description

[Technical Field]

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

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

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

[0004] In recent years, as health consciousness has grown, so has interest in the safety of processed foods and food additives. However, there is an abundance of information available, making it difficult for average consumers to discern its authenticity. Furthermore, there are limited means of obtaining specific advice on how to select appropriate foods and nutrients based on individual health conditions and dietary habits, and how to prevent health hazards. Against this backdrop, there is a growing need for a system that can centrally evaluate the risks of processed foods and food additives, provide health advice, and remind people to take regular health checks. [Means for solving the problem]

[0005] The present invention solves the above problems by the following means.

[0006] A system is provided that includes a means for user authentication, a means for collecting user-entered information, a means for analyzing the collected information, a means for generating a list of appropriate foods, nutrients, and supplements based on the analysis results, a means for evaluating the safety of processed foods and food additives, a means for providing the generated list and evaluation information to the user, a means for generating and providing health advice and preventative measures, and a means for reminding users to take regular health checks.This allows users to select appropriate foods and nutrients based on their own health condition and dietary habits, and receive specific advice to prevent health damage.Furthermore, the system supports continuous health management with a function for reminding users to take regular health checks.

[0007] "User authentication" is the process by which a user logs into a system and verifies their identity using authentication information such as a username and password.

[0008] "User-input information" refers to data provided by a user to the system, and includes individual information such as health status, dietary habits, and allergy information.

[0009] "Information analysis" is the data processing process by which the system generates a list of suitable foods, nutrients, and supplements based on the collected user-entered information.

[0010] "Safety assessment" is the process of analyzing information about processed foods and food additives and evaluating their risk and safety.

[0011] "Health advice" provides specific instructions and suggestions for improving health and preventing disease based on the user's health condition and dietary habits.

[0012] "Remind" is a function that sends notifications and alerts to users to encourage them to take important actions such as regular health checks.

[0013] A "session key" is a temporary identification code that indicates that the user's logged-in session is valid, and is generated after successful authentication.

[0014] A "database" is a collection of information managed within a system, and is used for the purpose of storing and managing data such as user information, input information, and analysis results.

[0015] "Analysis results" refers to data generated based on the analysis of user-entered information, including lists of appropriate foods and nutrients, safety assessment results, etc. [Brief explanation of the drawings]

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

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

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

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

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

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

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

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

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

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

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

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

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

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

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

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

[0037] The present invention is a system for enabling users to efficiently manage their health, analyzing information input by the user and providing appropriate health advice. A specific operation method of the system will be described below.

[0038] User Authentication

[0039] User:

[0040] The user accesses the login screen and enters their "user name" and "password."

[0041] Device:

[0042] The terminal sends the "user name" and "password" entered by the user to the server.

[0043] server:

[0044] The server checks the received authentication information against a database, and if authentication is successful, generates a session key and returns the generated session key to the terminal.

[0045] Device:

[0046] The terminal notifies the user that the authentication was successful and displays the dashboard screen.

[0047] Collecting user-entered information

[0048] User:

[0049] Users go to the "Enter Health Information" page in the dashboard and enter information such as "health status," "diet," and "allergy information."

[0050] Device:

[0051] The terminal transmits the information entered by the user to the server.

[0052] server:

[0053] The server saves the received information in a database and returns a notification to the device that saving is complete.

[0054] Information analysis

[0055] server:

[0056] The server runs algorithms that generate lists of suitable foods, nutrients, and supplements based on user-entered information in the database, and also performs safety assessments of processed foods and food additives.

[0057] Providing health advice

[0058] server:

[0059] The server documents specific health advice and preventive measures based on the generated list and safety assessment results.

[0060] Device:

[0061] The terminal displays the health advice and prevention methods received from the server to the user.

[0062] Regular health check reminders

[0063] server:

[0064] The server registers the next health check date in the schedule based on the user's check interval and generates a reminder message.

[0065] Device:

[0066] The device notifies the user of reminder messages and encourages regular health checks.

[0067] Specific examples

[0068] As a concrete example, the following scenario will be described.

[0069] Example 1: Entering and Evaluating New Health Information

[0070] User:

[0071] After logging in, the user enters their "weight," "dietary details," and "allergy information."

[0072] Device:

[0073] The input information is sent to the server.

[0074] server:

[0075] The information is stored in a database, appropriate food and nutrient lists are generated, and processed food safety is assessed.

[0076] server:

[0077] Based on the generated list and the evaluation results, health advice is created and sent to the device.

[0078] Device:

[0079] Health advice such as "Foods containing omega-3 fatty acids are beneficial for you" is displayed.

[0080] Example 2: Health check reminder

[0081] server:

[0082] Set the user's next health check date to three months later.

[0083] server:

[0084] When the set date and time approaches, a reminder message will be sent to your device.

[0085] Device:

[0086] A reminder message is sent to the user saying, "It's time for a health check."

[0087] The system of the present invention allows users to easily and efficiently manage their own health, make appropriate food choices, and take preventative measures, thereby contributing to the prevention of health hazards.

[0088] The processing flow will be explained below.

[0089] Program processing steps

[0090] User Authentication

[0091] Step 1:

[0092] User: Enter your "username" and "password" on the login screen.

[0093] Step 2:

[0094] Terminal: Sends the entered authentication information to the server.

[0095] Step 3:

[0096] Server: Compares the received authentication information with a database and performs user authentication.

[0097] Step 4:

[0098] Server: If authentication is successful, generates a session key and returns it to the terminal.

[0099] Step 5:

[0100] Terminal: The authentication result is displayed to the user, and if successful, the user is taken to the dashboard screen.

[0101] Collecting user-entered information

[0102] Step 1:

[0103] User: Enter information such as "health condition," "diet," and "allergy information" on the "Enter Health Information" page in the dashboard.

[0104] Step 2:

[0105] Terminal: Sends the entered information to the server.

[0106] Step 3:

[0107] Server: Stores the received information in a database.

[0108] Step 4:

[0109] Server: Sends confirmation of save completion to the device.

[0110] Information analysis

[0111] Step 1:

[0112] Server: Retrieves user input information from the database.

[0113] Step 2:

[0114] Server: Runs the algorithms that evaluate foods and nutrients.

[0115] Step 3:

[0116] Server: Generates a list of suitable foods, nutrients, and supplements.

[0117] Step 4:

[0118] Server: Evaluates the safety of processed foods and food additives.

[0119] Step 5:

[0120] Server: Stores the analysis results and safety evaluation results in a database.

[0121] Providing health advice

[0122] Step 1:

[0123] Server: Generates health advice based on the analysis results and safety assessment results.

[0124] Step 2:

[0125] Server: Sends health advice to the device.

[0126] Step 3:

[0127] Terminal: displays health advice to the user.

[0128] Regular health check reminders

[0129] Step 1:

[0130] Server: Schedules the user's next health check.

[0131] Step 2:

[0132] Server: Generates reminder messages based on configured intervals.

[0133] Step 3:

[0134] Server: Sends reminder messages to the device.

[0135] Step 4:

[0136] Terminal: Notify the user of the reminder message.

[0137] Example 1

[0138] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0139] Conventional health management systems struggle to efficiently provide appropriate health advice that takes into account a user's health status, diet, and allergy information. They also lacked reminders for regular health checks, and did not provide sufficient support for users to continuously manage their health. Furthermore, some systems lacked session management and generative AI models, resulting in a poor user experience.

[0140] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0141] In this invention, the server includes means for user authentication, means for collecting user-input information, means for analyzing the collected information, means for generating a list of appropriate foods, nutrients, and supplements based on the analysis results, means for evaluating the safety of processed foods and food additives, means for providing the generated list and evaluation information to the user, means for generating and providing health advice and preventive methods, means for reminding users to take regular health checks, means for generating and managing session keys, and means for creating health advice and reminder messages using a generative AI model, thereby enabling users to efficiently and continuously manage their own health.

[0142] "User authentication" is the process of verifying a user's identity when they access a system.

[0143] "User input information" refers to data such as health status, dietary habits, and allergy information that the user provides to the system.

[0144] "Means of analyzing information" refers to the method of analyzing and evaluating related data based on collected user-entered information.

[0145] The "means for generating a list of foods, nutrients, and supplements" is a method for selecting and listing foods, nutrients, and supplements suitable for the user based on the analysis results.

[0146] "Means for safety assessment" refers to the methods used to evaluate the safety of processed foods and food additives and reflect the results in the list.

[0147] The "means for providing to the user" refers to a method for conveying the generated list and rating information to the user.

[0148] The "means for generating and providing health advice and preventive measures" is a method for generating and providing specific health advice and preventive measures to the user based on the analysis results.

[0149] The "means for reminding users to check their health" is a method for generating and notifying reminder messages to encourage users to check their health regularly.

[0150] The "means for generating and managing a session key" is a method for generating and managing a session key for identifying a user during a session after user authentication has been successful.

[0151] A "generative AI model" is an artificial intelligence model used for natural language generation and data analysis, and an example is the GPT series.

[0152] The present invention is a system for enabling users to efficiently manage their health by analyzing input information from the user and providing appropriate health advice. Specific implementation and operation methods of the system are described below.

[0153] System configuration

[0154] The present invention consists of a user terminal, a server, and a database. The user terminal can be a PC, smartphone, tablet, etc. The server is a high-performance computer equipped with a database management system (e.g., MySQL (registered trademark)) and analytical software (e.g., Python scripts). In addition, a generative AI model (e.g., GPT-4 (registered trademark)) is used for natural language generation and data analysis.

[0155] User Authentication

[0156] The user accesses the login screen using a terminal and enters their "user name" and "password." This authentication information is sent from the terminal to the server via a secure protocol (HTTPS). The server compares the received information with data in a database, and if authentication is successful, it generates a session key and returns it to the terminal. The terminal notifies the user that authentication was successful and displays the dashboard screen.

[0157] Collecting user-entered information

[0158] The user goes to the "Enter Health Information" page in the dashboard and enters information such as "health status," "diet," and "allergy information." This information is sent from the device to the server in JSON format. The server stores the received information in a database and notifies the device once it has been saved.

[0159] Information analysis

[0160] The server retrieves user information from the database and analyzes it using Python scripts. Based on the analysis results, it generates a list of appropriate foods, nutrients, and supplements. It also evaluates the safety of processed foods and food additives and lists the results.

[0161] Providing health advice

[0162] The server then documents specific health advice and preventative measures based on the generated list and safety assessment results. This process uses a generative AI model (GPT-4). The generated advice is sent to the device and displayed to the user. For example, advice such as "Foods containing omega-3 fatty acids are beneficial for you" is provided.

[0163] Regular health check reminders

[0164] The server schedules the next health check based on the user's check interval. When the scheduled date and time approaches, it uses a generative AI model to create a reminder message and sends it to the device. The device then notifies the user of this reminder message, encouraging them to perform regular health checks. For example, a message saying, "It's time for a health check."

[0165] Specific examples

[0166] Here is a specific example.

[0167] Example 1: After logging in, a user enters their weight, dietary details, and allergy information, and the device sends the information to the server. The server stores the information in a database, generates a list of appropriate foods and nutrients, and provides health advice.

[0168] Example 2: The server sets the user's next health check date three months from now, and when the set date and time approaches, it generates a reminder message and sends it to the device.

[0169] In this way, users can efficiently and continuously manage their own health.

[0170] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0171] Step 1:

[0172] User: The user accesses the login screen and enters their "username" and "password."

[0173] Enter: "Username" and "Password"

[0174] Output: Sends authentication information to the terminal

[0175] Specific behavior: The user completes the login screen and clicks the "Login" button.

[0176] Step 2:

[0177] Terminal: The terminal encrypts the "username" and "password" entered by the user and sends them to the server via a secure protocol (e.g., HTTPS).

[0178] Input: Encrypted "Username" and "Password"

[0179] Output: Sends authentication information to the server

[0180] Specific operation: The device protects the information entered using SSL / TLS encryption and sends it to the server as an HTTPS request.

[0181] Step 3:

[0182] Server: The server checks the received credentials against a database (e.g. MySQL) using a hashed password.

[0183] Input: Received authentication information

[0184] Output: Authentication result (success or failure)

[0185] Specific operation: The server compares the hash value of the received information with the user information stored in the database.

[0186] Step 4:

[0187] Server: If authentication is successful, the server generates a random session key and returns it to the device.

[0188] Input: Authentication success flag

[0189] Output: Session key

[0190] Specific operation: The server generates a session ID, temporarily stores it in a database, and sends it back to the device.

[0191] Step 5:

[0192] Terminal: The terminal notifies the user that authentication was successful and displays the dashboard screen.

[0193] Input: Session key

[0194] Output: Dashboard screen display

[0195] Specific behavior: The device saves the received session key and displays the dashboard to the user along with a successful login message.

[0196] Step 6:

[0197] User: The user goes to the "Enter Health Information" page in the dashboard and enters information such as "health status," "diet," and "allergy information."

[0198] Input: "Health status", "Diet", "Allergy information"

[0199] Output: Sends information to the terminal

[0200] What happens: A user fills in a form and clicks the "Submit" button.

[0201] Step 7:

[0202] Terminal: The terminal sends the information entered by the user to the server, using JSON format data.

[0203] Input: User input information (JSON format)

[0204] Output: Sends input information to the server

[0205] Specific operation: The device converts the input information into JSON format and sends it to the server via an HTTPS request.

[0206] Step 8:

[0207] Server: The server stores the received information in a database.

[0208] Input: User input information (JSON format)

[0209] Output: Save result (success or failure)

[0210] Specific operation: The server writes the received information to the database.

[0211] Step 9:

[0212] Server: The server returns a notification to the device that the save is complete.

[0213] Input: Save success flag

[0214] Output: Save completion notification

[0215] Specific behavior: The server confirms the success of the save and returns a notification to the device as an HTTPS response.

[0216] Step 10:

[0217] Server: The server retrieves the user information from the database and runs the analysis algorithm.

[0218] Input: User information

[0219] Output: Analysis results (food list, safety assessment)

[0220] What it does: The server runs a Python script to evaluate the list of suitable foods and nutrients and the safety of processed foods.

[0221] Step 11:

[0222] Server: The server uses generative AI models to document health advice and prevention methods.

[0223] Input: Analysis results

[0224] Output: Health advice and prevention methods (text)

[0225] Specific operation: The server runs a generative AI model (e.g., GPT-4) and generates advice in natural language based on the analysis results.

[0226] Step 12:

[0227] Server: The server sends the generated advice and prevention methods to the device.

[0228] Input: Health advice and prevention methods (text)

[0229] Output: Send advice to terminal

[0230] Specific operation: The server returns the generated text to the terminal as an HTTPS response.

[0231] Step 13:

[0232] Terminal: The terminal displays the health advice and prevention methods received from the server to the user.

[0233] Input: Advice received from the server

[0234] Output: Display advice to the user

[0235] Specific operation: The terminal displays the received information on the user screen in an appropriate format.

[0236] Step 14:

[0237] Server: The server schedules the next health check date based on the user's check interval.

[0238] Input: User check interval

[0239] Output: Next health check date

[0240] Specific operation: The server registers the next health check date in the schedule management system.

[0241] Step 15:

[0242] Server: When the set date and time approaches, the server uses a generative AI model to generate a reminder message.

[0243] Input: Next health check date

[0244] Output: Reminder message (text)

[0245] Specific operation: The server uses the generative AI model to generate appropriate reminder text.

[0246] Step 16:

[0247] Server: The server sends the generated remind message to the device.

[0248] Input: Reminder message (text)

[0249] Output: Send a reminder message to the device

[0250] Specific operation: The server sends the generated message to the terminal as an HTTPS response.

[0251] Step 17:

[0252] Device: The device will notify the user as a reminder message that it is time for a health check.

[0253] Input: Reminder message received from the server

[0254] Output: Notify the user

[0255] What happens: The device displays a reminder message to the user and notifies the user using the notification system.

[0256] (Application example 1)

[0257] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0258] Conventional health management systems make it difficult for users to select appropriate foods and nutrients based on their own health information. They also lacked a means to effectively recommend related products and services, making it difficult for users to make optimal purchasing decisions based on their health status. Furthermore, they lacked a mechanism to provide health advice while also encouraging actual purchasing behavior.

[0259] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0260] In this invention, the server includes means for user authentication, means for collecting user-entered information, means for analyzing the collected information, means for recommending appropriate products and services based on the analysis results, means for evaluating the safety of processed products and ingredients, means for providing the generated list and evaluation information to the user, means for generating and providing health advice and preventive methods, means for reminding the user to take regular health checks, and means for displaying links to online shopping sites to facilitate purchases. This allows users to easily select optimal products and services based on their own health condition and efficiently manage their health.

[0261] "User authentication" is the process by which a user accesses a system using their authentication information (e.g., username and password).

[0262] "User-input information" refers to data such as health status, dietary habits, and allergy information that a user provides to the system.

[0263] "Information analysis" is data processing to recommend appropriate products and foods based on collected user-entered information.

[0264] "Product recommendation" is the process of presenting optimal products and services to users based on the results of information analysis.

[0265] "Ingredient safety evaluation" is a procedure for evaluating the safety of processed products and ingredients and providing that information to users.

[0266] "Providing a list" is a procedure for transmitting the generated list of products and services and evaluation information to users.

[0267] "Health advice" is a procedure that provides specific health management methods and preventative measures based on the user's health information.

[0268] "Remind" is a procedure that notifies the user when it is time for a regular health check and encourages them to carry out the check.

[0269] "Mail Order Link" is a procedure for generating and displaying a link that allows users to purchase recommended products or services.

[0270] This specification details a specific embodiment of a system for efficiently managing a user's health. The system collects and analyzes health information provided by the user, recommends appropriate products and nutrients, and provides links to online shopping sites to encourage users to make purchases.

[0271] System Overview

[0272] The system includes the following elements:

[0273] A means of user authentication

[0274] A means of collecting user input information

[0275] How we analyze the information we collect

[0276] A means of recommending appropriate products and services based on analysis results

[0277] A means of assessing the safety of processed products and ingredients

[0278] Means for providing generated list and rating information to a user

[0279] A means of generating and delivering health advice and prevention methods

[0280] A means of reminding people to check their health regularly

[0281] Displaying links to online shopping sites to make purchasing easier

[0282] Hardware and Software Configuration

[0283] Hardware

[0284] Smartphone: a device on which the user operates an interface

[0285] Server: Backend server that stores and processes data

[0286] software

[0287] Flask: A lightweight web framework built in Python

[0288] sqlite3: a local database management system

[0289] React: Used to build the front-end user interface

[0290] Data processing and calculation

[0291] User Authentication

[0292] The user enters their authentication information (username and password) and sends it to the server, which checks it against the database and, if authentication is successful, generates and returns a session key.

[0293] Collecting user-entered information

[0294] The user enters information about their health, diet, allergies, etc., and the device sends this information to the server, which then stores the received information in a database.

[0295] Information analysis

[0296] The server analyzes the user-entered information in the database and performs data calculations to recommend appropriate products, nutrients, and supplements. Using a generative AI model, it analyzes the data based on the prompt text and generates results.

[0297] Providing health advice

[0298] The server generates specific health advice and preventive measures based on the user's health information and sends them to the device, which then displays them to the user.

[0299] Reminders and shopping links

[0300] The server sets the date for the user's next health check and generates a reminder message. The device notifies the user of this and encourages regular health checks. The device also displays a link to purchase recommended products, allowing the user to easily access the online shopping site.

[0301] Specific examples

[0302] Example 1: Entering and Evaluating New Health Information

[0303] After logging in, users enter their health information (weight, dietary habits, and allergy information). The device sends the information to the server, which stores it in a database. The server uses a generative AI model to generate a list of appropriate foods and nutrients and evaluates the safety of processed foods. Based on the results, health advice and product recommendations are provided and notified to the user.

[0304] Example prompt sentence:

[0305] Recommend optimal foods and nutrients based on your health, diet, and allergies. Use the following information:

[0306] Health: Weight gain in the past week

[0307] Diet: Few vegetables in daily meals

[0308] Allergy Information: Nut allergy

[0309] Example 2: Displaying online shopping links and encouraging purchases

[0310] The server creates a list of recommended products based on the analysis results and generates a link to the online shopping site. The device displays this to the user, who can click on the product link to access the online shopping site and make a purchase.

[0311] As described above, the system of the present invention allows users to easily select optimal products and services based on their own health condition, and efficiently manage their health.

[0312] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0313] Step 1:

[0314] When a user opens the app, a login screen appears. The user enters their authentication information (username and password). The entered information is sent from the device to the server.

[0315] Input: Username, Password

[0316] Output: Sending authentication information to the server

[0317] Step 2:

[0318] The server checks the received authentication information against a database, and if authentication is successful, generates a session key and returns the generated session key to the terminal.

[0319] Input: Credentials

[0320] Output: Session key, authentication result

[0321] Step 3:

[0322] The device notifies the user that authentication was successful and displays the dashboard screen. The user then moves to the "Enter Health Information" page to enter data such as health status, dietary habits, and allergy information.

[0323] Input: Session key, user information

[0324] Output: View dashboard

[0325] Step 4:

[0326] After entering health information, the user sends the information from the device to the server, which stores the information in a database and returns a notification to the device that the information has been saved.

[0327] Input: Health information (e.g., health condition, diet, allergy information)

[0328] Output: Saving to database, notification of saving completion

[0329] Step 5:

[0330] The server analyzes the user-entered information stored in the database and uses a generative AI model to generate a list of appropriate foods and nutrients based on the prompt.

[0331] Input: User's health information

[0332] Output: List of foods and nutrients

[0333] Step 6:

[0334] The server uses the generated list and other data to evaluate the safety of processed products and ingredients, and then compiles the evaluation results into written advice for the user.

[0335] Input: list of foods and nutrients, generative AI model

[0336] Output: Safety assessment, health advice

[0337] Step 7:

[0338] The server sends the generated advice to the terminal, which displays it to the user. The terminal then displays further recommended information on suitable products and services, as well as links to online shopping sites where the products can be purchased.

