system

Abstract

We provide the system. [Solution] Information acquisition means for collecting personal biometric information, A data analysis means for analyzing the aforementioned biological information, A plan generation means that generates individual health management plans based on the aforementioned data analysis, A notification means for presenting the generated health management plan, A system that includes this.

Description

【Technical Field】 , , 【0004】 , , , 【0005】 , , , , 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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 Application Laid-Open No. 2022-18028 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In modern society, personal health management is complex and difficult. Especially for people with chronic diseases, the unified management of daily health data and continuous health monitoring are issues. Furthermore, it is required that individuals can easily grasp their health status and independently select appropriate lifestyle habits without relying on medical institutions. However, current technologies lack effective means to achieve such individual health management. 【Means for Solving the Problems】 <​To solve these problems, the present invention provides information acquisition means and data analysis means for collecting and analyzing personal biometric information. Furthermore, it provides a system that includes a plan generation means for generating an individualized health management plan based on the analysis results, and a notification means for notifying the user of the generated plan. This system supports individualized health management by continuously monitoring the user's health data in real time using wearable devices and mobile communication devices, and warning the user using an anomaly detection function as needed. 【0006】 "Information acquisition means" refers to a device or system that has the function of collecting an individual's biometric information. 【0007】 A "data analysis tool" is a system that has the function of analyzing collected biological information to clarify health status and trends. 【0008】 A "plan generation means" is a device or program that has the function of automatically generating individual health management plans based on the results of data analysis. 【0009】 "Notification means" refers to means for providing the generated health management plan to the user, and includes the function of sending advice and warnings via terminals or other communication devices. 【0010】 A "monitoring system" is a system that has the function of continuously observing biological information and detecting abnormalities at an early stage. 【0011】 The "alert function" is a feature that warns the user if an abnormality is detected during monitoring of biometric information. 【0012】 A "wearable device" is an electronic device that can acquire biometric information when worn by a user. 【0013】 A "mobile communication device" is a portable electronic device that can transmit a user's biometric information to an external device. [Brief explanation of the drawing] 【0014】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention] 【0015】 Next, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0016】 First, the terms used in the following description will be explained. 【0017】 In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0018】 In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0019】 In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like. 【0020】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0021】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0022】 [First Embodiment] 【0023】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0024】 As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. 【0025】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0026】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0027】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0028】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0029】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0030】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0031】 As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30. 【0032】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0033】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0034】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0035】 This invention is a system for effectively managing an individual's health, and includes a process for collecting and analyzing a user's biometric information in real time using wearable devices and communication equipment. The following describes embodiments for implementing this system. 【0036】 First, the device collects biometric information such as heart rate, steps taken, and sleep patterns from the wearable device worn by the user. For example, using a smartwatch, it can track the total number of steps taken in a day, activity level, and heart rate variability. This data is transmitted to a smartphone via Bluetooth or Wi-Fi. 【0037】 Next, the device securely encrypts the collected data and sends it to a server in the cloud. The server analyzes the received biometric information using data analysis tools. Here, algorithms are used to identify normal patterns and signs of abnormalities, and a model is created of the health status of each individual user. 【0038】 Based on the analysis results, the server uses a plan generation mechanism to create a health management plan tailored to the user. For example, if the user is not getting enough exercise, the server might suggest walking three times a week and advise increasing protein intake in terms of diet. 【0039】 The generated health management plan is sent from the server to the user's smartphone via a notification system. This allows the user to receive specific advice for maintaining and improving their daily health. In addition, if an abnormality is detected, the server will quickly issue an alert and prompt the user to take appropriate action. 【0040】 Thus, the present invention enables easy and effective management of users' health by providing a consistent service from the acquisition of biometric information to the provision of health plans. 【0041】 The following describes the processing flow. 【0042】 Step 1: 【0043】 The device acquires the user's biometric information from the wearable device. This includes the number of steps the user takes in a day, heart rate during exercise, and activity data during sleep. The data is periodically transmitted to the device via Bluetooth or Wi-Fi. 【0044】 Step 2: 【0045】 The device stores the acquired biometric information in a database and encrypts it to maintain data integrity. The data is then securely uploaded to a server via the internet. 