[0339] Input: Health advice, assessment results

[0340] Output: Display advice, display mail order link

[0341] Step 8:

[0342] When a user clicks on a shopping link, a browser is launched and the specified shopping site is opened, allowing the user to easily purchase the product.

[0343] Input: Click on the online shopping link

[0344] Output: Display of online shopping site, facilitating product purchase

[0345] Step 9:

[0346] The server sets the date of the user's next health check and generates a reminder message. When the set date and time approaches, the reminder message is sent to the device. The device then notifies the user of the reminder message.

[0347] Input: User health check interval

[0348] Output: Generate reminder message, notification

[0349] Through the above processing steps, the system of the present invention enables users to efficiently manage their health and conveniently purchase related products and services.

[0350] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0351] The present invention is a system for efficiently managing a user's health, and in particular, recognizes the user's emotions and provides health advice and reminders based on those emotions. The specific operation of the system is described below.

[0352] User Authentication

[0353] User:

[0354] The user accesses the login screen and enters their "user name" and "password."

[0355] Device:

[0356] The terminal sends the "user name" and "password" entered by the user to the server.

[0357] server:

[0358] The server compares the received authentication information with a database to authenticate the user. If authentication is successful, it generates a session key and returns it to the terminal.

[0359] Device:

[0360] The terminal displays the authentication result to the user, and if successful, transitions to the dashboard screen.

[0361] Collecting user-entered information

[0362] User:

[0363] Users enter information such as their health status, diet, and allergy information on the "Enter Health Information" page within the dashboard.

[0364] Device:

[0365] The entered information is sent to the server.

[0366] server:

[0367] The received information is saved in the database, and a notification that saving is complete is returned to the device.

[0368] Information analysis

[0369] server:

[0370] It takes user input from the database and runs algorithms to evaluate foods and nutrients, generates lists of suitable foods, nutrients, and supplements, and evaluates the safety of processed foods and food additives.

[0371] server:

[0372] The analysis results and safety evaluation results are stored in a database.

[0373] Providing health advice

[0374] server:

[0375] Health advice is generated based on the analysis results and safety assessment results, taking into account emotion recognition results from the emotion engine.

[0376] Device:

[0377] Health advice is displayed to the user. For example, if the user is feeling stressed, it also provides ways to alleviate the stress.

[0378] Regular health check reminders

[0379] server:

[0380] Schedule the user's next health check. Generate reminder messages based on the interval you set.

[0381] server:

[0382] Send a reminder message to your device.

[0383] Device:

[0384] Reminder messages are sent to users to encourage them to check their health.

[0385] Emotion Engine Operation

[0386] User:

[0387] Emotions are analyzed from video, audio, and text information entered or uploaded by the user.

[0388] Device:

[0389] The emotion data is sent to the server.

[0390] server:

[0391] The emotion engine analyzes the transmitted data and recognizes the user's emotions. The recognition results are stored in a database and used to generate health advice.

[0392] Specific examples

[0393] Example 1: Entering and Evaluating New Health Information

[0394] User:

[0395] After logging in, users enter their weight, dietary information, and allergy information. They also enter or upload information that indicates their current emotional state.

[0396] Device:

[0397] The input information and emotion data are sent to the server.

[0398] server:

[0399] The information is stored in a database and a list of appropriate foods and nutrients is generated. If the user is feeling stressed, it will recommend foods and activities that will help relieve stress.

[0400] Device:

[0401] The advice displayed is, "Foods containing omega-3 fatty acids are beneficial for you. You seem to have been feeling stressed lately, so try meditating to help you relax."

[0402] Example 2: Health check reminder

[0403] server:

[0404] Set the user's next health check date three months from now. If the user has recently reported stress, set an earlier reminder message.

[0405] server:

[0406] When the set date and time approaches, a reminder message will be sent to your device.

[0407] Device:

[0408] It notifies you, "It's time for a health check. Let's also check your recent stress level."

[0409] The system of the present invention supports users in optimal health management based on their own health and emotional state. By combining it with an emotion engine, it becomes possible to provide more personalized health advice, which is of great help to users in improving their health and preventing disease.

[0410] The processing flow will be explained below.

[0411] Program processing steps

[0412] User Authentication

[0413] Step 1:

[0414] User: Enter your "username" and "password" on the login screen.

[0415] Step 2:

[0416] Terminal: Sends the entered authentication information to the server.

[0417] Step 3:

[0418] Server: Compares the received authentication information with a database and performs user authentication.

[0419] Step 4:

[0420] Server: If authentication is successful, generates a session key and returns it to the terminal.

[0421] Step 5:

[0422] Terminal: The authentication result is displayed to the user, and if successful, the user is taken to the dashboard screen.

[0423] Collecting user-entered information

[0424] Step 1:

[0425] User: Enter information such as "health condition," "diet," and "allergy information" on the "Enter Health Information" page in the dashboard.

[0426] Step 2:

[0427] Terminal: Sends the entered information to the server.

[0428] Step 3:

[0429] Server: Stores the received information in a database.

[0430] Step 4:

[0431] Server: Sends confirmation of save completion to the device.

[0432] Information analysis

[0433] Step 1:

[0434] Server: Retrieves user input information from the database.

[0435] Step 2:

[0436] Server: Runs the algorithms that evaluate foods and nutrients.

[0437] Step 3:

[0438] Server: Generates a list of suitable foods, nutrients, and supplements.

[0439] Step 4:

[0440] Server: Evaluates the safety of processed foods and food additives.

[0441] Step 5:

[0442] Server: Stores the analysis results and safety evaluation results in a database.

[0443] Providing health advice

[0444] Step 1:

[0445] Server: Generates health advice based on the analysis results and safety assessment results, taking into account emotion recognition results from the emotion engine.

[0446] Step 2:

[0447] Server: Sends health advice to the device.

[0448] Step 3:

[0449] Terminal: displays health advice to the user.

[0450] Regular health check reminders

[0451] Step 1:

[0452] Server: Schedules the user's next health check.

[0453] Step 2:

[0454] Server: Generates reminder messages based on configured intervals.

[0455] Step 3:

[0456] Server: Sends reminder messages to the device.

[0457] Step 4:

[0458] Terminal: Notify the user of the reminder message.

[0459] Emotion Engine Operation

[0460] Step 1:

[0461] User: Analyze emotions from video, audio, and text information you input or upload.

[0462] Step 2:

[0463] Terminal: Sends emotion data to the server.

[0464] Step 3:

[0465] Server: The emotion engine analyzes the transmitted data and recognizes the user's emotion.

[0466] Step 4:

[0467] Server: Stores emotion recognition results in a database and uses them to generate health advice.

[0468] Specific examples

[0469] Example 1: Entering and Evaluating New Health Information

[0470] Step 1:

[0471] User: After logging in, the user enters their weight, dietary information, and allergy information. They also enter or upload information that indicates their current emotional state.

[0472] Step 2:

[0473] Terminal: Sends input information and emotion data to the server.

[0474] Step 3:

[0475] Server: Stores the information in a database.

[0476] Step 4:

[0477] Server: Generates a list of appropriate foods and nutrients. If the user is feeling stressed, it recommends foods and activities that are good for stress relief.

[0478] Step 5:

[0479] Device: The generated list and the evaluation results are notified to the user. For example, advice such as "Foods containing omega-3 fatty acids are beneficial for you. You seem to have been feeling stressed lately, so try meditating to relax." is displayed.

[0480] Example 2: Health check reminder

[0481] Step 1:

[0482] Server: Set the user's next health check date to three months from now. If the user has recently reported stress, set an earlier reminder message.

[0483] Step 2:

[0484] Server: Generates a reminder message when the set date and time approaches.

[0485] Step 3:

[0486] Server: Sends reminder messages to the device.

[0487] Step 4:

[0488] Device: A reminder message is sent to the user saying, "It's time for a health check. Check your recent stress level."

[0489] Example 2

[0490] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0491] In modern society, users tend to neglect their health and emotional management in their busy daily lives. As a result, health problems and stress that are often overlooked can accumulate, potentially leading to serious health problems. Furthermore, fluctuations in emotional states often have a direct impact on health, creating a need for health advice that takes this into account. However, existing systems lack the ability to recognize a user's specific emotional state and provide appropriate advice based on that. Therefore, there is a need for a system that can comprehensively manage a user's health and emotional states and provide more personalized health advice.

[0492] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for user authentication, means for collecting user-input information, means for analyzing the collected information, means for generating a list of appropriate foods, nutrients, and supplements based on the analysis results, means for evaluating the safety of processed foods and food additives, means for providing the generated list and evaluation information to the user, means for generating and providing health advice and preventive measures, means for collecting and analyzing emotional data, means for adjusting health advice based on the collected emotional data, and means for reminding users to take regular health checks. This makes it possible to comprehensively manage the user's health and emotional states and provide health advice and regular reminders that are optimized for each individual user.

[0493] "Means for user authentication" is the process by which a user enters their "user name" and "password" and verifies the user's identity by checking them against a database.

[0494] "Means for collecting user-input information" refers to the process by which users provide personal information such as "health status," "dietary habits," and "allergy information" to the system, and this information is received and stored.

[0495] "Means for analyzing collected information" refers to the process by which the system processes collected user data using algorithms and analytical software to find the necessary insights and patterns.

[0496] The "means for generating a list of appropriate foods, nutrients, and supplements" is a process for listing optimal foods, nutrients, and supplements based on the user's health condition.

[0497] "Means for evaluating the safety of processed foods and food additives" refers to a process for evaluating the safety of processed foods and food additives consumed by users and providing the results.

[0498] The "means for providing the generated list and evaluation information to the user" is the process of providing the analyzed data and generated list in a format that is accessible to the user.

[0499] "Means for generating and providing health advice and prevention methods" refers to the process of creating and providing accurate health advice and guidance for disease prevention to the user based on the user's health condition and analysis data.

[0500] "Means for collecting and analyzing emotional data" refers to the process of identifying emotions from the user's video, audio, and text information and analyzing that data.

[0501] "Means for tailoring health advice based on collected emotional data" refers to a process for individually tailoring health advice content depending on the user's emotional state.

[0502] The "means for providing periodic health check reminders" is a process that notifies the user of the need for a health check based on set time intervals or conditions.

[0503] The present invention is a system for efficiently managing a user's health, which takes into account not only the user's health condition but also their emotional state to provide more personalized health advice and reminder functions. Specific embodiments for implementing the present invention will be described below.

[0504] Hardware and Software

[0505] This system is configured using the following hardware and software:

[0506] 1. Server: A high-performance computer or cloud-based computing resource (e.g., Amazon Web Services or Google® Cloud Platform)

[0507] 2. Device: The smartphone, tablet, or PC used by the user

[0508] 3. Database: Relational database management system (e.g., MySQL, PostgreSQL)

[0509] 4. Sentiment analysis engine: Emotion recognition services such as Microsoft® Azure® Cognitive Services

[0510] 5. Analysis software: Python scripts, data analysis libraries such as Pandas and NumPy

[0511] 6. Communication Protocol: Secure data transmission and reception using HTTPS

[0512] User Authentication

[0513] The user enters their "user name" and "password" on the login screen. The device sends this information to the server. The server compares it with the database, and if authentication is successful, generates a session key and returns it to the device. The device displays the authentication result to the user, and if successful, transitions to the dashboard screen.

[0514] Collecting user-entered information

[0515] The user enters information such as "health status," "diet," and "allergy information" on the "Enter Health Information" page within the dashboard. The device sends this information to the server, which then stores it in a database. Once the information has been saved, a notification is returned to the device.

[0516] Information analysis

[0517] The server retrieves user input from the database and runs algorithms to evaluate foods and nutrients. For example, it analyzes the data using Python's Pandas and NumPy. It generates necessary nutrients and a recommended food list, and also evaluates the safety of processed foods and food additives. These results are then stored in a database.

[0518] Providing health advice

[0519] Based on the analysis results, the server uses an emotion engine to generate health advice taking into account the user's emotional data. The generated advice is sent to the device and displayed to the user. For example, if the user is feeling stressed, the server also provides ways to alleviate that stress.

[0520] Regular health check reminders

[0521] The server schedules the user's next health check and generates a reminder message based on the interval, which is then sent to the terminal, which then notifies the user.

[0522] Emotion Engine Operation

[0523] Users input or upload their own video, audio, and text information, which is used for emotion analysis. The device sends the emotion data to the server, where it is analyzed by the server's emotion engine. The analysis results are stored in a database and used to generate health advice.

[0524] Specific examples

[0525] Example 1: Entering and Evaluating New Health Information

[0526] After logging in, users enter their weight, dietary information, and allergy information, and upload information indicating their current emotional state. The device sends this information to a server, which stores it in a database and generates an appropriate food and nutrient list. For example, the device displays advice such as, "Foods containing omega-3 fatty acids are beneficial for you. You seem to have been feeling stressed recently, so try meditating to relax."

[0527] Example 2: Health check reminder

[0528] The server schedules the user's next health check date for three months from now. If the user has recently reported stress, the server sends an earlier reminder message, such as "It's time for a health check. Please also check your recent stress level."

[0529] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0530] Step 1: User Login

[0531] User: The user opens the login screen and enters their "username" and "password."

[0532] Enter: "Username" and "Password"

[0533] Device: The device sends this information to the server via an HTTPS request.

[0534] Output: Credentials sent

[0535] Specific operation: Input form data from the terminal is converted into JSON format and sent to the server using a secure communication protocol.

[0536] Step 2: User authentication

[0537] Server: The server checks the received authentication information against the user data in its database.

[0538] Input: Received authentication information

[0539] Output: Authentication result (success or failure) and session key (if successful)

[0540] Specific operation: The server retrieves user information from the database using an SQL query and verifies the password. If authentication is successful, it generates a session key and returns it to the terminal as an HTTP response.

[0541] Step 3: Viewing the authentication results

[0542] Terminal: The terminal displays the authentication result received from the server to the user. If successful, the terminal transitions to the dashboard screen.

[0543] Input: Authentication result (success or failure) and session key (if successful)

[0544] Output: Dashboard screen or error message

[0545] Specific operation: The terminal analyzes the received authentication result, and if successful, redirects the user to the dashboard screen, and if unsuccessful, displays an error message.

[0546] Step 4: Enter your health information

[0547] User: The user enters information such as "health status," "diet," and "allergy information" on the "Enter Health Information" page in the dashboard.

[0548] Input: Health information such as "health condition," "diet," and "allergy information"

[0549] Terminal: The terminal converts the input information into JSON format and sends it to the server via an HTTPS request.

[0550] Output: Health information sent

[0551] Specific operation: The terminal receives the information entered by the user, converts it to JSON, and sends it to the server via a secure communication protocol.

[0552] Step 5: Save your health information

[0553] Server: The server stores the received health information in a database.

[0554] Input: Received health information

[0555] Output: Save completion notification

[0556] Specific operation: The server uses an SQL query to insert information into the database, checks whether the save is complete, and then returns a save completion message to the terminal.

[0557] Step 6: Information Analysis

[0558] Server: The server takes user input from a database and runs algorithms to evaluate foods and nutrients.

[0559] Input: Health information stored in a database

[0560] Output: Analysis results (list of suitable foods, nutrients, and supplements)

[0561] Specific operation: Using a Python script, data analysis is performed using Pandas and NumPy. As a result of the analysis, a list of foods, nutrients, and supplements suitable for the user is generated.

[0562] Step 7: Generate health advice

[0563] Server: The server generates health advice based on the analysis results and emotion data.

[0564] Input: Analysis results, emotion data

[0565] Output: Health advice

[0566] Specific operation: The emotion engine is used to analyze emotion data, adjust the analysis results based on the results, and generate appropriate health advice.

[0567] Step 8: Providing health advice

[0568] Terminal: The terminal displays the health advice received from the server to the user.

[0569] Enter: Health Advice

[0570] Output: User advice screen

[0571] Specific operation: The received health advice is displayed on the user's dashboard screen and notifications are provided as needed.

[0572] Step 9: Remind yourself to check your health regularly

[0573] Server: The server schedules the user's next health check and generates reminder messages based on the set interval.

[0574] Input: User's health information, interval settings

[0575] Output: Reminder message

[0576] Specific operation: Using a Cron job or similar, a reminder message is generated and sent to the device at the set time.

[0577] Step 10: Sending Reminder Messages

[0578] Device: The device will notify the user of reminder messages and encourage them to check their health.

[0579] Input: Reminder message

[0580] Output: Reminder notification

[0581] Specific operation: The device receives the reminder message and notifies the user via push notification or in-app notification.

[0582] These steps enable the system to optimize the user's health management and provide personalized advice that takes into account their emotional state.

[0583] (Application example 2)

[0584] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0585] Conventional health management systems provide health advice based on user-entered information, but they do not consider real-time recommendations based on purchasing behavior in physical stores. There is a need for a system that utilizes health information, including the user's emotional state, to provide appropriate food and nutrient recommendations in physical stores. It is also necessary to efficiently remind users to schedule their next health check.

[0586] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0587] In this invention, the server includes means for user authentication, means for collecting user-input information, means for analyzing the collected information, means for generating a list of appropriate foods, nutrients, and supplements based on the analysis results, means for evaluating the safety of processed foods and food additives, means for providing the generated list and evaluation information to the user, means for generating and providing health advice and preventive methods, means for reminding the user to take regular health checks, means for providing recommendations to the user using smart glasses in a physical store, and means for scheduling and reminding the user of the user's next health check. This allows the user to receive appropriate health recommendations in real time while making a purchase in the physical store, and also enables efficient reminders for the next health check.

[0588] "User authentication" is the process of verifying a user's identity using a username and password when accessing a system.

[0589] "Collecting user-input information" is the stage where the user inputs information such as health status, dietary habits, and allergies into the system.

[0590] "Information analysis" is the process of using algorithms to evaluate collected user-entered information and generate a list of appropriate foods and nutrients.

[0591] "List generation" is the stage where a list of foods, nutrients, and supplements suitable for the user is created based on the analysis results.

[0592] "Safety assessment" is an analytical process conducted to evaluate the safety of processed foods and food additives.

[0593] "Providing advice" is the process of providing health advice and preventive methods to the user based on the generated list and evaluation information.

[0594] "Remind" is the process of scheduling a user's next health check date and sending a timely reminder message.

[0595] "Recommendations in physical stores" refers to the use of smart glasses to recommend appropriate products and health information in real time to users in physical stores based on their purchasing behavior.

[0596] "Health check schedule setting" is a process of setting the date of the user's next health check and sending reminders based on that schedule.

[0597] The present invention provides a system for efficiently managing a user's health, and in particular provides real-time recommendations and health check reminders in physical stores. The specific operation of the system is described below.

[0598] First, let's explain user authentication. The user accesses the login screen and enters their "user name" and "password." The terminal sends the "user name" and "password" entered by the user to the server. The server compares the received authentication information with a database and performs user authentication. If authentication is successful, it generates a session key and returns it to the terminal. The terminal displays the authentication result to the user, and if successful, transitions to the dashboard screen.

[0599] Next, we will explain how to collect user-entered information. The user enters information such as "health status," "diet," and "allergy information" on the "Enter Health Information" page in the dashboard. The device sends the entered information to the server. The server stores the received information in a database. A notification that the information has been saved is returned to the device.

[0600] In the information analysis step, the server retrieves user input information from the database and runs algorithms to evaluate foods and nutrients. It generates a list of appropriate foods, nutrients, and supplements, and performs safety evaluations of processed foods and food additives. The analysis results and safety evaluation results are stored in the database.

[0601] When providing health advice, the server generates health advice based on the analysis results and safety assessment results. This advice also takes into account the emotion recognition results of the emotion engine. The device displays the health advice to the user. For example, if the user is feeling stressed, it also provides ways to alleviate that stress.

[0602] It also includes a function to schedule the user's next health check and generate a reminder message. The server sends the reminder message to the device based on the interval. The device notifies the user of the reminder message and encourages them to check their health.

[0603] We also explain real-time recommendations in physical stores. When a user walks around a store wearing smart glasses, the device requests recommendations from the server based on the user's location and emotional state. The server analyzes the received information and recommends appropriate products and activities. For example, if the user is feeling stressed, recommendations such as "green tea" and "dark chocolate" will be displayed.

[0604] The implementation of this system uses the following hardware and software:

[0605] Hardware: Smart glasses (e.g., smart glasses), cloud server (e.g., cloud server), terminal (e.g., PC or smartphone)

[0606] Software: Databases (e.g., MySQL, PostgreSQL, MongoDB), data analysis algorithms, emotion engines

[0607] As a concrete example, a user wearing smart glasses receives recommendations such as "green tea" or "dark chocolate" when selecting products in a physical store. At the same time, a reminder message is displayed saying, "Don't forget your next health check," since the user's next health check is approaching.

[0608] An example of a prompt to be input to the generative AI model is, "Write a Python program that analyzes the user's emotional state and recommends healthy foods and activities based on that. Also, include a function to remind them to come for their next health check."

[0609] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0610] Step 1: User authentication

[0611] Input: Username, Password

[0612] Specific operation: The user accesses the login screen and enters their username and password. The device sends the input information to the server.

[0613] Data processing: The server checks the received username and password against its database.

[0614] Output: If authentication is successful, the server generates a session key and returns it to the terminal. The terminal displays the authentication result to the user, and if successful, transitions to the dashboard screen.

[0615] Step 2: Collecting User-Input Information

[0616] Input: Health condition, dietary habits, allergy information

[0617] Specific operation: The user enters information on the "Enter Health Information" page in the dashboard. The device sends the entered information to the server.

[0618] Data processing: The server stores the received information in a database.

[0619] Output: The server returns a notification to the device that the save is complete.

[0620] Step 3: Information analysis

[0621] Input: User-entered information (health status, dietary habits, allergy information)

[0622] Specific operation: The server retrieves user input information from the database and runs algorithms to evaluate foods and nutrients.

[0623] Data calculation: The server runs the evaluation algorithm and generates a list of suitable foods, nutrients, and supplements.

[0624] Output: The analysis results and generated list are obtained. In addition, the safety assessment of processed foods and food additives is performed and the results are also obtained.