【0046】 Step 3: 【0047】 The server applies AI algorithms to analyze the received data. By comparing it with past data, it identifies normal and abnormal patterns and analyzes the user's health status and lifestyle. 【0048】 Step 4: 【0049】 The server generates a health management plan based on the analysis results. This plan includes specific suggestions regarding the type and frequency of exercise, ways to improve diet, and appropriate sleep patterns. 【0050】 Step 5: 【0051】 The server sends notifications to the user's device based on the generated health management plan and analysis results. This allows the user to receive specific advice on maintaining and improving their health in their daily life. 【0052】 Step 6: 【0053】 The server monitors the data using a continuous monitoring function and immediately sends an alert to the user if an anomaly is detected. This alert allows the user to quickly address the anomaly. 【0054】 (Example 1) 【0055】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0056】 Personal health management in modern society is becoming increasingly complex due to diverse lifestyles and environmental factors. Conventional health management systems suffer from insufficient real-time collection and analysis of biometric information, making it difficult to provide users with optimal health management plans. Furthermore, they struggle to respond quickly in the event of an abnormality. 【0057】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0058】 In this invention, the server includes information acquisition means for acquiring an individual's biometric information in real time; data transmission means for encrypting the biometric information and transmitting it via a communication network; data analysis means for decrypting and analyzing the biometric information and modeling the health status using a pattern recognition algorithm; plan generation means for generating an individual health management plan using a generated AI model based on the analyzed data; and notification means for notifying the user of the generated health management plan via a mobile communication device. This enables real-time collection and analysis of biometric information, rapid provision of personalized health management plans, and immediate alert generation in case of abnormalities. 【0059】 "Biometric information" refers to numerical values ​​and patterns that indicate the user's physical condition, including information such as heart rate, steps taken, and sleep patterns. 【0060】 "Information acquisition means" refers to devices and methods for collecting biometric information from users in real time, and includes wearable devices and sensors. 【0061】 "Data transmission means" refers to a technology or device that encrypts collected biometric information and transmits it to other devices or cloud servers via a communication network. 【0062】 "Data analysis means" refers to the process or technology of decoding received biometric information and modeling health status using a specific algorithm. 【0063】 "Plan generation means" refers to a method or system for creating individual health management plans using a generated AI model based on data analysis results. 【0064】 "Notification means" refers to a method or device for presenting generated health management plans and alerts in case of abnormalities to the user's device. 【0065】 The "alert function" is a mechanism that quickly alerts the user when an anomaly is detected during biometric information monitoring. 【0066】 A "wearable data collection device" is a device that, when worn by a user, can continuously collect data about their body. 【0067】 "Mobile communication devices" refer to devices such as smartphones and tablets that can communicate even while on the move. 【0068】 A "generative AI model" is an artificial intelligence model that includes algorithms used for data analysis and plan generation. 【0069】 This invention is a system for effectively managing an individual's health, utilizing various devices and data processing means to collect and analyze the user's biometric information in real time and provide a health management plan. 【0070】 First, the system uses a wearable device worn by the user as the terminal. This device collects biometric information such as heart rate, steps taken, and sleep patterns using sensors. A smartwatch is one example, which meticulously records the user's daily activities. This data is transferred to the user's smartphone via Bluetooth or Wi-Fi. 【0071】 Next, the device encrypts the biometric information received by the smartphone using encryption technology such as AES and sends it to a server in the cloud. The data arriving at the server is securely decrypted and analyzed using data analysis tools. Specifically, pattern recognition algorithms are used to model the user's normal health state, enabling the detection of anomalies. 【0072】 Based on the analyzed results, the server uses a generative AI model to generate a personalized health management plan. This plan provides optimal advice tailored to the user's lifestyle and health condition. For example, if a lack of exercise is detected, it might recommend walking three times a week or suggest ways to improve the nutritional balance of their diet. 【0073】 The generated health management plan is sent from the server to the user's smartphone via a notification system. Users can review and improve their daily habits based on the provided health management plan. In addition, if an abnormality is detected, the server will immediately issue a warning and, if necessary, send a notification prompting the user to seek medical attention. 【0074】 For example, if a user's heart rate is detected to be higher than normal one day, the device quickly transmits this information, the server determines it to be "temporary stress," and sends a notification to the user's smartphone recommending deep breathing. In this way, the user can take appropriate measures in real time. 【0075】 Examples of prompts for the generating AI model include: "Based on my current health data, please create exercise and nutrition advice. Include specific suggestions for insufficient exercise and dietary improvements." 【0076】 This invention enables users to easily understand their own health status and efficiently manage their health based on personalized advice. 【0077】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0078】 Step 1: 【0079】 The device acquires the user's biometric information in real time using a wearable device. Specifically, this includes heart rate, steps taken, and sleep patterns. This data is collected via sensors in the wearable device and transmitted to the user's smartphone via Bluetooth or Wi-Fi. At this stage, the input is the biometric information detected by the sensors, and the output is the biometric information sent to the smartphone. 