[0625] Step 4: Providing health advice

[0626] Input: Analysis results, generated list, safety assessment results, emotion recognition results by emotion engine

[0627] Specific operation: The server generates health advice based on the analysis results and safety assessment results, taking into account emotion recognition results.

[0628] Data calculation: Comprehensively evaluate the emotion recognition results obtained from the emotion engine and generate optimal health advice.

[0629] Output: The terminal displays the generated health advice to the user.

[0630] Step 5: Remind yourself to check your health regularly

[0631] Input: The user's next scheduled health check

[0632] Specific operation: The server generates reminder messages based on the set interval.

[0633] Data processing: Reminder messages are generated based on each user's health check interval.

[0634] Output: The server sends a remind message to the terminal, which notifies the user of the message.

[0635] Step 6: Real-time recommendations in-store

[0636] Input: User's location, emotional state

[0637] Specific operation: When a user walks around a store using smart glasses, the device requests the user's location information and emotional state from the server.

[0638] Data calculation: The server analyzes the received location information and emotional state and recommends appropriate products and activities.

[0639] Output: The device displays the recommendation results in real time on the user's smart glasses.

[0640] Step 7: Schedule your health checks

[0641] Input: User's health check schedule information

[0642] Specific operation: The server schedules the user's next health check.

[0643] Data processing: Schedule the next health check date and time based on the user's health data.

[0644] Output: The device sends a reminder message to the user based on the configured schedule information.

[0645] The above are the specific steps of the program processing.

[0646] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0647] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0648] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0649] [Second embodiment]

[0650] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0651] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0652] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0653] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0654] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0655] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0656] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0657] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0658] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0659] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0660] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0661] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0662] The present invention is a system for enabling users to efficiently manage their health, analyzing information input by the user and providing appropriate health advice. A specific operation method of the system will be described below.

[0663] User Authentication

[0664] User:

[0665] The user accesses the login screen and enters their "user name" and "password."

[0666] Device:

[0667] The terminal sends the "user name" and "password" entered by the user to the server.

[0668] server:

[0669] The server checks the received authentication information against a database, and if authentication is successful, generates a session key and returns the generated session key to the terminal.

[0670] Device:

[0671] The terminal notifies the user that the authentication was successful and displays the dashboard screen.

[0672] Collecting user-entered information

[0673] User:

[0674] Users go to the "Enter Health Information" page in the dashboard and enter information such as "health status," "diet," and "allergy information."

[0675] Device:

[0676] The terminal transmits the information entered by the user to the server.

[0677] server:

[0678] The server saves the received information in a database and returns a notification to the device that saving is complete.

[0679] Information analysis

[0680] server:

[0681] The server runs algorithms that generate lists of suitable foods, nutrients, and supplements based on user-entered information in the database, and also performs safety assessments of processed foods and food additives.

[0682] Providing health advice

[0683] server:

[0684] The server documents specific health advice and preventive measures based on the generated list and safety assessment results.

[0685] Device:

[0686] The terminal displays the health advice and prevention methods received from the server to the user.

[0687] Regular health check reminders

[0688] server:

[0689] The server registers the next health check date in the schedule based on the user's check interval and generates a reminder message.

[0690] Device:

[0691] The device notifies the user of reminder messages and encourages regular health checks.

[0692] Specific examples

[0693] As a concrete example, the following scenario will be described.

[0694] Example 1: Entering and Evaluating New Health Information

[0695] User:

[0696] After logging in, the user enters their "weight," "dietary details," and "allergy information."

[0697] Device:

[0698] The input information is sent to the server.

[0699] server:

[0700] The information is stored in a database, appropriate food and nutrient lists are generated, and processed food safety is assessed.

[0701] server:

[0702] Based on the generated list and the evaluation results, health advice is created and sent to the device.

[0703] Device:

[0704] Health advice such as "Foods containing omega-3 fatty acids are beneficial for you" is displayed.

[0705] Example 2: Health check reminder

[0706] server:

[0707] Set the user's next health check date to three months later.

[0708] server:

[0709] When the set date and time approaches, a reminder message will be sent to your device.

[0710] Device:

[0711] A reminder message is sent to the user saying, "It's time for a health check."

[0712] The system of the present invention allows users to easily and efficiently manage their own health, make appropriate food choices, and take preventative measures, thereby contributing to the prevention of health hazards.

[0713] The processing flow will be explained below.

[0714] Program processing steps

[0715] User Authentication

[0716] Step 1:

[0717] User: Enter your "username" and "password" on the login screen.

[0718] Step 2:

[0719] Terminal: Sends the entered authentication information to the server.

[0720] Step 3:

[0721] Server: Compares the received authentication information with a database and performs user authentication.

[0722] Step 4:

[0723] Server: If authentication is successful, generates a session key and returns it to the terminal.

[0724] Step 5:

[0725] Terminal: The authentication result is displayed to the user, and if successful, the user is taken to the dashboard screen.

[0726] Collecting user-entered information

[0727] Step 1:

[0728] User: Enter information such as "health condition," "diet," and "allergy information" on the "Enter Health Information" page in the dashboard.

[0729] Step 2:

[0730] Terminal: Sends the entered information to the server.

[0731] Step 3:

[0732] Server: Stores the received information in a database.

[0733] Step 4:

[0734] Server: Sends confirmation of save completion to the device.

[0735] Information analysis

[0736] Step 1:

[0737] Server: Retrieves user input information from the database.

[0738] Step 2:

[0739] Server: Runs the algorithms that evaluate foods and nutrients.

[0740] Step 3:

[0741] Server: Generates a list of suitable foods, nutrients, and supplements.

[0742] Step 4:

[0743] Server: Evaluates the safety of processed foods and food additives.

[0744] Step 5:

[0745] Server: Stores the analysis results and safety evaluation results in a database.

[0746] Providing health advice

[0747] Step 1:

[0748] Server: Generates health advice based on the analysis results and safety assessment results.

[0749] Step 2:

[0750] Server: Sends health advice to the device.

[0751] Step 3:

[0752] Terminal: displays health advice to the user.

[0753] Regular health check reminders

[0754] Step 1:

[0755] Server: Schedules the user's next health check.

[0756] Step 2:

[0757] Server: Generates reminder messages based on configured intervals.

[0758] Step 3:

[0759] Server: Sends reminder messages to the device.

[0760] Step 4:

[0761] Terminal: Notify the user of the reminder message.

[0762] Example 1

[0763] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0764] Conventional health management systems struggle to efficiently provide appropriate health advice that takes into account a user's health status, diet, and allergy information. They also lacked reminders for regular health checks, and did not provide sufficient support for users to continuously manage their health. Furthermore, some systems lacked session management and generative AI models, resulting in a poor user experience.

[0765] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0766] In this invention, the server includes means for user authentication, means for collecting user-input information, means for analyzing the collected information, means for generating a list of appropriate foods, nutrients, and supplements based on the analysis results, means for evaluating the safety of processed foods and food additives, means for providing the generated list and evaluation information to the user, means for generating and providing health advice and preventive methods, means for reminding users to take regular health checks, means for generating and managing session keys, and means for creating health advice and reminder messages using a generative AI model, thereby enabling users to efficiently and continuously manage their own health.

[0767] "User authentication" is the process of verifying a user's identity when they access a system.

[0768] "User input information" refers to data such as health status, dietary habits, and allergy information that the user provides to the system.

[0769] "Means of analyzing information" refers to the method of analyzing and evaluating related data based on collected user-entered information.

[0770] The "means for generating a list of foods, nutrients, and supplements" is a method for selecting and listing foods, nutrients, and supplements suitable for the user based on the analysis results.

[0771] "Means for safety assessment" refers to the methods used to evaluate the safety of processed foods and food additives and reflect the results in the list.

[0772] The "means for providing to the user" refers to a method for conveying the generated list and rating information to the user.

[0773] The "means for generating and providing health advice and preventive measures" is a method for generating and providing specific health advice and preventive measures to the user based on the analysis results.

[0774] The "means for reminding users to check their health" is a method for generating and notifying reminder messages to encourage users to check their health regularly.

[0775] The "means for generating and managing a session key" is a method for generating and managing a session key for identifying a user during a session after user authentication has been successful.

[0776] A "generative AI model" is an artificial intelligence model used for natural language generation and data analysis, and an example is the GPT series.

[0777] The present invention is a system for enabling users to efficiently manage their health by analyzing input information from the user and providing appropriate health advice. Specific implementation and operation methods of the system are described below.

[0778] System configuration

[0779] The present invention consists of a user terminal, a server, and a database. The user terminal can be a PC, smartphone, tablet, etc. The server is a high-performance computer equipped with a database management system (e.g., MySQL) and analytical software (e.g., Python scripts). In addition, a generative AI model (e.g., GPT-4) is used for natural language generation and data analysis.

[0780] User Authentication

[0781] The user accesses the login screen using a terminal and enters their "user name" and "password." This authentication information is sent from the terminal to the server via a secure protocol (HTTPS). The server compares the received information with data in a database, and if authentication is successful, it generates a session key and returns it to the terminal. The terminal notifies the user that authentication was successful and displays the dashboard screen.

[0782] Collecting user-entered information

[0783] The user goes to the "Enter Health Information" page in the dashboard and enters information such as "health status," "diet," and "allergy information." This information is sent from the device to the server in JSON format. The server stores the received information in a database and notifies the device once it has been saved.

[0784] Information analysis

[0785] The server retrieves user information from the database and analyzes it using Python scripts. Based on the analysis results, it generates a list of appropriate foods, nutrients, and supplements. It also evaluates the safety of processed foods and food additives and lists the results.

[0786] Providing health advice

[0787] The server then documents specific health advice and preventative measures based on the generated list and safety assessment results. This process uses a generative AI model (GPT-4). The generated advice is sent to the device and displayed to the user. For example, advice such as "Foods containing omega-3 fatty acids are beneficial for you" is provided.

[0788] Regular health check reminders

[0789] The server schedules the next health check based on the user's check interval. When the scheduled date and time approaches, it uses a generative AI model to create a reminder message and sends it to the device. The device then notifies the user of this reminder message, encouraging them to perform regular health checks. For example, a message saying, "It's time for a health check."

[0790] Specific examples

[0791] Here is a specific example.

[0792] Example 1: After logging in, a user enters their weight, dietary details, and allergy information, and the device sends the information to the server. The server stores the information in a database, generates a list of appropriate foods and nutrients, and provides health advice.

[0793] Example 2: The server sets the user's next health check date three months from now, and when the set date and time approaches, it generates a reminder message and sends it to the device.

[0794] In this way, users can efficiently and continuously manage their own health.

[0795] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0796] Step 1:

[0797] User: The user accesses the login screen and enters their "username" and "password."

[0798] Enter: "Username" and "Password"

[0799] Output: Sends authentication information to the terminal

[0800] Specific behavior: The user completes the login screen and clicks the "Login" button.

[0801] Step 2:

[0802] Terminal: The terminal encrypts the "username" and "password" entered by the user and sends them to the server via a secure protocol (e.g., HTTPS).

[0803] Input: Encrypted "Username" and "Password"

[0804] Output: Sends authentication information to the server

[0805] Specific operation: The device protects the information entered using SSL / TLS encryption and sends it to the server as an HTTPS request.

[0806] Step 3:

[0807] Server: The server checks the received credentials against a database (e.g. MySQL) using a hashed password.

[0808] Input: Received authentication information

[0809] Output: Authentication result (success or failure)

[0810] Specific operation: The server compares the hash value of the received information with the user information stored in the database.

[0811] Step 4:

[0812] Server: If authentication is successful, the server generates a random session key and returns it to the device.

[0813] Input: Authentication success flag

[0814] Output: Session key

[0815] Specific operation: The server generates a session ID, temporarily stores it in a database, and sends it back to the device.

[0816] Step 5:

[0817] Terminal: The terminal notifies the user that authentication was successful and displays the dashboard screen.

[0818] Input: Session key

[0819] Output: Dashboard screen display

[0820] Specific behavior: The device saves the received session key and displays the dashboard to the user along with a successful login message.

[0821] Step 6:

[0822] User: The user goes to the "Enter Health Information" page in the dashboard and enters information such as "health status," "diet," and "allergy information."

[0823] Input: "Health status", "Diet", "Allergy information"

[0824] Output: Sends information to the terminal

[0825] What happens: A user fills in a form and clicks the "Submit" button.

[0826] Step 7:

[0827] Terminal: The terminal sends the information entered by the user to the server, using JSON format data.

[0828] Input: User input information (JSON format)

[0829] Output: Sends input information to the server

[0830] Specific operation: The device converts the input information into JSON format and sends it to the server via an HTTPS request.

[0831] Step 8:

[0832] Server: The server stores the received information in a database.

[0833] Input: User input information (JSON format)

[0834] Output: Save result (success or failure)

[0835] Specific operation: The server writes the received information to the database.

[0836] Step 9:

[0837] Server: The server returns a notification to the device that the save is complete.

[0838] Input: Save success flag

[0839] Output: Save completion notification

[0840] Specific behavior: The server confirms the success of the save and returns a notification to the device as an HTTPS response.

[0841] Step 10:

[0842] Server: The server retrieves the user information from the database and runs the analysis algorithm.

[0843] Input: User information

[0844] Output: Analysis results (food list, safety assessment)

[0845] What it does: The server runs a Python script to evaluate the list of suitable foods and nutrients and the safety of processed foods.

[0846] Step 11:

[0847] Server: The server uses generative AI models to document health advice and prevention methods.

[0848] Input: Analysis results

[0849] Output: Health advice and prevention methods (text)

[0850] Specific operation: The server runs a generative AI model (e.g., GPT-4) and generates advice in natural language based on the analysis results.

[0851] Step 12:

[0852] Server: The server sends the generated advice and prevention methods to the device.

[0853] Input: Health advice and prevention methods (text)

[0854] Output: Send advice to terminal

[0855] Specific operation: The server returns the generated text to the terminal as an HTTPS response.

[0856] Step 13:

[0857] Terminal: The terminal displays the health advice and prevention methods received from the server to the user.

[0858] Input: Advice received from the server

[0859] Output: Display advice to the user

[0860] Specific operation: The terminal displays the received information on the user screen in an appropriate format.

[0861] Step 14:

[0862] Server: The server schedules the next health check date based on the user's check interval.

[0863] Input: User check interval

[0864] Output: Next health check date

[0865] Specific operation: The server registers the next health check date in the schedule management system.

[0866] Step 15:

[0867] Server: When the set date and time approaches, the server uses a generative AI model to generate a reminder message.

[0868] Input: Next health check date

[0869] Output: Reminder message (text)

[0870] Specific operation: The server uses the generative AI model to generate appropriate reminder text.

[0871] Step 16:

[0872] Server: The server sends the generated remind message to the device.

[0873] Input: Reminder message (text)

[0874] Output: Send a reminder message to the device

[0875] Specific operation: The server sends the generated message to the terminal as an HTTPS response.

[0876] Step 17:

[0877] Device: The device will notify the user as a reminder message that it is time for a health check.

[0878] Input: Reminder message received from the server

[0879] Output: Notify the user

[0880] What happens: The device displays a reminder message to the user and notifies the user using the notification system.

[0881] (Application example 1)

[0882] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0883] Conventional health management systems make it difficult for users to select appropriate foods and nutrients based on their own health information. They also lacked a means to effectively recommend related products and services, making it difficult for users to make optimal purchasing decisions based on their health status. Furthermore, they lacked a mechanism to provide health advice while also encouraging actual purchasing behavior.

[0884] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0885] In this invention, the server includes means for user authentication, means for collecting user-entered information, means for analyzing the collected information, means for recommending appropriate products and services based on the analysis results, means for evaluating the safety of processed products and ingredients, means for providing the generated list and evaluation information to the user, means for generating and providing health advice and preventive methods, means for reminding the user to take regular health checks, and means for displaying links to online shopping sites to facilitate purchases. This allows users to easily select optimal products and services based on their own health condition and efficiently manage their health.

[0886] "User authentication" is the process by which a user accesses a system using their authentication information (e.g., username and password).

[0887] "User-input information" refers to data such as health status, dietary habits, and allergy information that a user provides to the system.

[0888] "Information analysis" is data processing to recommend appropriate products and foods based on collected user-entered information.

[0889] "Product recommendation" is the process of presenting optimal products and services to users based on the results of information analysis.

[0890] "Ingredient safety evaluation" is a procedure for evaluating the safety of processed products and ingredients and providing that information to users.

[0891] "Providing a list" is a procedure for transmitting the generated list of products and services and evaluation information to users.

[0892] "Health advice" is a procedure that provides specific health management methods and preventative measures based on the user's health information.

[0893] "Remind" is a procedure that notifies the user when it is time for a regular health check and encourages them to carry out the check.

[0894] "Mail Order Link" is a procedure for generating and displaying a link that allows users to purchase recommended products or services.

[0895] This specification details a specific embodiment of a system for efficiently managing a user's health. The system collects and analyzes health information provided by the user, recommends appropriate products and nutrients, and provides links to online shopping sites to encourage users to make purchases.

[0896] System Overview

[0897] The system includes the following elements:

[0898] A means of user authentication

[0899] A means of collecting user input information

[0900] How we analyze the information we collect

[0901] A means of recommending appropriate products and services based on analysis results

[0902] A means of assessing the safety of processed products and ingredients

[0903] Means for providing generated list and rating information to a user

[0904] A means of generating and delivering health advice and prevention methods

[0905] A means of reminding people to check their health regularly

[0906] Displaying links to online shopping sites to make purchasing easier

[0907] Hardware and Software Configuration

[0908] Hardware

[0909] Smartphone: a device on which the user operates an interface

[0910] Server: Backend server that stores and processes data

[0911] software

[0912] Flask: A lightweight web framework built in Python

[0913] sqlite3: a local database management system

[0914] React: Used to build the front-end user interface

[0915] Data processing and calculation

[0916] User Authentication

[0917] The user enters their authentication information (username and password) and sends it to the server, which checks it against the database and, if authentication is successful, generates and returns a session key.

[0918] Collecting user-entered information

[0919] The user enters information about their health, diet, allergies, etc., and the device sends this information to the server, which then stores the received information in a database.

[0920] Information analysis

[0921] The server analyzes the user-entered information in the database and performs data calculations to recommend appropriate products, nutrients, and supplements. Using a generative AI model, it analyzes the data based on the prompt text and generates results.

[0922] Providing health advice

[0923] The server generates specific health advice and preventive measures based on the user's health information and sends them to the device, which then displays them to the user.

[0924] Reminders and shopping links

[0925] The server sets the date for the user's next health check and generates a reminder message. The device notifies the user of this and encourages regular health checks. The device also displays a link to purchase recommended products, allowing the user to easily access the online shopping site.

[0926] Specific examples

[0927] Example 1: Entering and Evaluating New Health Information

[0928] After logging in, users enter their health information (weight, dietary habits, and allergy information). The device sends the information to the server, which stores it in a database. The server uses a generative AI model to generate a list of appropriate foods and nutrients and evaluates the safety of processed foods. Based on the results, health advice and product recommendations are provided and notified to the user.

[0929] Example prompt sentence:

[0930] Recommend optimal foods and nutrients based on your health, diet, and allergies. Use the following information:

[0931] Health: Weight gain in the past week

[0932] Diet: Few vegetables in daily meals

[0933] Allergy Information: Nut allergy

[0934] Example 2: Displaying online shopping links and encouraging purchases

[0935] The server creates a list of recommended products based on the analysis results and generates a link to the online shopping site. The device displays this to the user, who can click on the product link to access the online shopping site and make a purchase.

[0936] As described above, the system of the present invention allows users to easily select optimal products and services based on their own health condition, and efficiently manage their health.

[0937] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0938] Step 1:

[0939] When a user opens the app, a login screen appears. The user enters their authentication information (username and password). The entered information is sent from the device to the server.

[0940] Input: Username, Password

[0941] Output: Sending authentication information to the server

[0942] Step 2:

[0943] The server checks the received authentication information against a database, and if authentication is successful, generates a session key and returns the generated session key to the terminal.

[0944] Input: Credentials

[0945] Output: Session key, authentication result

[0946] Step 3:

[0947] The device notifies the user that authentication was successful and displays the dashboard screen. The user then moves to the "Enter Health Information" page to enter data such as health status, dietary habits, and allergy information.

[0948] Input: Session key, user information

[0949] Output: View dashboard

[0950] Step 4:

[0951] After entering health information, the user sends the information from the device to the server, which stores the information in a database and returns a notification to the device that the information has been saved.

[0952] Input: Health information (e.g., health condition, diet, allergy information)

[0953] Output: Saving to database, notification of saving completion

[0954] Step 5:

[0955] The server analyzes the user-entered information stored in the database and uses a generative AI model to generate a list of appropriate foods and nutrients based on the prompt.

[0956] Input: User's health information

[0957] Output: List of foods and nutrients

[0958] Step 6:

[0959] The server uses the generated list and other data to evaluate the safety of processed products and ingredients, and then compiles the evaluation results into written advice for the user.

[0960] Input: list of foods and nutrients, generative AI model

[0961] Output: Safety assessment, health advice

[0962] Step 7:

[0963] The server sends the generated advice to the terminal, which displays it to the user. The terminal then displays further recommended information on suitable products and services, as well as links to online shopping sites where the products can be purchased.

[0964] Input: Health advice, assessment results

[0965] Output: Display advice, display mail order link

[0966] Step 8:

[0967] When a user clicks on a shopping link, a browser is launched and the specified shopping site is opened, allowing the user to easily purchase the product.

[0968] Input: Click on the online shopping link

[0969] Output: Display of online shopping site, facilitating product purchase

[0970] Step 9:

[0971] The server sets the date of the user's next health check and generates a reminder message. When the set date and time approaches, the reminder message is sent to the device. The device then notifies the user of the reminder message.

[0972] Input: User health check interval

[0973] Output: Generate reminder message, notification

[0974] Through the above processing steps, the system of the present invention enables users to efficiently manage their health and conveniently purchase related products and services.

[0975] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0976] The present invention is a system for efficiently managing a user's health, and in particular, recognizes the user's emotions and provides health advice and reminders based on those emotions. The specific operation of the system is described below.

[0977] User Authentication

[0978] User:

[0979] The user accesses the login screen and enters their "user name" and "password."

[0980] Device:

[0981] The terminal sends the "user name" and "password" entered by the user to the server.

[0982] server:

[0983] The server compares the received authentication information with a database to authenticate the user. If authentication is successful, it generates a session key and returns it to the terminal.

[0984] Device:

[0985] The terminal displays the authentication result to the user, and if successful, transitions to the dashboard screen.

[0986] Collecting user-entered information

[0987] User:

[0988] Users enter information such as their health status, diet, and allergy information on the "Enter Health Information" page within the dashboard.

[0989] Device:

[0990] The entered information is sent to the server.

[0991] server:

[0992] The received information is saved in the database, and a notification that saving is complete is returned to the device.

[0993] Information analysis

[0994] server:

[0995] It takes user input from the database and runs algorithms to evaluate foods and nutrients, generates lists of suitable foods, nutrients, and supplements, and evaluates the safety of processed foods and food additives.

[0996] server:

[0997] The analysis results and safety evaluation results are stored in a database.

[0998] Providing health advice

[0999] server:

[1000] Health advice is generated based on the analysis results and safety assessment results, taking into account emotion recognition results from the emotion engine.

[1001] Device:

[1002] Health advice is displayed to the user. For example, if the user is feeling stressed, it also provides ways to alleviate the stress.

[1003] Regular health check reminders

[1004] server:

[1005] Schedule the user's next health check. Generate reminder messages based on the interval you set.

[1006] server:

[1007] Send a reminder message to your device.

[1008] Device:

[1009] Reminder messages are sent to users to encourage them to check their health.

[1010] Emotion Engine Operation

[1011] User:

[1012] Emotions are analyzed from video, audio, and text information entered or uploaded by the user.

[1013] Device:

[1014] The emotion data is sent to the server.

[1015] server:

[1016] The emotion engine analyzes the transmitted data and recognizes the user's emotions. The recognition results are stored in a database and used to generate health advice.

[1017] Specific examples

[1018] Example 1: Entering and Evaluating New Health Information

[1019] User:

[1020] After logging in, users enter their weight, dietary information, and allergy information. They also enter or upload information that indicates their current emotional state.

[1021] Device:

[1022] The input information and emotion data are sent to the server.

[1023] server:

[1024] The information is stored in a database and a list of appropriate foods and nutrients is generated. If the user is feeling stressed, it will recommend foods and activities that will help relieve stress.

[1025] Device:

[1026] The advice displayed is, "Foods containing omega-3 fatty acids are beneficial for you. You seem to have been feeling stressed lately, so try meditating to help you relax."

[1027] Example 2: Health check reminder

[1028] server:

[1029] Set the user's next health check date three months from now. If the user has recently reported stress, set an earlier reminder message.

[1030] server:

[1031] When the set date and time approaches, a reminder message will be sent to your device.

[1032] Device:

[1033] It notifies you, "It's time for a health check. Let's also check your recent stress level."

[1034] The system of the present invention supports users in optimal health management based on their own health and emotional state. By combining it with an emotion engine, it becomes possible to provide more personalized health advice, which is of great help to users in improving their health and preventing disease.

[1035] The processing flow will be explained below.

[1036] Program processing steps

[1037] User Authentication

[1038] Step 1:

[1039] User: Enter your "username" and "password" on the login screen.

[1040] Step 2:

[1041] Terminal: Sends the entered authentication information to the server.

[1042] Step 3:

[1043] Server: Compares the received authentication information with a database and performs user authentication.

[1044] Step 4:

[1045] Server: If authentication is successful, generates a session key and returns it to the terminal.

[1046] Step 5:

[1047] Terminal: The authentication result is displayed to the user, and if successful, the user is taken to the dashboard screen.

[1048] Collecting user-entered information

[1049] Step 1:

[1050] User: Enter information such as "health condition," "diet," and "allergy information" on the "Enter Health Information" page in the dashboard.

[1051] Step 2:

[1052] Terminal: Sends the entered information to the server.

[1053] Step 3:

[1054] Server: Stores the received information in a database.

[1055] Step 4:

[1056] Server: Sends confirmation of save completion to the device.

[1057] Information analysis

[1058] Step 1:

[1059] Server: Retrieves user input information from the database.

[1060] Step 2:

[1061] Server: Runs the algorithms that evaluate foods and nutrients.

[1062] Step 3:

[1063] Server: Generates a list of suitable foods, nutrients, and supplements.

[1064] Step 4:

[1065] Server: Evaluates the safety of processed foods and food additives.

[1066] Step 5:

[1067] Server: Stores the analysis results and safety evaluation results in a database.

[1068] Providing health advice

[1069] Step 1:

[1070] Server: Generates health advice based on the analysis results and safety assessment results, taking into account emotion recognition results from the emotion engine.

[1071] Step 2:

[1072] Server: Sends health advice to the device.

[1073] Step 3:

[1074] Terminal: displays health advice to the user.

[1075] Regular health check reminders

[1076] Step 1:

[1077] Server: Schedules the user's next health check.

[1078] Step 2:

[1079] Server: Generates reminder messages based on configured intervals.

[1080] Step 3:

[1081] Server: Sends reminder messages to the device.

[1082] Step 4:

[1083] Terminal: Notify the user of the reminder message.

[1084] Emotion Engine Operation

[1085] Step 1:

[1086] User: Analyze emotions from video, audio, and text information you input or upload.

[1087] Step 2:

[1088] Terminal: Sends emotion data to the server.

[1089] Step 3:

[1090] Server: The emotion engine analyzes the transmitted data and recognizes the user's emotion.

[1091] Step 4:

[1092] Server: Stores emotion recognition results in a database and uses them to generate health advice.

[1093] Specific examples

[1094] Example 1: Entering and Evaluating New Health Information

[1095] Step 1:

[1096] User: After logging in, the user enters their weight, dietary information, and allergy information. They also enter or upload information that indicates their current emotional state.

[1097] Step 2:

[1098] Terminal: Sends input information and emotion data to the server.

[1099] Step 3:

[1100] Server: Stores the information in a database.

[1101] Step 4:

[1102] Server: Generates a list of appropriate foods and nutrients. If the user is feeling stressed, it recommends foods and activities that are good for stress relief.

[1103] Step 5:

[1104] Device: The generated list and the evaluation results are notified to the user. For example, advice such as "Foods containing omega-3 fatty acids are beneficial for you. You seem to have been feeling stressed lately, so try meditating to relax." is displayed.

[1105] Example 2: Health check reminder

[1106] Step 1:

[1107] Server: Set the user's next health check date to three months from now. If the user has recently reported stress, set an earlier reminder message.

[1108] Step 2:

[1109] Server: Generates a reminder message when the set date and time approaches.

[1110] Step 3:

[1111] Server: Sends reminder messages to the device.

[1112] Step 4:

[1113] Device: A reminder message is sent to the user saying, "It's time for a health check. Check your recent stress level."

[1114] Example 2

[1115] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1116] In modern society, users tend to neglect their health and emotional management in their busy daily lives. As a result, health problems and stress that are often overlooked can accumulate, potentially leading to serious health problems. Furthermore, fluctuations in emotional states often have a direct impact on health, creating a need for health advice that takes this into account. However, existing systems lack the ability to recognize a user's specific emotional state and provide appropriate advice based on that. Therefore, there is a need for a system that can comprehensively manage a user's health and emotional states and provide more personalized health advice.

[1117] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for user authentication, means for collecting user-input information, means for analyzing the collected information, means for generating a list of appropriate foods, nutrients, and supplements based on the analysis results, means for evaluating the safety of processed foods and food additives, means for providing the generated list and evaluation information to the user, means for generating and providing health advice and preventive measures, means for collecting and analyzing emotional data, means for adjusting health advice based on the collected emotional data, and means for reminding users to take regular health checks. This makes it possible to comprehensively manage the user's health and emotional states and provide health advice and regular reminders that are optimized for each individual user.

[1118] "Means for user authentication" is the process by which a user enters their "user name" and "password" and verifies the user's identity by checking them against a database.

[1119] "Means for collecting user-input information" refers to the process by which users provide personal information such as "health status," "dietary habits," and "allergy information" to the system, and this information is received and stored.

[1120] "Means for analyzing collected information" refers to the process by which the system processes collected user data using algorithms and analytical software to find the necessary insights and patterns.

[1121] The "means for generating a list of appropriate foods, nutrients, and supplements" is a process for listing optimal foods, nutrients, and supplements based on the user's health condition.

[1122] "Means for evaluating the safety of processed foods and food additives" refers to a process for evaluating the safety of processed foods and food additives consumed by users and providing the results.

[1123] The "means for providing the generated list and evaluation information to the user" is the process of providing the analyzed data and generated list in a format that is accessible to the user.

[1124] "Means for generating and providing health advice and prevention methods" refers to the process of creating and providing accurate health advice and guidance for disease prevention to the user based on the user's health condition and analysis data.

[1125] "Means for collecting and analyzing emotional data" refers to the process of identifying emotions from the user's video, audio, and text information and analyzing that data.

[1126] "Means for tailoring health advice based on collected emotional data" refers to a process for individually tailoring health advice content depending on the user's emotional state.

[1127] The "means for providing periodic health check reminders" is a process that notifies the user of the need for a health check based on set time intervals or conditions.

[1128] The present invention is a system for efficiently managing a user's health, which takes into account not only the user's health condition but also their emotional state to provide more personalized health advice and reminder functions. Specific embodiments for implementing the present invention will be described below.

[1129] Hardware and Software

[1130] This system is configured using the following hardware and software:

[1131] 1. Server: A high-performance computer or cloud-based computing resource (e.g., Amazon Web Services or Google Cloud Platform)

[1132] 2. Device: The smartphone, tablet, or PC used by the user

[1133] 3. Database: Relational database management system (e.g., MySQL, PostgreSQL)

[1134] 4. Sentiment Analysis Engine: Emotion recognition services such as Microsoft Azure Cognitive Services

[1135] 5. Analysis software: Python scripts, data analysis libraries such as Pandas and NumPy

[1136] 6. Communication Protocol: Secure data transmission and reception using HTTPS

[1137] User Authentication

[1138] The user enters their "user name" and "password" on the login screen. The device sends this information to the server. The server compares it with the database, and if authentication is successful, generates a session key and returns it to the device. The device displays the authentication result to the user, and if successful, transitions to the dashboard screen.

[1139] Collecting user-entered information

[1140] The user enters information such as "health status," "diet," and "allergy information" on the "Enter Health Information" page within the dashboard. The device sends this information to the server, which then stores it in a database. Once the information has been saved, a notification is returned to the device.

[1141] Information analysis

[1142] The server retrieves user input from the database and runs algorithms to evaluate foods and nutrients. For example, it analyzes the data using Python's Pandas and NumPy. It generates necessary nutrients and a recommended food list, and also evaluates the safety of processed foods and food additives. These results are then stored in a database.

[1143] Providing health advice

[1144] Based on the analysis results, the server uses an emotion engine to generate health advice taking into account the user's emotional data. The generated advice is sent to the device and displayed to the user. For example, if the user is feeling stressed, the server also provides ways to alleviate that stress.

[1145] Regular health check reminders

[1146] The server schedules the user's next health check and generates a reminder message based on the interval, which is then sent to the terminal, which then notifies the user.

[1147] Emotion Engine Operation

[1148] Users input or upload their own video, audio, and text information, which is used for emotion analysis. The device sends the emotion data to the server, where it is analyzed by the server's emotion engine. The analysis results are stored in a database and used to generate health advice.

[1149] Specific examples

[1150] Example 1: Entering and Evaluating New Health Information

[1151] After logging in, users enter their weight, dietary information, and allergy information, and upload information indicating their current emotional state. The device sends this information to a server, which stores it in a database and generates an appropriate food and nutrient list. For example, the device displays advice such as, "Foods containing omega-3 fatty acids are beneficial for you. You seem to have been feeling stressed recently, so try meditating to relax."

[1152] Example 2: Health check reminder

[1153] The server schedules the user's next health check date for three months from now. If the user has recently reported stress, the server sends an earlier reminder message, such as "It's time for a health check. Please also check your recent stress level."

[1154] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1155] Step 1: User Login

[1156] User: The user opens the login screen and enters their "username" and "password."

[1157] Enter: "Username" and "Password"

[1158] Device: The device sends this information to the server via an HTTPS request.

[1159] Output: Credentials sent

[1160] Specific operation: Input form data from the terminal is converted into JSON format and sent to the server using a secure communication protocol.

[1161] Step 2: User authentication

[1162] Server: The server checks the received authentication information against the user data in its database.

[1163] Input: Received authentication information

[1164] Output: Authentication result (success or failure) and session key (if successful)

[1165] Specific operation: The server retrieves user information from the database using an SQL query and verifies the password. If authentication is successful, it generates a session key and returns it to the terminal as an HTTP response.

[1166] Step 3: Viewing the authentication results

[1167] Terminal: The terminal displays the authentication result received from the server to the user. If successful, the terminal transitions to the dashboard screen.

[1168] Input: Authentication result (success or failure) and session key (if successful)

[1169] Output: Dashboard screen or error message

[1170] Specific operation: The terminal analyzes the received authentication result, and if successful, redirects the user to the dashboard screen, and if unsuccessful, displays an error message.

[1171] Step 4: Enter your health information

[1172] User: The user enters information such as "health status," "diet," and "allergy information" on the "Enter Health Information" page in the dashboard.

[1173] Input: Health information such as "health condition," "diet," and "allergy information"

[1174] Terminal: The terminal converts the input information into JSON format and sends it to the server via an HTTPS request.

[1175] Output: Health information sent

[1176] Specific operation: The terminal receives the information entered by the user, converts it to JSON, and sends it to the server via a secure communication protocol.

[1177] Step 5: Save your health information

[1178] Server: The server stores the received health information in a database.

[1179] Input: Received health information

[1180] Output: Save completion notification

[1181] Specific operation: The server uses an SQL query to insert information into the database, checks whether the save is complete, and then returns a save completion message to the terminal.

[1182] Step 6: Information Analysis

[1183] Server: The server takes user input from a database and runs algorithms to evaluate foods and nutrients.

[1184] Input: Health information stored in a database

[1185] Output: Analysis results (list of suitable foods, nutrients, and supplements)

[1186] Specific operation: Using a Python script, data analysis is performed using Pandas and NumPy. As a result of the analysis, a list of foods, nutrients, and supplements suitable for the user is generated.

[1187] Step 7: Generate health advice

[1188] Server: The server generates health advice based on the analysis results and emotion data.

[1189] Input: Analysis results, emotion data

[1190] Output: Health advice

[1191] Specific operation: The emotion engine is used to analyze emotion data, adjust the analysis results based on the results, and generate appropriate health advice.

[1192] Step 8: Providing health advice

[1193] Terminal: The terminal displays the health advice received from the server to the user.

[1194] Enter: Health Advice

[1195] Output: User advice screen

[1196] Specific operation: The received health advice is displayed on the user's dashboard screen and notifications are provided as needed.

[1197] Step 9: Remind yourself to check your health regularly

[1198] Server: The server schedules the user's next health check and generates reminder messages based on the set interval.

[1199] Input: User's health information, interval settings

[1200] Output: Reminder message

[1201] Specific operation: Using a Cron job or similar, a reminder message is generated and sent to the device at the set time.

[1202] Step 10: Sending Reminder Messages

[1203] Device: The device will notify the user of reminder messages and encourage them to check their health.

[1204] Input: Reminder message

[1205] Output: Reminder notification

[1206] Specific operation: The device receives the reminder message and notifies the user via push notification or in-app notification.

[1207] These steps enable the system to optimize the user's health management and provide personalized advice that takes into account their emotional state.

[1208] (Application example 2)

[1209] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1210] Conventional health management systems provide health advice based on user-entered information, but they do not consider real-time recommendations based on purchasing behavior in physical stores. There is a need for a system that utilizes health information, including the user's emotional state, to provide appropriate food and nutrient recommendations in physical stores. It is also necessary to efficiently remind users to schedule their next health check.

[1211] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1212] In this invention, the server includes means for user authentication, means for collecting user-input information, means for analyzing the collected information, means for generating a list of appropriate foods, nutrients, and supplements based on the analysis results, means for evaluating the safety of processed foods and food additives, means for providing the generated list and evaluation information to the user, means for generating and providing health advice and preventive methods, means for reminding the user to take regular health checks, means for providing recommendations to the user using smart glasses in a physical store, and means for scheduling and reminding the user of the user's next health check. This allows the user to receive appropriate health recommendations in real time while making a purchase in the physical store, and also enables efficient reminders for the next health check.

[1213] "User authentication" is the process of verifying a user's identity using a username and password when accessing a system.

[1214] "Collecting user-input information" is the stage where the user inputs information such as health status, dietary habits, and allergies into the system.

[1215] "Information analysis" is the process of using algorithms to evaluate collected user-entered information and generate a list of appropriate foods and nutrients.

[1216] "List generation" is the stage where a list of foods, nutrients, and supplements suitable for the user is created based on the analysis results.

[1217] "Safety assessment" is an analytical process conducted to evaluate the safety of processed foods and food additives.

[1218] "Providing advice" is the process of providing health advice and preventive methods to the user based on the generated list and evaluation information.

[1219] "Remind" is the process of scheduling a user's next health check date and sending a timely reminder message.

[1220] "Recommendations in physical stores" refers to the use of smart glasses to recommend appropriate products and health information in real time to users in physical stores based on their purchasing behavior.

[1221] "Health check schedule setting" is a process of setting the date of the user's next health check and sending reminders based on that schedule.

[1222] The present invention provides a system for efficiently managing a user's health, and in particular provides real-time recommendations and health check reminders in physical stores. The specific operation of the system is described below.

[1223] First, let's explain user authentication. The user accesses the login screen and enters their "user name" and "password." The terminal sends the "user name" and "password" entered by the user to the server. The server compares the received authentication information with a database and performs user authentication. If authentication is successful, it generates a session key and returns it to the terminal. The terminal displays the authentication result to the user, and if successful, transitions to the dashboard screen.

[1224] Next, we will explain how to collect user-entered information. The user enters information such as "health status," "diet," and "allergy information" on the "Enter Health Information" page in the dashboard. The device sends the entered information to the server. The server stores the received information in a database. A notification that the information has been saved is returned to the device.

[1225] In the information analysis step, the server retrieves user input information from the database and runs algorithms to evaluate foods and nutrients. It generates a list of appropriate foods, nutrients, and supplements, and performs safety evaluations of processed foods and food additives. The analysis results and safety evaluation results are stored in the database.

[1226] When providing health advice, the server generates health advice based on the analysis results and safety assessment results. This advice also takes into account the emotion recognition results of the emotion engine. The device displays the health advice to the user. For example, if the user is feeling stressed, it also provides ways to alleviate that stress.

[1227] It also includes a function to schedule the user's next health check and generate a reminder message. The server sends the reminder message to the device based on the interval. The device notifies the user of the reminder message and encourages them to check their health.

[1228] We also explain real-time recommendations in physical stores. When a user walks around a store wearing smart glasses, the device requests recommendations from the server based on the user's location and emotional state. The server analyzes the received information and recommends appropriate products and activities. For example, if the user is feeling stressed, recommendations such as "green tea" and "dark chocolate" will be displayed.

[1229] The implementation of this system uses the following hardware and software:

[1230] Hardware: Smart glasses (e.g., smart glasses), cloud server (e.g., cloud server), terminal (e.g., PC or smartphone)

[1231] Software: Databases (e.g., MySQL, PostgreSQL, MongoDB), data analysis algorithms, emotion engines

[1232] As a concrete example, a user wearing smart glasses receives recommendations such as "green tea" or "dark chocolate" when selecting products in a physical store. At the same time, a reminder message is displayed saying, "Don't forget your next health check," since the user's next health check is approaching.

[1233] An example of a prompt to be input to the generative AI model is, "Write a Python program that analyzes the user's emotional state and recommends healthy foods and activities based on that. Also, include a function to remind them to come for their next health check."

[1234] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1235] Step 1: User authentication

[1236] Input: Username, Password

[1237] Specific operation: The user accesses the login screen and enters their username and password. The device sends the input information to the server.

[1238] Data processing: The server checks the received username and password against its database.

[1239] Output: If authentication is successful, the server generates a session key and returns it to the terminal. The terminal displays the authentication result to the user, and if successful, transitions to the dashboard screen.

[1240] Step 2: Collecting User-Input Information

[1241] Input: Health condition, dietary habits, allergy information

[1242] Specific operation: The user enters information on the "Enter Health Information" page in the dashboard. The device sends the entered information to the server.

[1243] Data processing: The server stores the received information in a database.

[1244] Output: The server returns a notification to the device that the save is complete.

[1245] Step 3: Information analysis

[1246] Input: User-entered information (health status, dietary habits, allergy information)

[1247] Specific operation: The server retrieves user input information from the database and runs algorithms to evaluate foods and nutrients.

[1248] Data calculation: The server runs the evaluation algorithm and generates a list of suitable foods, nutrients, and supplements.

[1249] Output: The analysis results and generated list are obtained. In addition, the safety assessment of processed foods and food additives is performed and the results are also obtained.

[1250] Step 4: Providing health advice

[1251] Input: Analysis results, generated list, safety assessment results, emotion recognition results by emotion engine

[1252] Specific operation: The server generates health advice based on the analysis results and safety assessment results, taking into account emotion recognition results.

[1253] Data calculation: Comprehensively evaluate the emotion recognition results obtained from the emotion engine and generate optimal health advice.

[1254] Output: The terminal displays the generated health advice to the user.

[1255] Step 5: Remind yourself to check your health regularly

[1256] Input: The user's next scheduled health check

[1257] Specific operation: The server generates reminder messages based on the set interval.

[1258] Data processing: Reminder messages are generated based on each user's health check interval.

[1259] Output: The server sends a remind message to the terminal, which notifies the user of the message.