【0080】 Step 2: 【0081】 The device encrypts biometric information using encryption technologies such as AES. The encrypted data is then transmitted to a server in the cloud via the internet. The input is the unprocessed biometric information present on the smartphone, and the output is the encrypted and transmitted biometric information. This process ensures that the data is transferred securely. 【0082】 Step 3: 【0083】 The server decrypts the received biometric information. This decryption is a crucial step preceding data analysis. Next, the server analyzes the decrypted information using data analysis tools. Pattern recognition algorithms are used for this analysis. The input is encrypted biometric information, and the output is the analysis result. Specifically, the server checks for normal patterns and signs of anomalies. 【0084】 Step 4: 【0085】 The server generates a health management plan using an AI model based on the analyzed data. The analysis results are input to the AI ​​as prompts, generating suggestions tailored to the individual's health condition. The input is the analysis results, and the output is a personalized health management plan. For example, if the system determines that the user is not getting enough exercise, an appropriate exercise plan will be generated. 【0086】 Step 5: 【0087】 The health management plan obtained from the server is sent to the user's smartphone by the server. The user is presented with the details of the plan using a notification method. The input is the generated health management plan, and the output is the notification message to the user. The user receives this notification and checks the health management advice that is appropriate for their daily life. 【0088】 Step 6: 【0089】 If an anomaly is detected, the server quickly generates an alert and warns the user. The input is the anomaly pattern detected during analysis, and the output is the warning message to the user. The user receives this warning and considers seeking medical attention if necessary. 【0090】 (Application Example 1) 【0091】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0092】 To effectively monitor the health status of the elderly and provide appropriate care support, it is necessary to collect and analyze biometric information in real time and provide continuous health management. However, current systems lack the functionality to efficiently aggregate this information and propose individualized health management plans. This creates a challenge in maintaining the health and providing care support for the elderly. 【0093】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0094】 In this invention, the server includes information acquisition means for collecting personal biometric data, data analysis means for analyzing the biometric data, plan generation means for generating individual health management plans based on the data analysis, monitoring means having an alert function for issuing warnings when abnormalities are detected, communication means for securely encrypting and transmitting the collected data, and support means for suggesting exercises and meals suitable for elderly care support. This enables real-time monitoring of the health status of elderly individuals, provision of individualized care plans, and rapid response in the event of abnormalities. 【0095】 "Information acquisition means" refers to devices and methods for collecting an individual's biometric data in real time. 【0096】 "Data analysis means" refers to methods and technologies for processing and analyzing acquired biological data to evaluate health status. 【0097】 "Plan generation method" refers to a method for automatically creating individual health management plans based on the results of data analysis. 【0098】 "Notification means" refers to methods or devices for communicating generated health management plans or warnings of abnormalities to the user. 【0099】 The "alert function" refers to a feature that issues a warning when an anomaly is detected through monitoring, prompting a quick response. 【0100】 "Monitoring means" refers to methods and devices for continuously observing biological data and determining whether or not there are any abnormalities. 【0101】 "Communication method" refers to a system for securely encrypting acquired biometric data and transmitting it to the necessary servers and devices. 【0102】 "Support measures" refer to methods and techniques for maintaining health, such as suggesting appropriate exercise and diet as part of care support for the elderly. 【0103】 To realize this invention, it is necessary to build a series of systems that collect, analyze, and utilize individual biometric data for health management. The terminal uses a wearable data collection device to collect the user's heart rate, steps, sleep patterns, etc., in real time. This data is securely encrypted and transmitted to a server in the cloud via a mobile communication device. 【0104】 The server analyzes data received on the cloud using data analysis tools. For example, it uses algorithms on collected heart rate data to evaluate an individual's health status and detect normal patterns and abnormalities. Based on the analysis results, the server generates a personalized health management plan and suggests exercise and diet plans suitable for the user. 【0105】 Furthermore, the server has a monitoring function that issues alerts if an anomaly is detected, quickly notifying users and caregivers via their terminals. This allows users to monitor their daily health status and respond immediately to any abnormalities. For example, it can be used to check whether elderly people are getting adequate exercise on a daily basis and, if insufficient exercise is detected, suggest increasing their walking. 【0106】 In the application of this invention, the use of a generative AI model is also being considered. As an example of a prompt, data can be input to the AI ​​model in the form of, "An 80-year-old user uses a health management app and, after obtaining a history of their daily activities, should be suggested an appropriate exercise program." 【0107】 In this way, detailed health management and early detection of abnormalities can be achieved for individual users, leading to overall health improvement. 【0108】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0109】 Step 1: 【0110】 The device collects biometric data such as heart rate, steps taken, and sleep patterns from the user via a wearable data collection device. This biometric data serves as input for initial processing on the device. After that, the data is encrypted and prepared for secure communication. 【0111】 Step 2: 【0112】 The device transmits encrypted data to a server in the cloud using a mobile communication device. The input is encrypted biometric data, and the data that reaches the server is subject to analysis. 