[1260] Step 6: Real-time recommendations in-store

[1261] Input: User's location, emotional state

[1262] Specific operation: When a user walks around a store using smart glasses, the device requests the user's location information and emotional state from the server.

[1263] Data calculation: The server analyzes the received location information and emotional state and recommends appropriate products and activities.

[1264] Output: The device displays the recommendation results in real time on the user's smart glasses.

[1265] Step 7: Schedule your health checks

[1266] Input: User's health check schedule information

[1267] Specific operation: The server schedules the user's next health check.

[1268] Data processing: Schedule the next health check date and time based on the user's health data.

[1269] Output: The device sends a reminder message to the user based on the configured schedule information.

[1270] The above are the specific steps of the program processing.

[1271] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1272] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1273] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1274] [Third embodiment]

[1275] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1276] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1277] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1278] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1279] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1280] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1281] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1282] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1283] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1284] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1285] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1286] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1287] The present invention is a system for enabling users to efficiently manage their health, analyzing information input by the user and providing appropriate health advice. A specific operation method of the system will be described below.

[1288] User Authentication

[1289] User:

[1290] The user accesses the login screen and enters their "user name" and "password."

[1291] Device:

[1292] The terminal sends the "user name" and "password" entered by the user to the server.

[1293] server:

[1294] The server checks the received authentication information against a database, and if authentication is successful, generates a session key and returns the generated session key to the terminal.

[1295] Device:

[1296] The terminal notifies the user that the authentication was successful and displays the dashboard screen.

[1297] Collecting user-entered information

[1298] User:

[1299] Users go to the "Enter Health Information" page in the dashboard and enter information such as "health status," "diet," and "allergy information."

[1300] Device:

[1301] The terminal transmits the information entered by the user to the server.

[1302] server:

[1303] The server saves the received information in a database and returns a notification to the device that saving is complete.

[1304] Information analysis

[1305] server:

[1306] The server runs algorithms that generate lists of suitable foods, nutrients, and supplements based on user-entered information in the database, and also performs safety assessments of processed foods and food additives.

[1307] Providing health advice

[1308] server:

[1309] The server documents specific health advice and preventive measures based on the generated list and safety assessment results.

[1310] Device:

[1311] The terminal displays the health advice and prevention methods received from the server to the user.

[1312] Regular health check reminders

[1313] server:

[1314] The server registers the next health check date in the schedule based on the user's check interval and generates a reminder message.

[1315] Device:

[1316] The device notifies the user of reminder messages and encourages regular health checks.

[1317] Specific examples

[1318] As a concrete example, the following scenario will be described.

[1319] Example 1: Entering and Evaluating New Health Information

[1320] User:

[1321] After logging in, the user enters their "weight," "dietary details," and "allergy information."

[1322] Device:

[1323] The input information is sent to the server.

[1324] server:

[1325] The information is stored in a database, appropriate food and nutrient lists are generated, and processed food safety is assessed.

[1326] server:

[1327] Based on the generated list and the evaluation results, health advice is created and sent to the device.

[1328] Device:

[1329] Health advice such as "Foods containing omega-3 fatty acids are beneficial for you" is displayed.

[1330] Example 2: Health check reminder

[1331] server:

[1332] Set the user's next health check date to three months later.

[1333] server:

[1334] When the set date and time approaches, a reminder message will be sent to your device.

[1335] Device:

[1336] A reminder message is sent to the user saying, "It's time for a health check."

[1337] The system of the present invention allows users to easily and efficiently manage their own health, make appropriate food choices, and take preventative measures, thereby contributing to the prevention of health hazards.

[1338] The processing flow will be explained below.

[1339] Program processing steps

[1340] User Authentication

[1341] Step 1:

[1342] User: Enter your "username" and "password" on the login screen.

[1343] Step 2:

[1344] Terminal: Sends the entered authentication information to the server.

[1345] Step 3:

[1346] Server: Compares the received authentication information with a database and performs user authentication.

[1347] Step 4:

[1348] Server: If authentication is successful, generates a session key and returns it to the terminal.

[1349] Step 5:

[1350] Terminal: The authentication result is displayed to the user, and if successful, the user is taken to the dashboard screen.

[1351] Collecting user-entered information

[1352] Step 1:

[1353] User: Enter information such as "health condition," "diet," and "allergy information" on the "Enter Health Information" page in the dashboard.

[1354] Step 2:

[1355] Terminal: Sends the entered information to the server.

[1356] Step 3:

[1357] Server: Stores the received information in a database.

[1358] Step 4:

[1359] Server: Sends confirmation of save completion to the device.

[1360] Information analysis

[1361] Step 1:

[1362] Server: Retrieves user input information from the database.

[1363] Step 2:

[1364] Server: Runs the algorithms that evaluate foods and nutrients.

[1365] Step 3:

[1366] Server: Generates a list of suitable foods, nutrients, and supplements.

[1367] Step 4:

[1368] Server: Evaluates the safety of processed foods and food additives.

[1369] Step 5:

[1370] Server: Stores the analysis results and safety evaluation results in a database.

[1371] Providing health advice

[1372] Step 1:

[1373] Server: Generates health advice based on the analysis results and safety assessment results.

[1374] Step 2:

[1375] Server: Sends health advice to the device.

[1376] Step 3:

[1377] Terminal: displays health advice to the user.

[1378] Regular health check reminders

[1379] Step 1:

[1380] Server: Schedules the user's next health check.

[1381] Step 2:

[1382] Server: Generates reminder messages based on configured intervals.

[1383] Step 3:

[1384] Server: Sends reminder messages to the device.

[1385] Step 4:

[1386] Terminal: Notify the user of the reminder message.

[1387] Example 1

[1388] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1389] Conventional health management systems struggle to efficiently provide appropriate health advice that takes into account a user's health status, diet, and allergy information. They also lacked reminders for regular health checks, and did not provide sufficient support for users to continuously manage their health. Furthermore, some systems lacked session management and generative AI models, resulting in a poor user experience.

[1390] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1391] In this invention, the server includes means for user authentication, means for collecting user-input information, means for analyzing the collected information, means for generating a list of appropriate foods, nutrients, and supplements based on the analysis results, means for evaluating the safety of processed foods and food additives, means for providing the generated list and evaluation information to the user, means for generating and providing health advice and preventive methods, means for reminding users to take regular health checks, means for generating and managing session keys, and means for creating health advice and reminder messages using a generative AI model, thereby enabling users to efficiently and continuously manage their own health.

[1392] "User authentication" is the process of verifying a user's identity when they access a system.

[1393] "User input information" refers to data such as health status, dietary habits, and allergy information that the user provides to the system.

[1394] "Means of analyzing information" refers to the method of analyzing and evaluating related data based on collected user-entered information.

[1395] The "means for generating a list of foods, nutrients, and supplements" is a method for selecting and listing foods, nutrients, and supplements suitable for the user based on the analysis results.

[1396] "Means for safety assessment" refers to the methods used to evaluate the safety of processed foods and food additives and reflect the results in the list.

[1397] The "means for providing to the user" refers to a method for conveying the generated list and rating information to the user.

[1398] The "means for generating and providing health advice and preventive measures" is a method for generating and providing specific health advice and preventive measures to the user based on the analysis results.

[1399] The "means for reminding users to check their health" is a method for generating and notifying reminder messages to encourage users to check their health regularly.

[1400] The "means for generating and managing a session key" is a method for generating and managing a session key for identifying a user during a session after user authentication has been successful.

[1401] A "generative AI model" is an artificial intelligence model used for natural language generation and data analysis, and an example is the GPT series.

[1402] The present invention is a system for enabling users to efficiently manage their health by analyzing input information from the user and providing appropriate health advice. Specific implementation and operation methods of the system are described below.

[1403] System configuration

[1404] The present invention consists of a user terminal, a server, and a database. The user terminal can be a PC, smartphone, tablet, etc. The server is a high-performance computer equipped with a database management system (e.g., MySQL) and analytical software (e.g., Python scripts). In addition, a generative AI model (e.g., GPT-4) is used for natural language generation and data analysis.

[1405] User Authentication

[1406] The user accesses the login screen using a terminal and enters their "user name" and "password." This authentication information is sent from the terminal to the server via a secure protocol (HTTPS). The server compares the received information with data in a database, and if authentication is successful, it generates a session key and returns it to the terminal. The terminal notifies the user that authentication was successful and displays the dashboard screen.

[1407] Collecting user-entered information

[1408] The user goes to the "Enter Health Information" page in the dashboard and enters information such as "health status," "diet," and "allergy information." This information is sent from the device to the server in JSON format. The server stores the received information in a database and notifies the device once it has been saved.

[1409] Information analysis

[1410] The server retrieves user information from the database and analyzes it using Python scripts. Based on the analysis results, it generates a list of appropriate foods, nutrients, and supplements. It also evaluates the safety of processed foods and food additives and lists the results.

[1411] Providing health advice

[1412] The server then documents specific health advice and preventative measures based on the generated list and safety assessment results. This process uses a generative AI model (GPT-4). The generated advice is sent to the device and displayed to the user. For example, advice such as "Foods containing omega-3 fatty acids are beneficial for you" is provided.

[1413] Regular health check reminders

[1414] The server schedules the next health check based on the user's check interval. When the scheduled date and time approaches, it uses a generative AI model to create a reminder message and sends it to the device. The device then notifies the user of this reminder message, encouraging them to perform regular health checks. For example, a message saying, "It's time for a health check."

[1415] Specific examples

[1416] Here is a specific example.

[1417] Example 1: After logging in, a user enters their weight, dietary details, and allergy information, and the device sends the information to the server. The server stores the information in a database, generates a list of appropriate foods and nutrients, and provides health advice.

[1418] Example 2: The server sets the user's next health check date three months from now, and when the set date and time approaches, it generates a reminder message and sends it to the device.

[1419] In this way, users can efficiently and continuously manage their own health.

[1420] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1421] Step 1:

[1422] User: The user accesses the login screen and enters their "username" and "password."

[1423] Enter: "Username" and "Password"

[1424] Output: Sends authentication information to the terminal

[1425] Specific behavior: The user completes the login screen and clicks the "Login" button.

[1426] Step 2:

[1427] Terminal: The terminal encrypts the "username" and "password" entered by the user and sends them to the server via a secure protocol (e.g., HTTPS).

[1428] Input: Encrypted "Username" and "Password"

[1429] Output: Sends authentication information to the server

[1430] Specific operation: The device protects the information entered using SSL / TLS encryption and sends it to the server as an HTTPS request.

[1431] Step 3:

[1432] Server: The server checks the received credentials against a database (e.g. MySQL) using a hashed password.

[1433] Input: Received authentication information

[1434] Output: Authentication result (success or failure)

[1435] Specific operation: The server compares the hash value of the received information with the user information stored in the database.

[1436] Step 4:

[1437] Server: If authentication is successful, the server generates a random session key and returns it to the device.

[1438] Input: Authentication success flag

[1439] Output: Session key

[1440] Specific operation: The server generates a session ID, temporarily stores it in a database, and sends it back to the device.

[1441] Step 5:

[1442] Terminal: The terminal notifies the user that authentication was successful and displays the dashboard screen.

[1443] Input: Session key

[1444] Output: Dashboard screen display

[1445] Specific behavior: The device saves the received session key and displays the dashboard to the user along with a successful login message.

[1446] Step 6:

[1447] User: The user goes to the "Enter Health Information" page in the dashboard and enters information such as "health status," "diet," and "allergy information."

[1448] Input: "Health status", "Diet", "Allergy information"

[1449] Output: Sends information to the terminal

[1450] What happens: A user fills in a form and clicks the "Submit" button.

[1451] Step 7:

[1452] Terminal: The terminal sends the information entered by the user to the server, using JSON format data.

[1453] Input: User input information (JSON format)

[1454] Output: Sends input information to the server

[1455] Specific operation: The device converts the input information into JSON format and sends it to the server via an HTTPS request.

[1456] Step 8:

[1457] Server: The server stores the received information in a database.

[1458] Input: User input information (JSON format)

[1459] Output: Save result (success or failure)

[1460] Specific operation: The server writes the received information to the database.

[1461] Step 9:

[1462] Server: The server returns a notification to the device that the save is complete.

[1463] Input: Save success flag

[1464] Output: Save completion notification

[1465] Specific behavior: The server confirms the success of the save and returns a notification to the device as an HTTPS response.

[1466] Step 10:

[1467] Server: The server retrieves the user information from the database and runs the analysis algorithm.

[1468] Input: User information

[1469] Output: Analysis results (food list, safety assessment)

[1470] What it does: The server runs a Python script to evaluate the list of suitable foods and nutrients and the safety of processed foods.

[1471] Step 11:

[1472] Server: The server uses generative AI models to document health advice and prevention methods.

[1473] Input: Analysis results

[1474] Output: Health advice and prevention methods (text)

[1475] Specific operation: The server runs a generative AI model (e.g., GPT-4) and generates advice in natural language based on the analysis results.

[1476] Step 12:

[1477] Server: The server sends the generated advice and prevention methods to the device.

[1478] Input: Health advice and prevention methods (text)

[1479] Output: Send advice to terminal

[1480] Specific operation: The server returns the generated text to the terminal as an HTTPS response.

[1481] Step 13:

[1482] Terminal: The terminal displays the health advice and prevention methods received from the server to the user.

[1483] Input: Advice received from the server

[1484] Output: Display advice to the user

[1485] Specific operation: The terminal displays the received information on the user screen in an appropriate format.

[1486] Step 14:

[1487] Server: The server schedules the next health check date based on the user's check interval.

[1488] Input: User check interval

[1489] Output: Next health check date

[1490] Specific operation: The server registers the next health check date in the schedule management system.

[1491] Step 15:

[1492] Server: When the set date and time approaches, the server uses a generative AI model to generate a reminder message.

[1493] Input: Next health check date

[1494] Output: Reminder message (text)

[1495] Specific operation: The server uses the generative AI model to generate appropriate reminder text.

[1496] Step 16:

[1497] Server: The server sends the generated remind message to the device.

[1498] Input: Reminder message (text)

[1499] Output: Send a reminder message to the device

[1500] Specific operation: The server sends the generated message to the terminal as an HTTPS response.

[1501] Step 17:

[1502] Device: The device will notify the user as a reminder message that it is time for a health check.

[1503] Input: Reminder message received from the server

[1504] Output: Notify the user

[1505] What happens: The device displays a reminder message to the user and notifies the user using the notification system.

[1506] (Application example 1)

[1507] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1508] Conventional health management systems make it difficult for users to select appropriate foods and nutrients based on their own health information. They also lacked a means to effectively recommend related products and services, making it difficult for users to make optimal purchasing decisions based on their health status. Furthermore, they lacked a mechanism to provide health advice while also encouraging actual purchasing behavior.

[1509] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1510] In this invention, the server includes means for user authentication, means for collecting user-entered information, means for analyzing the collected information, means for recommending appropriate products and services based on the analysis results, means for evaluating the safety of processed products and ingredients, means for providing the generated list and evaluation information to the user, means for generating and providing health advice and preventive methods, means for reminding the user to take regular health checks, and means for displaying links to online shopping sites to facilitate purchases. This allows users to easily select optimal products and services based on their own health condition and efficiently manage their health.

[1511] "User authentication" is the process by which a user accesses a system using their authentication information (e.g., username and password).

[1512] "User-input information" refers to data such as health status, dietary habits, and allergy information that a user provides to the system.

[1513] "Information analysis" is data processing to recommend appropriate products and foods based on collected user-entered information.

[1514] "Product recommendation" is the process of presenting optimal products and services to users based on the results of information analysis.

[1515] "Ingredient safety evaluation" is a procedure for evaluating the safety of processed products and ingredients and providing that information to users.

[1516] "Providing a list" is a procedure for transmitting the generated list of products and services and evaluation information to users.

[1517] "Health advice" is a procedure that provides specific health management methods and preventative measures based on the user's health information.

[1518] "Remind" is a procedure that notifies the user when it is time for a regular health check and encourages them to carry out the check.

[1519] "Mail Order Link" is a procedure for generating and displaying a link that allows users to purchase recommended products or services.

[1520] This specification details a specific embodiment of a system for efficiently managing a user's health. The system collects and analyzes health information provided by the user, recommends appropriate products and nutrients, and provides links to online shopping sites to encourage users to make purchases.

[1521] System Overview

[1522] The system includes the following elements:

[1523] A means of user authentication

[1524] A means of collecting user input information

[1525] How we analyze the information we collect

[1526] A means of recommending appropriate products and services based on analysis results

[1527] A means of assessing the safety of processed products and ingredients

[1528] Means for providing generated list and rating information to a user

[1529] A means of generating and delivering health advice and prevention methods

[1530] A means of reminding people to check their health regularly

[1531] Displaying links to online shopping sites to make purchasing easier

[1532] Hardware and Software Configuration

[1533] Hardware

[1534] Smartphone: a device on which the user operates an interface

[1535] Server: Backend server that stores and processes data

[1536] software

[1537] Flask: A lightweight web framework built in Python

[1538] sqlite3: a local database management system

[1539] React: Used to build the front-end user interface

[1540] Data processing and calculation

[1541] User Authentication

[1542] The user enters their authentication information (username and password) and sends it to the server, which checks it against the database and, if authentication is successful, generates and returns a session key.

[1543] Collecting user-entered information

[1544] The user enters information about their health, diet, allergies, etc., and the device sends this information to the server, which then stores the received information in a database.

[1545] Information analysis

[1546] The server analyzes the user-entered information in the database and performs data calculations to recommend appropriate products, nutrients, and supplements. Using a generative AI model, it analyzes the data based on the prompt text and generates results.

[1547] Providing health advice

[1548] The server generates specific health advice and preventive measures based on the user's health information and sends them to the device, which then displays them to the user.

[1549] Reminders and shopping links

[1550] The server sets the date for the user's next health check and generates a reminder message. The device notifies the user of this and encourages regular health checks. The device also displays a link to purchase recommended products, allowing the user to easily access the online shopping site.

[1551] Specific examples

[1552] Example 1: Entering and Evaluating New Health Information

[1553] After logging in, users enter their health information (weight, dietary habits, and allergy information). The device sends the information to the server, which stores it in a database. The server uses a generative AI model to generate a list of appropriate foods and nutrients and evaluates the safety of processed foods. Based on the results, health advice and product recommendations are provided and notified to the user.

[1554] Example prompt sentence:

[1555] Recommend optimal foods and nutrients based on your health, diet, and allergies. Use the following information:

[1556] Health: Weight gain in the past week

[1557] Diet: Few vegetables in daily meals

[1558] Allergy Information: Nut allergy

[1559] Example 2: Displaying online shopping links and encouraging purchases

[1560] The server creates a list of recommended products based on the analysis results and generates a link to the online shopping site. The device displays this to the user, who can click on the product link to access the online shopping site and make a purchase.

[1561] As described above, the system of the present invention allows users to easily select optimal products and services based on their own health condition, and efficiently manage their health.

[1562] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1563] Step 1:

[1564] When a user opens the app, a login screen appears. The user enters their authentication information (username and password). The entered information is sent from the device to the server.

[1565] Input: Username, Password

[1566] Output: Sending authentication information to the server

[1567] Step 2:

[1568] The server checks the received authentication information against a database, and if authentication is successful, generates a session key and returns the generated session key to the terminal.

[1569] Input: Credentials

[1570] Output: Session key, authentication result

[1571] Step 3:

[1572] The device notifies the user that authentication was successful and displays the dashboard screen. The user then moves to the "Enter Health Information" page to enter data such as health status, dietary habits, and allergy information.

[1573] Input: Session key, user information

[1574] Output: View dashboard

[1575] Step 4:

[1576] After entering health information, the user sends the information from the device to the server, which stores the information in a database and returns a notification to the device that the information has been saved.

[1577] Input: Health information (e.g., health condition, diet, allergy information)

[1578] Output: Saving to database, notification of saving completion

[1579] Step 5:

[1580] The server analyzes the user-entered information stored in the database and uses a generative AI model to generate a list of appropriate foods and nutrients based on the prompt.

[1581] Input: User's health information

[1582] Output: List of foods and nutrients

[1583] Step 6:

[1584] The server uses the generated list and other data to evaluate the safety of processed products and ingredients, and then compiles the evaluation results into written advice for the user.

[1585] Input: list of foods and nutrients, generative AI model

[1586] Output: Safety assessment, health advice

[1587] Step 7:

[1588] The server sends the generated advice to the terminal, which displays it to the user. The terminal then displays further recommended information on suitable products and services, as well as links to online shopping sites where the products can be purchased.

[1589] Input: Health advice, assessment results

[1590] Output: Display advice, display mail order link

[1591] Step 8:

[1592] When a user clicks on a shopping link, a browser is launched and the specified shopping site is opened, allowing the user to easily purchase the product.

[1593] Input: Click on the online shopping link

[1594] Output: Display of online shopping site, facilitating product purchase

[1595] Step 9:

[1596] The server sets the date of the user's next health check and generates a reminder message. When the set date and time approaches, the reminder message is sent to the device. The device then notifies the user of the reminder message.

[1597] Input: User health check interval

[1598] Output: Generate reminder message, notification

[1599] Through the above processing steps, the system of the present invention enables users to efficiently manage their health and conveniently purchase related products and services.

[1600] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1601] The present invention is a system for efficiently managing a user's health, and in particular, recognizes the user's emotions and provides health advice and reminders based on those emotions. The specific operation of the system is described below.

[1602] User Authentication

[1603] User:

[1604] The user accesses the login screen and enters their "user name" and "password."

[1605] Device:

[1606] The terminal sends the "user name" and "password" entered by the user to the server.

[1607] server:

[1608] The server compares the received authentication information with a database to authenticate the user. If authentication is successful, it generates a session key and returns it to the terminal.

[1609] Device:

[1610] The terminal displays the authentication result to the user, and if successful, transitions to the dashboard screen.

[1611] Collecting user-entered information

[1612] User:

[1613] Users enter information such as their health status, diet, and allergy information on the "Enter Health Information" page within the dashboard.

[1614] Device:

[1615] The entered information is sent to the server.

[1616] server:

[1617] The received information is saved in the database, and a notification that saving is complete is returned to the device.

[1618] Information analysis

[1619] server:

[1620] It takes user input from the database and runs algorithms to evaluate foods and nutrients, generates lists of suitable foods, nutrients, and supplements, and evaluates the safety of processed foods and food additives.

[1621] server:

[1622] The analysis results and safety evaluation results are stored in a database.

[1623] Providing health advice

[1624] server:

[1625] Health advice is generated based on the analysis results and safety assessment results, taking into account emotion recognition results from the emotion engine.

[1626] Device:

[1627] Health advice is displayed to the user. For example, if the user is feeling stressed, it also provides ways to alleviate the stress.

[1628] Regular health check reminders

[1629] server:

[1630] Schedule the user's next health check. Generate reminder messages based on the interval you set.

[1631] server:

[1632] Send a reminder message to your device.

[1633] Device:

[1634] Reminder messages are sent to users to encourage them to check their health.

[1635] Emotion Engine Operation

[1636] User:

[1637] Emotions are analyzed from video, audio, and text information entered or uploaded by the user.

[1638] Device:

[1639] The emotion data is sent to the server.

[1640] server:

[1641] The emotion engine analyzes the transmitted data and recognizes the user's emotions. The recognition results are stored in a database and used to generate health advice.

[1642] Specific examples

[1643] Example 1: Entering and Evaluating New Health Information

[1644] User:

[1645] After logging in, users enter their weight, dietary information, and allergy information. They also enter or upload information that indicates their current emotional state.

[1646] Device:

[1647] The input information and emotion data are sent to the server.

[1648] server:

[1649] The information is stored in a database and a list of appropriate foods and nutrients is generated. If the user is feeling stressed, it will recommend foods and activities that will help relieve stress.

[1650] Device:

[1651] The advice displayed is, "Foods containing omega-3 fatty acids are beneficial for you. You seem to have been feeling stressed lately, so try meditating to help you relax."

[1652] Example 2: Health check reminder

[1653] server:

[1654] Set the user's next health check date three months from now. If the user has recently reported stress, set an earlier reminder message.

[1655] server:

[1656] When the set date and time approaches, a reminder message will be sent to your device.

[1657] Device:

[1658] It notifies you, "It's time for a health check. Let's also check your recent stress level."

[1659] The system of the present invention supports users in optimal health management based on their own health and emotional state. By combining it with an emotion engine, it becomes possible to provide more personalized health advice, which is of great help to users in improving their health and preventing disease.

[1660] The processing flow will be explained below.

[1661] Program processing steps

[1662] User Authentication

[1663] Step 1:

[1664] User: Enter your "username" and "password" on the login screen.

[1665] Step 2:

[1666] Terminal: Sends the entered authentication information to the server.

[1667] Step 3:

[1668] Server: Compares the received authentication information with a database and performs user authentication.

[1669] Step 4:

[1670] Server: If authentication is successful, generates a session key and returns it to the terminal.

[1671] Step 5:

[1672] Terminal: The authentication result is displayed to the user, and if successful, the user is taken to the dashboard screen.

[1673] Collecting user-entered information

[1674] Step 1:

[1675] User: Enter information such as "health condition," "diet," and "allergy information" on the "Enter Health Information" page in the dashboard.

[1676] Step 2:

[1677] Terminal: Sends the entered information to the server.

[1678] Step 3:

[1679] Server: Stores the received information in a database.

[1680] Step 4:

[1681] Server: Sends confirmation of save completion to the device.

[1682] Information analysis

[1683] Step 1:

[1684] Server: Retrieves user input information from the database.

[1685] Step 2:

[1686] Server: Runs the algorithms that evaluate foods and nutrients.

[1687] Step 3:

[1688] Server: Generates a list of suitable foods, nutrients, and supplements.

[1689] Step 4:

[1690] Server: Evaluates the safety of processed foods and food additives.

[1691] Step 5:

[1692] Server: Stores the analysis results and safety evaluation results in a database.

[1693] Providing health advice

[1694] Step 1:

[1695] Server: Generates health advice based on the analysis results and safety assessment results, taking into account emotion recognition results from the emotion engine.

[1696] Step 2:

[1697] Server: Sends health advice to the device.

[1698] Step 3:

[1699] Terminal: displays health advice to the user.

[1700] Regular health check reminders

[1701] Step 1:

[1702] Server: Schedules the user's next health check.

[1703] Step 2:

[1704] Server: Generates reminder messages based on configured intervals.

[1705] Step 3:

[1706] Server: Sends reminder messages to the device.

[1707] Step 4:

[1708] Terminal: Notify the user of the reminder message.

[1709] Emotion Engine Operation

[1710] Step 1:

[1711] User: Analyze emotions from video, audio, and text information you input or upload.

[1712] Step 2:

[1713] Terminal: Sends emotion data to the server.

[1714] Step 3:

[1715] Server: The emotion engine analyzes the transmitted data and recognizes the user's emotion.

[1716] Step 4:

[1717] Server: Stores emotion recognition results in a database and uses them to generate health advice.

[1718] Specific examples

[1719] Example 1: Entering and Evaluating New Health Information

[1720] Step 1:

[1721] User: After logging in, the user enters their weight, dietary information, and allergy information. They also enter or upload information that indicates their current emotional state.

[1722] Step 2:

[1723] Terminal: Sends input information and emotion data to the server.

[1724] Step 3:

[1725] Server: Stores the information in a database.

[1726] Step 4:

[1727] Server: Generates a list of appropriate foods and nutrients. If the user is feeling stressed, it recommends foods and activities that are good for stress relief.

[1728] Step 5:

[1729] Device: The generated list and the evaluation results are notified to the user. For example, advice such as "Foods containing omega-3 fatty acids are beneficial for you. You seem to have been feeling stressed lately, so try meditating to relax." is displayed.

[1730] Example 2: Health check reminder

[1731] Step 1:

[1732] Server: Set the user's next health check date to three months from now. If the user has recently reported stress, set an earlier reminder message.

[1733] Step 2:

[1734] Server: Generates a reminder message when the set date and time approaches.

[1735] Step 3:

[1736] Server: Sends reminder messages to the device.

[1737] Step 4:

[1738] Device: A reminder message is sent to the user saying, "It's time for a health check. Check your recent stress level."

[1739] Example 2

[1740] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1741] In modern society, users tend to neglect their health and emotional management in their busy daily lives. As a result, health problems and stress that are often overlooked can accumulate, potentially leading to serious health problems. Furthermore, fluctuations in emotional states often have a direct impact on health, creating a need for health advice that takes this into account. However, existing systems lack the ability to recognize a user's specific emotional state and provide appropriate advice based on that. Therefore, there is a need for a system that can comprehensively manage a user's health and emotional states and provide more personalized health advice.

[1742] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for user authentication, means for collecting user-input information, means for analyzing the collected information, means for generating a list of appropriate foods, nutrients, and supplements based on the analysis results, means for evaluating the safety of processed foods and food additives, means for providing the generated list and evaluation information to the user, means for generating and providing health advice and preventive measures, means for collecting and analyzing emotional data, means for adjusting health advice based on the collected emotional data, and means for reminding users to take regular health checks. This makes it possible to comprehensively manage the user's health and emotional states and provide health advice and regular reminders that are optimized for each individual user.

[1743] "Means for user authentication" is the process by which a user enters their "user name" and "password" and verifies the user's identity by checking them against a database.

[1744] "Means for collecting user-input information" refers to the process by which users provide personal information such as "health status," "dietary habits," and "allergy information" to the system, and this information is received and stored.

[1745] "Means for analyzing collected information" refers to the process by which the system processes collected user data using algorithms and analytical software to find the necessary insights and patterns.

[1746] The "means for generating a list of appropriate foods, nutrients, and supplements" is a process for listing optimal foods, nutrients, and supplements based on the user's health condition.

[1747] "Means for evaluating the safety of processed foods and food additives" refers to a process for evaluating the safety of processed foods and food additives consumed by users and providing the results.

[1748] The "means for providing the generated list and evaluation information to the user" is the process of providing the analyzed data and generated list in a format that is accessible to the user.

[1749] "Means for generating and providing health advice and prevention methods" refers to the process of creating and providing accurate health advice and guidance for disease prevention to the user based on the user's health condition and analysis data.

[1750] "Means for collecting and analyzing emotional data" refers to the process of identifying emotions from the user's video, audio, and text information and analyzing that data.

[1751] "Means for tailoring health advice based on collected emotional data" refers to a process for individually tailoring health advice content depending on the user's emotional state.

[1752] The "means for providing periodic health check reminders" is a process that notifies the user of the need for a health check based on set time intervals or conditions.

[1753] The present invention is a system for efficiently managing a user's health, which takes into account not only the user's health condition but also their emotional state to provide more personalized health advice and reminder functions. Specific embodiments for implementing the present invention will be described below.

[1754] Hardware and Software

[1755] This system is configured using the following hardware and software:

[1756] 1. Server: A high-performance computer or cloud-based computing resource (e.g., Amazon Web Services or Google Cloud Platform)

[1757] 2. Device: The smartphone, tablet, or PC used by the user

[1758] 3. Database: Relational database management system (e.g., MySQL, PostgreSQL)

[1759] 4. Sentiment Analysis Engine: Emotion recognition services such as Microsoft Azure Cognitive Services

[1760] 5. Analysis software: Python scripts, data analysis libraries such as Pandas and NumPy

[1761] 6. Communication Protocol: Secure data transmission and reception using HTTPS

[1762] User Authentication

[1763] The user enters their "user name" and "password" on the login screen. The device sends this information to the server. The server compares it with the database, and if authentication is successful, generates a session key and returns it to the device. The device displays the authentication result to the user, and if successful, transitions to the dashboard screen.

[1764] Collecting user-entered information

[1765] The user enters information such as "health status," "diet," and "allergy information" on the "Enter Health Information" page within the dashboard. The device sends this information to the server, which then stores it in a database. Once the information has been saved, a notification is returned to the device.

[1766] Information analysis

[1767] The server retrieves user input from the database and runs algorithms to evaluate foods and nutrients. For example, it analyzes the data using Python's Pandas and NumPy. It generates necessary nutrients and a recommended food list, and also evaluates the safety of processed foods and food additives. These results are then stored in a database.

[1768] Providing health advice

[1769] Based on the analysis results, the server uses an emotion engine to generate health advice taking into account the user's emotional data. The generated advice is sent to the device and displayed to the user. For example, if the user is feeling stressed, the server also provides ways to alleviate that stress.

[1770] Regular health check reminders

[1771] The server schedules the user's next health check and generates a reminder message based on the interval, which is then sent to the terminal, which then notifies the user.

[1772] Emotion Engine Operation

[1773] Users input or upload their own video, audio, and text information, which is used for emotion analysis. The device sends the emotion data to the server, where it is analyzed by the server's emotion engine. The analysis results are stored in a database and used to generate health advice.

[1774] Specific examples

[1775] Example 1: Entering and Evaluating New Health Information

[1776] After logging in, users enter their weight, dietary information, and allergy information, and upload information indicating their current emotional state. The device sends this information to a server, which stores it in a database and generates an appropriate food and nutrient list. For example, the device displays advice such as, "Foods containing omega-3 fatty acids are beneficial for you. You seem to have been feeling stressed recently, so try meditating to relax."

[1777] Example 2: Health check reminder

[1778] The server schedules the user's next health check date for three months from now. If the user has recently reported stress, the server sends an earlier reminder message, such as "It's time for a health check. Please also check your recent stress level."

[1779] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1780] Step 1: User Login

[1781] User: The user opens the login screen and enters their "username" and "password."

[1782] Enter: "Username" and "Password"

[1783] Device: The device sends this information to the server via an HTTPS request.

[1784] Output: Credentials sent

[1785] Specific operation: Input form data from the terminal is converted into JSON format and sent to the server using a secure communication protocol.

[1786] Step 2: User authentication

[1787] Server: The server checks the received authentication information against the user data in its database.

[1788] Input: Received authentication information

[1789] Output: Authentication result (success or failure) and session key (if successful)

[1790] Specific operation: The server retrieves user information from the database using an SQL query and verifies the password. If authentication is successful, it generates a session key and returns it to the terminal as an HTTP response.

[1791] Step 3: Viewing the authentication results

[1792] Terminal: The terminal displays the authentication result received from the server to the user. If successful, the terminal transitions to the dashboard screen.

[1793] Input: Authentication result (success or failure) and session key (if successful)

[1794] Output: Dashboard screen or error message

[1795] Specific operation: The terminal analyzes the received authentication result, and if successful, redirects the user to the dashboard screen, and if unsuccessful, displays an error message.

[1796] Step 4: Enter your health information

[1797] User: The user enters information such as "health status," "diet," and "allergy information" on the "Enter Health Information" page in the dashboard.

[1798] Input: Health information such as "health condition," "diet," and "allergy information"

[1799] Terminal: The terminal converts the input information into JSON format and sends it to the server via an HTTPS request.

[1800] Output: Health information sent

[1801] Specific operation: The terminal receives the information entered by the user, converts it to JSON, and sends it to the server via a secure communication protocol.

[1802] Step 5: Save your health information

[1803] Server: The server stores the received health information in a database.

[1804] Input: Received health information

[1805] Output: Save completion notification

[1806] Specific operation: The server uses an SQL query to insert information into the database, checks whether the save is complete, and then returns a save completion message to the terminal.

[1807] Step 6: Information Analysis

[1808] Server: The server takes user input from a database and runs algorithms to evaluate foods and nutrients.

[1809] Input: Health information stored in a database

[1810] Output: Analysis results (list of suitable foods, nutrients, and supplements)

[1811] Specific operation: Using a Python script, data analysis is performed using Pandas and NumPy. As a result of the analysis, a list of foods, nutrients, and supplements suitable for the user is generated.

[1812] Step 7: Generate health advice

[1813] Server: The server generates health advice based on the analysis results and emotion data.

[1814] Input: Analysis results, emotion data

[1815] Output: Health advice

[1816] Specific operation: The emotion engine is used to analyze emotion data, adjust the analysis results based on the results, and generate appropriate health advice.

[1817] Step 8: Providing health advice

[1818] Terminal: The terminal displays the health advice received from the server to the user.

[1819] Enter: Health Advice

[1820] Output: User advice screen

[1821] Specific operation: The received health advice is displayed on the user's dashboard screen and notifications are provided as needed.

[1822] Step 9: Remind yourself to check your health regularly

[1823] Server: The server schedules the user's next health check and generates reminder messages based on the set interval.

[1824] Input: User's health information, interval settings

[1825] Output: Reminder message

[1826] Specific operation: Using a Cron job or similar, a reminder message is generated and sent to the device at the set time.

[1827] Step 10: Sending Reminder Messages

[1828] Device: The device will notify the user of reminder messages and encourage them to check their health.

[1829] Input: Reminder message

[1830] Output: Reminder notification

[1831] Specific operation: The device receives the reminder message and notifies the user via push notification or in-app notification.

[1832] These steps enable the system to optimize the user's health management and provide personalized advice that takes into account their emotional state.

[1833] (Application example 2)

[1834] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1835] Conventional health management systems provide health advice based on user-entered information, but they do not consider real-time recommendations based on purchasing behavior in physical stores. There is a need for a system that utilizes health information, including the user's emotional state, to provide appropriate food and nutrient recommendations in physical stores. It is also necessary to efficiently remind users to schedule their next health check.

[1836] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1837] In this invention, the server includes means for user authentication, means for collecting user-input information, means for analyzing the collected information, means for generating a list of appropriate foods, nutrients, and supplements based on the analysis results, means for evaluating the safety of processed foods and food additives, means for providing the generated list and evaluation information to the user, means for generating and providing health advice and preventive methods, means for reminding the user to take regular health checks, means for providing recommendations to the user using smart glasses in a physical store, and means for scheduling and reminding the user of the user's next health check. This allows the user to receive appropriate health recommendations in real time while making a purchase in the physical store, and also enables efficient reminders for the next health check.

[1838] "User authentication" is the process of verifying a user's identity using a username and password when accessing a system.

[1839] "Collecting user-input information" is the stage where the user inputs information such as health status, dietary habits, and allergies into the system.

[1840] "Information analysis" is the process of using algorithms to evaluate collected user-entered information and generate a list of appropriate foods and nutrients.

[1841] "List generation" is the stage where a list of foods, nutrients, and supplements suitable for the user is created based on the analysis results.

[1842] "Safety assessment" is an analytical process conducted to evaluate the safety of processed foods and food additives.

[1843] "Providing advice" is the process of providing health advice and preventive methods to the user based on the generated list and evaluation information.

[1844] "Remind" is the process of scheduling a user's next health check date and sending a timely reminder message.

[1845] "Recommendations in physical stores" refers to the use of smart glasses to recommend appropriate products and health information in real time to users in physical stores based on their purchasing behavior.

[1846] "Health check schedule setting" is a process of setting the date of the user's next health check and sending reminders based on that schedule.

[1847] The present invention provides a system for efficiently managing a user's health, and in particular provides real-time recommendations and health check reminders in physical stores. The specific operation of the system is described below.

[1848] First, let's explain user authentication. The user accesses the login screen and enters their "user name" and "password." The terminal sends the "user name" and "password" entered by the user to the server. The server compares the received authentication information with a database and performs user authentication. If authentication is successful, it generates a session key and returns it to the terminal. The terminal displays the authentication result to the user, and if successful, transitions to the dashboard screen.

[1849] Next, we will explain how to collect user-entered information. The user enters information such as "health status," "diet," and "allergy information" on the "Enter Health Information" page in the dashboard. The device sends the entered information to the server. The server stores the received information in a database. A notification that the information has been saved is returned to the device.

[1850] In the information analysis step, the server retrieves user input information from the database and runs algorithms to evaluate foods and nutrients. It generates a list of appropriate foods, nutrients, and supplements, and performs safety evaluations of processed foods and food additives. The analysis results and safety evaluation results are stored in the database.

[1851] When providing health advice, the server generates health advice based on the analysis results and safety assessment results. This advice also takes into account the emotion recognition results of the emotion engine. The device displays the health advice to the user. For example, if the user is feeling stressed, it also provides ways to alleviate that stress.

[1852] It also includes a function to schedule the user's next health check and generate a reminder message. The server sends the reminder message to the device based on the interval. The device notifies the user of the reminder message and encourages them to check their health.

[1853] We also explain real-time recommendations in physical stores. When a user walks around a store wearing smart glasses, the device requests recommendations from the server based on the user's location and emotional state. The server analyzes the received information and recommends appropriate products and activities. For example, if the user is feeling stressed, recommendations such as "green tea" and "dark chocolate" will be displayed.

[1854] The implementation of this system uses the following hardware and software:

[1855] Hardware: Smart glasses (e.g., smart glasses), cloud server (e.g., cloud server), terminal (e.g., PC or smartphone)

[1856] Software: Databases (e.g., MySQL, PostgreSQL, MongoDB), data analysis algorithms, emotion engines

[1857] As a concrete example, a user wearing smart glasses receives recommendations such as "green tea" or "dark chocolate" when selecting products in a physical store. At the same time, a reminder message is displayed saying, "Don't forget your next health check," since the user's next health check is approaching.

[1858] An example of a prompt to be input to the generative AI model is, "Write a Python program that analyzes the user's emotional state and recommends healthy foods and activities based on that. Also, include a function to remind them to come for their next health check."

[1859] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1860] Step 1: User authentication

[1861] Input: Username, Password

[1862] Specific operation: The user accesses the login screen and enters their username and password. The device sends the input information to the server.

[1863] Data processing: The server checks the received username and password against its database.

[1864] Output: If authentication is successful, the server generates a session key and returns it to the terminal. The terminal displays the authentication result to the user, and if successful, transitions to the dashboard screen.

[1865] Step 2: Collecting User-Input Information

[1866] Input: Health condition, dietary habits, allergy information

[1867] Specific operation: The user enters information on the "Enter Health Information" page in the dashboard. The device sends the entered information to the server.

[1868] Data processing: The server stores the received information in a database.

[1869] Output: The server returns a notification to the device that the save is complete.

[1870] Step 3: Information analysis

[1871] Input: User-entered information (health status, dietary habits, allergy information)

[1872] Specific operation: The server retrieves user input information from the database and runs algorithms to evaluate foods and nutrients.

[1873] Data calculation: The server runs the evaluation algorithm and generates a list of suitable foods, nutrients, and supplements.

[1874] Output: The analysis results and generated list are obtained. In addition, the safety assessment of processed foods and food additives is performed and the results are also obtained.

[1875] Step 4: Providing health advice

[1876] Input: Analysis results, generated list, safety assessment results, emotion recognition results by emotion engine

[1877] Specific operation: The server generates health advice based on the analysis results and safety assessment results, taking into account emotion recognition results.

[1878] Data calculation: Comprehensively evaluate the emotion recognition results obtained from the emotion engine and generate optimal health advice.

[1879] Output: The terminal displays the generated health advice to the user.

[1880] Step 5: Remind yourself to check your health regularly

[1881] Input: The user's next scheduled health check

[1882] Specific operation: The server generates reminder messages based on the set interval.

[1883] Data processing: Reminder messages are generated based on each user's health check interval.

[1884] Output: The server sends a remind message to the terminal, which notifies the user of the message.

[1885] Step 6: Real-time recommendations in-store

[1886] Input: User's location, emotional state

[1887] Specific operation: When a user walks around a store using smart glasses, the device requests the user's location information and emotional state from the server.

[1888] Data calculation: The server analyzes the received location information and emotional state and recommends appropriate products and activities.

[1889] Output: The device displays the recommendation results in real time on the user's smart glasses.

[1890] Step 7: Schedule your health checks

[1891] Input: User's health check schedule information

[1892] Specific operation: The server schedules the user's next health check.

[1893] Data processing: Schedule the next health check date and time based on the user's health data.

[1894] Output: The device sends a reminder message to the user based on the configured schedule information.

[1895] The above are the specific steps of the program processing.

[1896] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1897] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1898] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1899] [Fourth embodiment]

[1900] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1901] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1902] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1903] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1904] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1905] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1906] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1907] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1908] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1909] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1910] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1911] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1912] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1913] The present invention is a system for enabling users to efficiently manage their health, analyzing information input by the user and providing appropriate health advice. A specific operation method of the system will be described below.

[1914] User Authentication

[1915] User:

[1916] The user accesses the login screen and enters their "user name" and "password."

[1917] Device:

[1918] The terminal sends the "user name" and "password" entered by the user to the server.

[1919] server:

[1920] The server checks the received authentication information against a database, and if authentication is successful, generates a session key and returns the generated session key to the terminal.

[1921] Device:

[1922] The terminal notifies the user that the authentication was successful and displays the dashboard screen.

[1923] Collecting user-entered information

[1924] User:

[1925] Users go to the "Enter Health Information" page in the dashboard and enter information such as "health status," "diet," and "allergy information."

[1926] Device:

[1927] The terminal transmits the information entered by the user to the server.

[1928] server:

[1929] The server saves the received information in a database and returns a notification to the device that saving is complete.

[1930] Information analysis

[1931] server:

[1932] The server runs algorithms that generate lists of suitable foods, nutrients, and supplements based on user-entered information in the database, and also performs safety assessments of processed foods and food additives.

[1933] Providing health advice

[1934] server:

[1935] The server documents specific health advice and preventive measures based on the generated list and safety assessment results.

[1936] Device:

[1937] The terminal displays the health advice and prevention methods received from the server to the user.

[1938] Regular health check reminders

[1939] server:

[1940] The server registers the next health check date in the schedule based on the user's check interval and generates a reminder message.

[1941] Device:

[1942] The device notifies the user of reminder messages and encourages regular health checks.

[1943] Specific examples

[1944] As a concrete example, the following scenario will be described.

[1945] Example 1: Entering and Evaluating New Health Information

[1946] User:

[1947] After logging in, the user enters their "weight," "dietary details," and "allergy information."

[1948] Device:

[1949] The input information is sent to the server.

[1950] server:

[1951] The information is stored in a database, appropriate food and nutrient lists are generated, and processed food safety is assessed.

[1952] server:

[1953] Based on the generated list and the evaluation results, health advice is created and sent to the device.

[1954] Device:

[1955] Health advice such as "Foods containing omega-3 fatty acids are beneficial for you" is displayed.

[1956] Example 2: Health check reminder

[1957] server:

[1958] Set the user's next health check date to three months later.

[1959] server:

[1960] When the set date and time approaches, a reminder message will be sent to your device.

[1961] Device:

[1962] A reminder message is sent to the user saying, "It's time for a health check."

[1963] The system of the present invention allows users to easily and efficiently manage their own health, make appropriate food choices, and take preventative measures, thereby contributing to the prevention of health hazards.

[1964] The processing flow will be explained below.

[1965] Program processing steps

[1966] User Authentication

[1967] Step 1:

[1968] User: Enter your "username" and "password" on the login screen.

[1969] Step 2:

[1970] Terminal: Sends the entered authentication information to the server.

[1971] Step 3:

[1972] Server: Compares the received authentication information with a database and performs user authentication.

[1973] Step 4:

[1974] Server: If authentication is successful, generates a session key and returns it to the terminal.

[1975] Step 5:

[1976] Terminal: The authentication result is displayed to the user, and if successful, the user is taken to the dashboard screen.

[1977] Collecting user-entered information

[1978] Step 1:

[1979] User: Enter information such as "health condition," "diet," and "allergy information" on the "Enter Health Information" page in the dashboard.

[1980] Step 2:

[1981] Terminal: Sends the entered information to the server.

[1982] Step 3:

[1983] Server: Stores the received information in a database.

[1984] Step 4:

[1985] Server: Sends confirmation of save completion to the device.

[1986] Information analysis

[1987] Step 1:

[1988] Server: Retrieves user input information from the database.

[1989] Step 2:

[1990] Server: Runs the algorithms that evaluate foods and nutrients.

[1991] Step 3:

[1992] Server: Generates a list of suitable foods, nutrients, and supplements.

[1993] Step 4:

[1994] Server: Evaluates the safety of processed foods and food additives.

[1995] Step 5:

[1996] Server: Stores the analysis results and safety evaluation results in a database.

[1997] Providing health advice

[1998] Step 1:

[1999] Server: Generates health advice based on the analysis results and safety assessment results.

[2000] Step 2:

[2001] Server: Sends health advice to the device.

[2002] Step 3:

[2003] Terminal: displays health advice to the user.

[2004] Regular health check reminders

[2005] Step 1:

[2006] Server: Schedules the user's next health check.

[2007] Step 2:

[2008] Server: Generates reminder messages based on configured intervals.

[2009] Step 3:

[2010] Server: Sends reminder messages to the device.

[2011] Step 4:

[2012] Terminal: Notify the user of the reminder message.

[2013] Example 1

[2014] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2015] Conventional health management systems struggle to efficiently provide appropriate health advice that takes into account a user's health status, diet, and allergy information. They also lacked reminders for regular health checks, and did not provide sufficient support for users to continuously manage their health. Furthermore, some systems lacked session management and generative AI models, resulting in a poor user experience.

[2016] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[2017] In this invention, the server includes means for user authentication, means for collecting user-input information, means for analyzing the collected information, means for generating a list of appropriate foods, nutrients, and supplements based on the analysis results, means for evaluating the safety of processed foods and food additives, means for providing the generated list and evaluation information to the user, means for generating and providing health advice and preventive methods, means for reminding users to take regular health checks, means for generating and managing session keys, and means for creating health advice and reminder messages using a generative AI model, thereby enabling users to efficiently and continuously manage their own health.

[2018] "User authentication" is the process of verifying a user's identity when they access a system.

[2019] "User input information" refers to data such as health status, dietary habits, and allergy information that the user provides to the system.

[2020] "Means of analyzing information" refers to the method of analyzing and evaluating related data based on collected user-entered information.

[2021] The "means for generating a list of foods, nutrients, and supplements" is a method for selecting and listing foods, nutrients, and supplements suitable for the user based on the analysis results.

[2022] "Means for safety assessment" refers to the methods used to evaluate the safety of processed foods and food additives and reflect the results in the list.

[2023] The "means for providing to the user" refers to a method for conveying the generated list and rating information to the user.

[2024] The "means for generating and providing health advice and preventive measures" is a method for generating and providing specific health advice and preventive measures to the user based on the analysis results.

[2025] The "means for reminding users to check their health" is a method for generating and notifying reminder messages to encourage users to check their health regularly.

[2026] The "means for generating and managing a session key" is a method for generating and managing a session key for identifying a user during a session after user authentication has been successful.

[2027] A "generative AI model" is an artificial intelligence model used for natural language generation and data analysis, and an example is the GPT series.

[2028] The present invention is a system for enabling users to efficiently manage their health by analyzing input information from the user and providing appropriate health advice. Specific implementation and operation methods of the system are described below.

[2029] System configuration

[2030] The present invention consists of a user terminal, a server, and a database. The user terminal can be a PC, smartphone, tablet, etc. The server is a high-performance computer equipped with a database management system (e.g., MySQL) and analytical software (e.g., Python scripts). In addition, a generative AI model (e.g., GPT-4) is used for natural language generation and data analysis.

[2031] User Authentication

[2032] The user accesses the login screen using a terminal and enters their "user name" and "password." This authentication information is sent from the terminal to the server via a secure protocol (HTTPS). The server compares the received information with data in a database, and if authentication is successful, it generates a session key and returns it to the terminal. The terminal notifies the user that authentication was successful and displays the dashboard screen.

[2033] Collecting user-entered information

[2034] The user goes to the "Enter Health Information" page in the dashboard and enters information such as "health status," "diet," and "allergy information." This information is sent from the device to the server in JSON format. The server stores the received information in a database and notifies the device once it has been saved.

[2035] Information analysis

[2036] The server retrieves user information from the database and analyzes it using Python scripts. Based on the analysis results, it generates a list of appropriate foods, nutrients, and supplements. It also evaluates the safety of processed foods and food additives and lists the results.

[2037] Providing health advice

[2038] The server then documents specific health advice and preventative measures based on the generated list and safety assessment results. This process uses a generative AI model (GPT-4). The generated advice is sent to the device and displayed to the user. For example, advice such as "Foods containing omega-3 fatty acids are beneficial for you" is provided.

[2039] Regular health check reminders

[2040] The server schedules the next health check based on the user's check interval. When the scheduled date and time approaches, it uses a generative AI model to create a reminder message and sends it to the device. The device then notifies the user of this reminder message, encouraging them to perform regular health checks. For example, a message saying, "It's time for a health check."

[2041] Specific examples

[2042] Here is a specific example.

[2043] Example 1: After logging in, a user enters their weight, dietary details, and allergy information, and the device sends the information to the server. The server stores the information in a database, generates a list of appropriate foods and nutrients, and provides health advice.

[2044] Example 2: The server sets the user's next health check date three months from now, and when the set date and time approaches, it generates a reminder message and sends it to the device.

[2045] In this way, users can efficiently and continuously manage their own health.

[2046] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2047] Step 1:

[2048] User: The user accesses the login screen and enters their "username" and "password."

[2049] Enter: "Username" and "Password"

[2050] Output: Sends authentication information to the terminal

[2051] Specific behavior: The user completes the login screen and clicks the "Login" button.

[2052] Step 2:

[2053] Terminal: The terminal encrypts the "username" and "password" entered by the user and sends them to the server via a secure protocol (e.g., HTTPS).

[2054] Input: Encrypted "Username" and "Password"

[2055] Output: Sends authentication information to the server

[2056] Specific operation: The device protects the information entered using SSL / TLS encryption and sends it to the server as an HTTPS request.

[2057] Step 3:

[2058] Server: The server checks the received credentials against a database (e.g. MySQL) using a hashed password.

[2059] Input: Received authentication information

[2060] Output: Authentication result (success or failure)

[2061] Specific operation: The server compares the hash value of the received information with the user information stored in the database.

[2062] Step 4:

[2063] Server: If authentication is successful, the server generates a random session key and returns it to the device.

[2064] Input: Authentication success flag

[2065] Output: Session key

[2066] Specific operation: The server generates a session ID, temporarily stores it in a database, and sends it back to the device.

[2067] Step 5:

[2068] Terminal: The terminal notifies the user that authentication was successful and displays the dashboard screen.

[2069] Input: Session key

[2070] Output: Dashboard screen display

[2071] Specific behavior: The device saves the received session key and displays the dashboard to the user along with a successful login message.

[2072] Step 6:

[2073] User: The user goes to the "Enter Health Information" page in the dashboard and enters information such as "health status," "diet," and "allergy information."

[2074] Input: "Health status", "Diet", "Allergy information"

[2075] Output: Sends information to the terminal

[2076] What happens: A user fills in a form and clicks the "Submit" button.

[2077] Step 7:

[2078] Terminal: The terminal sends the information entered by the user to the server, using JSON format data.

[2079] Input: User input information (JSON format)

[2080] Output: Sends input information to the server

[2081] Specific operation: The device converts the input information into JSON format and sends it to the server via an HTTPS request.

[2082] Step 8:

[2083] Server: The server stores the received information in a database.

[2084] Input: User input information (JSON format)

[2085] Output: Save result (success or failure)

[2086] Specific operation: The server writes the received information to the database.

[2087] Step 9:

[2088] Server: The server returns a notification to the device that the save is complete.

[2089] Input: Save success flag

[2090] Output: Save completion notification

[2091] Specific behavior: The server confirms the success of the save and returns a notification to the device as an HTTPS response.

[2092] Step 10:

[2093] Server: The server retrieves the user information from the database and runs the analysis algorithm.

[2094] Input: User information

[2095] Output: Analysis results (food list, safety assessment)

[2096] What it does: The server runs a Python script to evaluate the list of suitable foods and nutrients and the safety of processed foods.

[2097] Step 11:

[2098] Server: The server uses generative AI models to document health advice and prevention methods.

[2099] Input: Analysis results

[2100] Output: Health advice and prevention methods (text)

[2101] Specific operation: The server runs a generative AI model (e.g., GPT-4) and generates advice in natural language based on the analysis results.

[2102] Step 12:

[2103] Server: The server sends the generated advice and prevention methods to the device.

[2104] Input: Health advice and prevention methods (text)

[2105] Output: Send advice to terminal

[2106] Specific operation: The server returns the generated text to the terminal as an HTTPS response.

[2107] Step 13:

[2108] Terminal: The terminal displays the health advice and prevention methods received from the server to the user.

[2109] Input: Advice received from the server

[2110] Output: Display advice to the user

[2111] Specific operation: The terminal displays the received information on the user screen in an appropriate format.

[2112] Step 14:

[2113] Server: The server schedules the next health check date based on the user's check interval.

[2114] Input: User check interval

[2115] Output: Next health check date

[2116] Specific operation: The server registers the next health check date in the schedule management system.

[2117] Step 15:

[2118] Server: When the set date and time approaches, the server uses a generative AI model to generate a reminder message.

[2119] Input: Next health check date

[2120] Output: Reminder message (text)

[2121] Specific operation: The server uses the generative AI model to generate appropriate reminder text.

[2122] Step 16:

[2123] Server: The server sends the generated remind message to the device.

[2124] Input: Reminder message (text)

[2125] Output: Send a reminder message to the device

[2126] Specific operation: The server sends the generated message to the terminal as an HTTPS response.

[2127] Step 17:

[2128] Device: The device will notify the user as a reminder message that it is time for a health check.

[2129] Input: Reminder message received from the server

[2130] Output: Notify the user

[2131] What happens: The device displays a reminder message to the user and notifies the user using the notification system.

[2132] (Application example 1)

[2133] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2134] Conventional health management systems make it difficult for users to select appropriate foods and nutrients based on their own health information. They also lacked a means to effectively recommend related products and services, making it difficult for users to make optimal purchasing decisions based on their health status. Furthermore, they lacked a mechanism to provide health advice while also encouraging actual purchasing behavior.

[2135] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[2136] In this invention, the server includes means for user authentication, means for collecting user-entered information, means for analyzing the collected information, means for recommending appropriate products and services based on the analysis results, means for evaluating the safety of processed products and ingredients, means for providing the generated list and evaluation information to the user, means for generating and providing health advice and preventive methods, means for reminding the user to take regular health checks, and means for displaying links to online shopping sites to facilitate purchases. This allows users to easily select optimal products and services based on their own health condition and efficiently manage their health.

[2137] "User authentication" is the process by which a user accesses a system using their authentication information (e.g., username and password).

[2138] "User-input information" refers to data such as health status, dietary habits, and allergy information that a user provides to the system.

[2139] "Information analysis" is data processing to recommend appropriate products and foods based on collected user-entered information.

[2140] "Product recommendation" is the process of presenting optimal products and services to users based on the results of information analysis.

[2141] "Ingredient safety evaluation" is a procedure for evaluating the safety of processed products and ingredients and providing that information to users.

[2142] "Providing a list" is a procedure for transmitting the generated list of products and services and evaluation information to users.

[2143] "Health advice" is a procedure that provides specific health management methods and preventative measures based on the user's health information.

[2144] "Remind" is a procedure that notifies the user when it is time for a regular health check and encourages them to carry out the check.

[2145] "Mail Order Link" is a procedure for generating and displaying a link that allows users to purchase recommended products or services.

[2146] This specification details a specific embodiment of a system for efficiently managing a user's health. The system collects and analyzes health information provided by the user, recommends appropriate products and nutrients, and provides links to online shopping sites to encourage users to make purchases.

[2147] System Overview

[2148] The system includes the following elements:

[2149] A means of user authentication

[2150] A means of collecting user input information

[2151] How we analyze the information we collect

[2152] A means of recommending appropriate products and services based on analysis results

[2153] A means of assessing the safety of processed products and ingredients

[2154] Means for providing generated list and rating information to a user

[2155] A means of generating and delivering health advice and prevention methods

[2156] A means of reminding people to check their health regularly

[2157] Displaying links to online shopping sites to make purchasing easier

[2158] Hardware and Software Configuration

[2159] Hardware

[2160] Smartphone: a device on which the user operates an interface

[2161] Server: Backend server that stores and processes data

[2162] software

[2163] Flask: A lightweight web framework built in Python

[2164] sqlite3: a local database management system

[2165] React: Used to build the front-end user interface

[2166] Data processing and calculation

[2167] User Authentication

[2168] The user enters their authentication information (username and password) and sends it to the server, which checks it against the database and, if authentication is successful, generates and returns a session key.

[2169] Collecting user-entered information

[2170] The user enters information about their health, diet, allergies, etc., and the device sends this information to the server, which then stores the received information in a database.

[2171] Information analysis

[2172] The server analyzes the user-entered information in the database and performs data calculations to recommend appropriate products, nutrients, and supplements. Using a generative AI model, it analyzes the data based on the prompt text and generates results.

[2173] Providing health advice

[2174] The server generates specific health advice and preventive measures based on the user's health information and sends them to the device, which then displays them to the user.

[2175] Reminders and shopping links

[2176] The server sets the date for the user's next health check and generates a reminder message. The device notifies the user of this and encourages regular health checks. The device also displays a link to purchase recommended products, allowing the user to easily access the online shopping site.

[2177] Specific examples

[2178] Example 1: Entering and Evaluating New Health Information

[2179] After logging in, users enter their health information (weight, dietary habits, and allergy information). The device sends the information to the server, which stores it in a database. The server uses a generative AI model to generate a list of appropriate foods and nutrients and evaluates the safety of processed foods. Based on the results, health advice and product recommendations are provided and notified to the user.

[2180] Example prompt sentence:

[2181] Recommend optimal foods and nutrients based on your health, diet, and allergies. Use the following information:

[2182] Health: Weight gain in the past week

[2183] Diet: Few vegetables in daily meals

[2184] Allergy Information: Nut allergy

[2185] Example 2: Displaying online shopping links and encouraging purchases

[2186] The server creates a list of recommended products based on the analysis results and generates a link to the online shopping site. The device displays this to the user, who can click on the product link to access the online shopping site and make a purchase.

[2187] As described above, the system of the present invention allows users to easily select optimal products and services based on their own health condition, and efficiently manage their health.

[2188] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2189] Step 1:

[2190] When a user opens the app, a login screen appears. The user enters their authentication information (username and password). The entered information is sent from the device to the server.

[2191] Input: Username, Password

[2192] Output: Sending authentication information to the server

[2193] Step 2:

[2194] The server checks the received authentication information against a database, and if authentication is successful, generates a session key and returns the generated session key to the terminal.

[2195] Input: Credentials

[2196] Output: Session key, authentication result

[2197] Step 3:

[2198] The device notifies the user that authentication was successful and displays the dashboard screen. The user then moves to the "Enter Health Information" page to enter data such as health status, dietary habits, and allergy information.

[2199] Input: Session key, user information

[2200] Output: View dashboard

[2201] Step 4:

[2202] After entering health information, the user sends the information from the device to the server, which stores the information in a database and returns a notification to the device that the information has been saved.

[2203] Input: Health information (e.g., health condition, diet, allergy information)

[2204] Output: Saving to database, notification of saving completion

[2205] Step 5:

[2206] The server analyzes the user-entered information stored in the database and uses a generative AI model to generate a list of appropriate foods and nutrients based on the prompt.

[2207] Input: User's health information

[2208] Output: List of foods and nutrients

[2209] Step 6:

[2210] The server uses the generated list and other data to evaluate the safety of processed products and ingredients, and then compiles the evaluation results into written advice for the user.

[2211] Input: list of foods and nutrients, generative AI model

[2212] Output: Safety assessment, health advice

[2213] Step 7:

[2214] The server sends the generated advice to the terminal, which displays it to the user. The terminal then displays further recommended information on suitable products and services, as well as links to online shopping sites where the products can be purchased.

[2215] Input: Health advice, assessment results

[2216] Output: Display advice, display mail order link

[2217] Step 8:

[2218] When a user clicks on a shopping link, a browser is launched and the specified shopping site is opened, allowing the user to easily purchase the product.

[2219] Input: Click on the online shopping link

[2220] Output: Display of online shopping site, facilitating product purchase

[2221] Step 9:

[2222] The server sets the date of the user's next health check and generates a reminder message. When the set date and time approaches, the reminder message is sent to the device. The device then notifies the user of the reminder message.

[2223] Input: User health check interval

[2224] Output: Generate reminder message, notification

[2225] Through the above processing steps, the system of the present invention enables users to efficiently manage their health and conveniently purchase related products and services.

[2226] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2227] The present invention is a system for efficiently managing a user's health, and in particular, recognizes the user's emotions and provides health advice and reminders based on those emotions. The specific operation of the system is described below.

[2228] User Authentication

[2229] User:

[2230] The user accesses the login screen and enters their "user name" and "password."

[2231] Device:

[2232] The terminal sends the "user name" and "password" entered by the user to the server.

[2233] server:

[2234] The server compares the received authentication information with a database to authenticate the user. If authentication is successful, it generates a session key and returns it to the terminal.

[2235] Device:

[2236] The terminal displays the authentication result to the user, and if successful, transitions to the dashboard screen.

[2237] Collecting user-entered information

[2238] User:

[2239] Users enter information such as their health status, diet, and allergy information on the "Enter Health Information" page within the dashboard.

[2240] Device:

[2241] The entered information is sent to the server.

[2242] server:

[2243] The received information is saved in the database, and a notification that saving is complete is returned to the device.

[2244] Information analysis

[2245] server:

[2246] It takes user input from the database and runs algorithms to evaluate foods and nutrients, generates lists of suitable foods, nutrients, and supplements, and evaluates the safety of processed foods and food additives.

[2247] server:

[2248] The analysis results and safety evaluation results are stored in a database.

[2249] Providing health advice

[2250] server:

[2251] Health advice is generated based on the analysis results and safety assessment results, taking into account emotion recognition results from the emotion engine.

[2252] Device:

[2253] Health advice is displayed to the user. For example, if the user is feeling stressed, it also provides ways to alleviate the stress.

[2254] Regular health check reminders

[2255] server:

[2256] Schedule the user's next health check. Generate reminder messages based on the interval you set.

[2257] server:

[2258] Send a reminder message to your device.

[2259] Device:

[2260] Reminder messages are sent to users to encourage them to check their health.

[2261] Emotion Engine Operation

[2262] User:

[2263] Emotions are analyzed from video, audio, and text information entered or uploaded by the user.

[2264] Device:

[2265] The emotion data is sent to the server.

[2266] server:

[2267] The emotion engine analyzes the transmitted data and recognizes the user's emotions. The recognition results are stored in a database and used to generate health advice.

[2268] Specific examples

[2269] Example 1: Entering and Evaluating New Health Information

[2270] User:

[2271] After logging in, users enter their weight, dietary information, and allergy information. They also enter or upload information that indicates their current emotional state.

[2272] Device:

[2273] The input information and emotion data are sent to the server.

[2274] server:

[2275] The information is stored in a database and a list of appropriate foods and nutrients is generated. If the user is feeling stressed, it will recommend foods and activities that will help relieve stress.

[2276] Device:

[2277] The advice displayed is, "Foods containing omega-3 fatty acids are beneficial for you. You seem to have been feeling stressed lately, so try meditating to help you relax."

[2278] Example 2: Health check reminder

[2279] server:

[2280] Set the user's next health check date three months from now. If the user has recently reported stress, set an earlier reminder message.

[2281] server:

[2282] When the set date and time approaches, a reminder message will be sent to your device.

[2283] Device:

[2284] It notifies you, "It's time for a health check. Let's also check your recent stress level."

[2285] The system of the present invention supports users in optimal health management based on their own health and emotional state. By combining it with an emotion engine, it becomes possible to provide more personalized health advice, which is of great help to users in improving their health and preventing disease.

[2286] The processing flow will be explained below.

[2287] Program processing steps

[2288] User Authentication

[2289] Step 1:

[2290] User: Enter your "username" and "password" on the login screen.

[2291] Step 2:

[2292] Terminal: Sends the entered authentication information to the server.

[2293] Step 3:

[2294] Server: Compares the received authentication information with a database and performs user authentication.

[2295] Step 4:

[2296] Server: If authentication is successful, generates a session key and returns it to the terminal.

[2297] Step 5:

[2298] Terminal: The authentication result is displayed to the user, and if successful, the user is taken to the dashboard screen.

[2299] Collecting user-entered information

[2300] Step 1:

[2301] User: Enter information such as "health condition," "diet," and "allergy information" on the "Enter Health Information" page in the dashboard.

[2302] Step 2:

[2303] Terminal: Sends the entered information to the server.

[2304] Step 3:

[2305] Server: Stores the received information in a database.

[2306] Step 4:

[2307] Server: Sends confirmation of save completion to the device.

[2308] Information analysis

[2309] Step 1:

[2310] Server: Retrieves user input information from the database.

[2311] Step 2:

[2312] Server: Runs the algorithms that evaluate foods and nutrients.

[2313] Step 3:

[2314] Server: Generates a list of suitable foods, nutrients, and supplements.

[2315] Step 4:

[2316] Server: Evaluates the safety of processed foods and food additives.

[2317] Step 5:

[2318] Server: Stores the analysis results and safety evaluation results in a database.

[2319] Providing health advice

[2320] Step 1:

[2321] Server: Generates health advice based on the analysis results and safety assessment results, taking into account emotion recognition results from the emotion engine.

[2322] Step 2:

[2323] Server: Sends health advice to the device.

[2324] Step 3:

[2325] Terminal: displays health advice to the user.

[2326] Regular health check reminders

[2327] Step 1:

[2328] Server: Schedules the user's next health check.

[2329] Step 2:

[2330] Server: Generates reminder messages based on configured intervals.

[2331] Step 3:

[2332] Server: Sends reminder messages to the device.

[2333] Step 4:

[2334] Terminal: Notify the user of the reminder message.

[2335] Emotion Engine Operation

[2336] Step 1:

[2337] User: Analyze emotions from video, audio, and text information you input or upload.

[2338] Step 2:

[2339] Terminal: Sends emotion data to the server.

[2340] Step 3:

[2341] Server: The emotion engine analyzes the transmitted data and recognizes the user's emotion.

[2342] Step 4:

[2343] Server: Stores emotion recognition results in a database and uses them to generate health advice.

[2344] Specific examples

[2345] Example 1: Entering and Evaluating New Health Information

[2346] Step 1:

[2347] User: After logging in, the user enters their weight, dietary information, and allergy information. They also enter or upload information that indicates their current emotional state.

[2348] Step 2:

[2349] Terminal: Sends input information and emotion data to the server.

[2350] Step 3:

[2351] Server: Stores the information in a database.

[2352] Step 4:

[2353] Server: Generates a list of appropriate foods and nutrients. If the user is feeling stressed, it recommends foods and activities that are good for stress relief.

[2354] Step 5:

[2355] Device: The generated list and the evaluation results are notified to the user. For example, advice such as "Foods containing omega-3 fatty acids are beneficial for you. You seem to have been feeling stressed lately, so try meditating to relax." is displayed.

[2356] Example 2: Health check reminder

[2357] Step 1:

[2358] Server: Set the user's next health check date to three months from now. If the user has recently reported stress, set an earlier reminder message.

[2359] Step 2:

[2360] Server: Generates a reminder message when the set date and time approaches.

[2361] Step 3:

[2362] Server: Sends reminder messages to the device.

[2363] Step 4:

[2364] Device: A reminder message is sent to the user saying, "It's time for a health check. Check your recent stress level."

[2365] Example 2

[2366] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2367] In modern society, users tend to neglect their health and emotional management in their busy daily lives. As a result, health problems and stress that are often overlooked can accumulate, potentially leading to serious health problems. Furthermore, fluctuations in emotional states often have a direct impact on health, creating a need for health advice that takes this into account. However, existing systems lack the ability to recognize a user's specific emotional state and provide appropriate advice based on that. Therefore, there is a need for a system that can comprehensively manage a user's health and emotional states and provide more personalized health advice.

[2368] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for user authentication, means for collecting user-input information, means for analyzing the collected information, means for generating a list of appropriate foods, nutrients, and supplements based on the analysis results, means for evaluating the safety of processed foods and food additives, means for providing the generated list and evaluation information to the user, means for generating and providing health advice and preventive measures, means for collecting and analyzing emotional data, means for adjusting health advice based on the collected emotional data, and means for reminding users to take regular health checks. This makes it possible to comprehensively manage the user's health and emotional states and provide health advice and regular reminders that are optimized for each individual user.

[2369] "Means for user authentication" is the process by which a user enters their "user name" and "password" and verifies the user's identity by checking them against a database.

[2370] "Means for collecting user-input information" refers to the process by which users provide personal information such as "health status," "dietary habits," and "allergy information" to the system, and this information is received and stored.

[2371] "Means for analyzing collected information" refers to the process by which the system processes collected user data using algorithms and analytical software to find the necessary insights and patterns.

[2372] The "means for generating a list of appropriate foods, nutrients, and supplements" is a process for listing optimal foods, nutrients, and supplements based on the user's health condition.

[2373] "Means for evaluating the safety of processed foods and food additives" refers to a process for evaluating the safety of processed foods and food additives consumed by users and providing the results.

[2374] The "means for providing the generated list and evaluation information to the user" is the process of providing the analyzed data and generated list in a format that is accessible to the user.

[2375] "Means for generating and providing health advice and prevention methods" refers to the process of creating and providing accurate health advice and guidance for disease prevention to the user based on the user's health condition and analysis data.

[2376] "Means for collecting and analyzing emotional data" refers to the process of identifying emotions from the user's video, audio, and text information and analyzing that data.

[2377] "Means for tailoring health advice based on collected emotional data" refers to a process for individually tailoring health advice content depending on the user's emotional state.

[2378] The "means for providing periodic health check reminders" is a process that notifies the user of the need for a health check based on set time intervals or conditions.

[2379] The present invention is a system for efficiently managing a user's health, which takes into account not only the user's health condition but also their emotional state to provide more personalized health advice and reminder functions. Specific embodiments for implementing the present invention will be described below.

[2380] Hardware and Software

[2381] This system is configured using the following hardware and software:

[2382] 1. Server: A high-performance computer or cloud-based computing resource (e.g., Amazon Web Services or Google Cloud Platform)

[2383] 2. Device: The smartphone, tablet, or PC used by the user

[2384] 3. Database: Relational database management system (e.g., MySQL, PostgreSQL)

[2385] 4. Sentiment Analysis Engine: Emotion recognition services such as Microsoft Azure Cognitive Services

[2386] 5. Analysis software: Python scripts, data analysis libraries such as Pandas and NumPy

[2387] 6. Communication Protocol: Secure data transmission and reception using HTTPS

[2388] User Authentication

[2389] The user enters their "user name" and "password" on the login screen. The device sends this information to the server. The server compares it with the database, and if authentication is successful, generates a session key and returns it to the device. The device displays the authentication result to the user, and if successful, transitions to the dashboard screen.

[2390] Collecting user-entered information

[2391] The user enters information such as "health status," "diet," and "allergy information" on the "Enter Health Information" page within the dashboard. The device sends this information to the server, which then stores it in a database. Once the information has been saved, a notification is returned to the device.

[2392] Information analysis

[2393] The server retrieves user input from the database and runs algorithms to evaluate foods and nutrients. For example, it analyzes the data using Python's Pandas and NumPy. It generates necessary nutrients and a recommended food list, and also evaluates the safety of processed foods and food additives. These results are then stored in a database.

[2394] Providing health advice

[2395] Based on the analysis results, the server uses an emotion engine to generate health advice taking into account the user's emotional data. The generated advice is sent to the device and displayed to the user. For example, if the user is feeling stressed, the server also provides ways to alleviate that stress.

[2396] Regular health check reminders

[2397] The server schedules the user's next health check and generates a reminder message based on the interval, which is then sent to the terminal, which then notifies the user.

[2398] Emotion Engine Operation

[2399] Users input or upload their own video, audio, and text information, which is used for emotion analysis. The device sends the emotion data to the server, where it is analyzed by the server's emotion engine. The analysis results are stored in a database and used to generate health advice.

[2400] Specific examples

[2401] Example 1: Entering and Evaluating New Health Information

[2402] After logging in, users enter their weight, dietary information, and allergy information, and upload information indicating their current emotional state. The device sends this information to a server, which stores it in a database and generates an appropriate food and nutrient list. For example, the device displays advice such as, "Foods containing omega-3 fatty acids are beneficial for you. You seem to have been feeling stressed recently, so try meditating to relax."

[2403] Example 2: Health check reminder

[2404] The server schedules the user's next health check date for three months from now. If the user has recently reported stress, the server sends an earlier reminder message, such as "It's time for a health check. Please also check your recent stress level."

[2405] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2406] Step 1: User Login

[2407] User: The user opens the login screen and enters their "username" and "password."

[2408] Enter: "Username" and "Password"

[2409] Device: The device sends this information to the server via an HTTPS request.

[2410] Output: Credentials sent

[2411] Specific operation: Input form data from the terminal is converted into JSON format and sent to the server using a secure communication protocol.

[2412] Step 2: User authentication

[2413] Server: The server checks the received authentication information against the user data in its database.

[2414] Input: Received authentication information

[2415] Output: Authentication result (success or failure) and session key (if successful)

[2416] Specific operation: The server retrieves user information from the database using an SQL query and verifies the password. If authentication is successful, it generates a session key and returns it to the terminal as an HTTP response.

[2417] Step 3: Viewing the authentication results

[2418] Terminal: The terminal displays the authentication result received from the server to the user. If successful, the terminal transitions to the dashboard screen.

[2419] Input: Authentication result (success or failure) and session key (if successful)

[2420] Output: Dashboard screen or error message

[2421] Specific operation: The terminal analyzes the received authentication result, and if successful, redirects the user to the dashboard screen, and if unsuccessful, displays an error message.

[2422] Step 4: Enter your health information

[2423] User: The user enters information such as "health status," "diet," and "allergy information" on the "Enter Health Information" page in the dashboard.

[2424] Input: Health information such as "health condition," "diet," and "allergy information"

[2425] Terminal: The terminal converts the input information into JSON format and sends it to the server via an HTTPS request.

[2426] Output: Health information sent

[2427] Specific operation: The terminal receives the information entered by the user, converts it to JSON, and sends it to the server via a secure communication protocol.

[2428] Step 5: Save your health information

[2429] Server: The server stores the received health information in a database.

[2430] Input: Received health information

[2431] Output: Save completion notification

[2432] Specific operation: The server uses an SQL query to insert information into the database, checks whether the save is complete, and then returns a save completion message to the terminal.

[2433] Step 6: Information Analysis

[2434] Server: The server takes user input from a database and runs algorithms to evaluate foods and nutrients.

[2435] Input: Health information stored in a database

[2436] Output: Analysis results (list of suitable foods, nutrients, and supplements)

[2437] Specific operation: Using a Python script, data analysis is performed using Pandas and NumPy. As a result of the analysis, a list of foods, nutrients, and supplements suitable for the user is generated.

[2438] Step 7: Generate health advice

[2439] Server: The server generates health advice based on the analysis results and emotion data.

[2440] Input: Analysis results, emotion data

[2441] Output: Health advice

[2442] Specific operation: The emotion engine is used to analyze emotion data, adjust the analysis results based on the results, and generate appropriate health advice.

[2443] Step 8: Providing health advice

[2444] Terminal: The terminal displays the health advice received from the server to the user.

[2445] Enter: Health Advice

[2446] Output: User advice screen

[2447] Specific operation: The received health advice is displayed on the user's dashboard screen and notifications are provided as needed.

[2448] Step 9: Remind yourself to check your health regularly

[2449] Server: The server schedules the user's next health check and generates reminder messages based on the set interval.

[2450] Input: User's health information, interval settings

[2451] Output: Reminder message

[2452] Specific operation: Using a Cron job or similar, a reminder message is generated and sent to the device at the set time.

[2453] Step 10: Sending Reminder Messages

[2454] Device: The device will notify the user of reminder messages and encourage them to check their health.

[2455] Input: Reminder message

[2456] Output: Reminder notification

[2457] Specific operation: The device receives the reminder message and notifies the user via push notification or in-app notification.

[2458] These steps enable the system to optimize the user's health management and provide personalized advice that takes into account their emotional state.

[2459] (Application example 2)

[2460] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2461] Conventional health management systems provide health advice based on user-entered information, but they do not consider real-time recommendations based on purchasing behavior in physical stores. There is a need for a system that utilizes health information, including the user's emotional state, to provide appropriate food and nutrient recommendations in physical stores. It is also necessary to efficiently remind users to schedule their next health check.

[2462] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2463] In this invention, the server includes means for user authentication, means for collecting user-input information, means for analyzing the collected information, means for generating a list of appropriate foods, nutrients, and supplements based on the analysis results, means for evaluating the safety of processed foods and food additives, means for providing the generated list and evaluation information to the user, means for generating and providing health advice and preventive methods, means for reminding the user to take regular health checks, means for providing recommendations to the user using smart glasses in a physical store, and means for scheduling and reminding the user of the user's next health check. This allows the user to receive appropriate health recommendations in real time while making a purchase in the physical store, and also enables efficient reminders for the next health check.

[2464] "User authentication" is the process of verifying a user's identity using a username and password when accessing a system.

[2465] "Collecting user-input information" is the stage where the user inputs information such as health status, dietary habits, and allergies into the system.

[2466] "Information analysis" is the process of using algorithms to evaluate collected user-entered information and generate a list of appropriate foods and nutrients.

[2467] "List generation" is the stage where a list of foods, nutrients, and supplements suitable for the user is created based on the analysis results.

[2468] "Safety assessment" is an analytical process conducted to evaluate the safety of processed foods and food additives.

[2469] "Providing advice" is the process of providing health advice and preventive methods to the user based on the generated list and evaluation information.

[2470] "Remind" is the process of scheduling a user's next health check date and sending a timely reminder message.

[2471] "Recommendations in physical stores" refers to the use of smart glasses to recommend appropriate products and health information in real time to users in physical stores based on their purchasing behavior.

[2472] "Health check schedule setting" is a process of setting the date of the user's next health check and sending reminders based on that schedule.

[2473] The present invention provides a system for efficiently managing a user's health, and in particular provides real-time recommendations and health check reminders in physical stores. The specific operation of the system is described below.

[2474] First, let's explain user authentication. The user accesses the login screen and enters their "user name" and "password." The terminal sends the "user name" and "password" entered by the user to the server. The server compares the received authentication information with a database and performs user authentication. If authentication is successful, it generates a session key and returns it to the terminal. The terminal displays the authentication result to the user, and if successful, transitions to the dashboard screen.

[2475] Next, we will explain how to collect user-entered information. The user enters information such as "health status," "diet," and "allergy information" on the "Enter Health Information" page in the dashboard. The device sends the entered information to the server. The server stores the received information in a database. A notification that the information has been saved is returned to the device.

[2476] In the information analysis step, the server retrieves user input information from the database and runs algorithms to evaluate foods and nutrients. It generates a list of appropriate foods, nutrients, and supplements, and performs safety evaluations of processed foods and food additives. The analysis results and safety evaluation results are stored in the database.

[2477] When providing health advice, the server generates health advice based on the analysis results and safety assessment results. This advice also takes into account the emotion recognition results of the emotion engine. The device displays the health advice to the user. For example, if the user is feeling stressed, it also provides ways to alleviate that stress.

[2478] It also includes a function to schedule the user's next health check and generate a reminder message. The server sends the reminder message to the device based on the interval. The device notifies the user of the reminder message and encourages them to check their health.

[2479] We also explain real-time recommendations in physical stores. When a user walks around a store wearing smart glasses, the device requests recommendations from the server based on the user's location and emotional state. The server analyzes the received information and recommends appropriate products and activities. For example, if the user is feeling stressed, recommendations such as "green tea" and "dark chocolate" will be displayed.

[2480] The implementation of this system uses the following hardware and software:

[2481] Hardware: Smart glasses (e.g., smart glasses), cloud server (e.g., cloud server), terminal (e.g., PC or smartphone)

[2482] Software: Databases (e.g., MySQL, PostgreSQL, MongoDB), data analysis algorithms, emotion engines

[2483] As a concrete example, a user wearing smart glasses receives recommendations such as "green tea" or "dark chocolate" when selecting products in a physical store. At the same time, a reminder message is displayed saying, "Don't forget your next health check," since the user's next health check is approaching.

[2484] An example of a prompt to be input to the generative AI model is, "Write a Python program that analyzes the user's emotional state and recommends healthy foods and activities based on that. Also, include a function to remind them to come for their next health check."

[2485] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2486] Step 1: User authentication

[2487] Input: Username, Password

[2488] Specific operation: The user accesses the login screen and enters their username and password. The device sends the input information to the server.

[2489] Data processing: The server checks the received username and password against its database.

[2490] Output: If authentication is successful, the server generates a session key and returns it to the terminal. The terminal displays the authentication result to the user, and if successful, transitions to the dashboard screen.

[2491] Step 2: Collecting User-Input Information

[2492] Input: Health condition, dietary habits, allergy information

[2493] Specific operation: The user enters information on the "Enter Health Information" page in the dashboard. The device sends the entered information to the server.

[2494] Data processing: The server stores the received information in a database.

[2495] Output: The server returns a notification to the device that the save is complete.

[2496] Step 3: Information analysis

[2497] Input: User-entered information (health status, dietary habits, allergy information)

[2498] Specific operation: The server retrieves user input information from the database and runs algorithms to evaluate foods and nutrients.

[2499] Data calculation: The server runs the evaluation algorithm and generates a list of suitable foods, nutrients, and supplements.

[2500] Output: The analysis results and generated list are obtained. In addition, the safety assessment of processed foods and food additives is performed and the results are also obtained.

[2501] Step 4: Providing health advice

[2502] Input: Analysis results, generated list, safety assessment results, emotion recognition results by emotion engine

[2503] Specific operation: The server generates health advice based on the analysis results and safety assessment results, taking into account emotion recognition results.

[2504] Data calculation: Comprehensively evaluate the emotion recognition results obtained from the emotion engine and generate optimal health advice.

[2505] Output: The terminal displays the generated health advice to the user.

[2506] Step 5: Remind yourself to check your health regularly

[2507] Input: The user's next scheduled health check

[2508] Specific operation: The server generates reminder messages based on the set interval.

[2509] Data processing: Reminder messages are generated based on each user's health check interval.

[2510] Output: The server sends a remind message to the terminal, which notifies the user of the message.

[2511] Step 6: Real-time recommendations in-store

[2512] Input: User's location, emotional state

[2513] Specific operation: When a user walks around a store using smart glasses, the device requests the user's location information and emotional state from the server.

[2514] Data calculation: The server analyzes the received location information and emotional state and recommends appropriate products and activities.

[2515] Output: The device displays the recommendation results in real time on the user's smart glasses.

[2516] Step 7: Schedule your health checks

[2517] Input: User's health check schedule information

[2518] Specific operation: The server schedules the user's next health check.

[2519] Data processing: Schedule the next health check date and time based on the user's health data.

[2520] Output: The device sends a reminder message to the user based on the configured schedule information.

[2521] The above are the specific steps of the program processing.

[2522] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2523] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2524] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2525] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2526] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2527] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2528] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2529] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2530] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2531] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2532] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2533] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2534] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2535] 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.

[2536] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2537] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2538] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2539] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2540] Furthermore, the hard...

Claims

1. means for performing user authentication; means for collecting user input information; a means for analyzing the collected information; and A means of generating a list of appropriate foods, nutrients, and supplements based on the analysis results; A means of assessing the safety of processed foods and food additives; means for providing the generated list and rating information to a user; means for generating and providing health advice and prevention methods; A means of reminding people to check their health regularly, A system including:

2. 2. The system of claim 1, wherein the user input information includes health status, dietary habits, and allergy information.

3. 2. The system according to claim 1, wherein the reminder for a periodic health check is based on a check interval set for each user.

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