【0113】 Step 3: 【0114】 The server processes the received biometric data using data analysis tools. It analyzes heart rate data, step count data, and other data based on algorithms to evaluate the user's specific health status. This involves recognizing data patterns and detecting anomalies. 【0115】 Step 4: 【0116】 Based on the analysis results, the server generates an individualized health management plan. This plan includes guidelines for appropriate exercise and diet, indicating the optimal health maintenance measures for the user. The generated plan is output. 【0117】 Step 5: 【0118】 The server sends the generated health management plan to the terminal via a notification system and presents it to the user. Here, the analysis results and the generated health management plan are prepared as notification content for the terminal. 【0119】 Step 6: 【0120】 The server continuously checks for data anomalies through monitoring mechanisms and uses an alert function to promptly warn terminals if an anomaly is detected. The input is real-time updated biometric data, and the output is an alert issued when an anomaly occurs. 【0121】 Step 7: 【0122】 Users can utilize the generated AI model to receive advice tailored to their health condition using prompt messages. Here, prompt messages are provided as input to the generated AI model, allowing the model to output specific health advice. 【0123】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0124】 This invention is a system that comprehensively manages an individual's health and mental state, combining biometric information with an emotion engine that recognizes the user's emotional state. This makes it possible to optimize both the user's physical and emotional health. 【0125】 First, the device continuously collects biometric and environmental information via the user's wearable device or smartphone. This collected data includes not only heart rate, activity level, and sleep quality, but also emotional data using daily voice and facial characteristics. This information is measured using sensors, microphones, and cameras on the device. 【0126】 Next, the device encrypts the collected information and sends it to a server in the cloud via the internet. The server uses machine learning algorithms and natural language processing to analyze the received data. This allows for the diagnosis of the user's health status and changes in emotions such as stress and well-being. 【0127】 Based on the analysis results, the server generates a personalized health management plan and a mental health support plan based on the user's emotional state. For example, if signs of stress are detected through increased heart rate and analysis of the emotional engine, the server will suggest deep breathing and meditation exercises to promote relaxation. 【0128】 The generated plan is sent from the server to the user's device via a notification system. This allows the user to receive specific advice to help with daily health management, stress reduction, and emotional stabilization. Furthermore, if the user's emotional state becomes unstable, the server can issue an alert and prompt them to consult a professional. 【0129】 In this way, this system, which combines an emotional engine, comprehensively supports users' emotional well-being along with their physical health, enabling lifestyle improvements and the maintenance of mental health. 【0130】 The following describes the processing flow. 【0131】 Step 1: 【0132】 The device acquires biometric information from the wearable device worn by the user. This data includes heart rate, steps taken, calories burned, and sleep patterns. It also uses the device's microphone and camera to collect emotional data from voice tone and facial expressions. 【0133】 Step 2: 【0134】 The device analyzes the collected data in real time and performs initial processing. It converts biometric and emotional data into the optimal format, encrypts the data, and then transfers it to the server via the internet. 【0135】 Step 3: 【0136】 The server uses AI algorithms to analyze the received data. It detects health patterns and anomalies from biometric information and identifies the user's emotional state from emotional data. For example, it analyzes signs of increased stress based on the user's normal heart rate. 【0137】 Step 4: 【0138】 The server generates personalized health and mental health plans based on analyzed biometric and emotional information. These plans include exercise, dietary adjustments, and stress management activities. For example, if emotional analysis indicates high stress levels, relaxation exercises will be recommended. 【0139】 Step 5: 【0140】 The server sends the generated plan to the user's device via a notification system. The user can then use this to manage their daily health and emotions. They might receive notifications recommending specific action plans, such as deep breathing exercises every morning or evening walks. 【0141】 Step 6: 【0142】 The server continuously monitors user data and sends an alert to the user if an anomaly is detected. This alert prompts the user to immediately seek help from a medical institution or mental health professional. 【0143】 (Example 2) 【0144】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0145】 In modern society, managing individual health and mental well-being is crucial, but traditional methods struggle to comprehensively support both physical and emotional health. Furthermore, the lack of real-time health monitoring and the provision of appropriate health management plans prevents effective support tailored to individual user needs. 【0146】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0147】 In this invention, the server includes information acquisition means for acquiring biometric and environmental information, data protection and transmission means for encrypting and transmitting the biometric and environmental information, data analysis means for analyzing the received information using a machine learning algorithm, plan generation means for generating individual health management and emotional state management plans based on the analysis results, and notification means for notifying the generated plans. This enables comprehensive support for the user's physical and emotional health, real-time monitoring of health status, and provision of effective health management plans. 【0148】 "Biometric information" refers to data that indicates an individual's health status, including physical data such as heart rate, activity level, and sleep quality. 【0149】 "Environmental information" refers to information about the situation in which the user is placed, and includes data on external factors such as surrounding audio and video data. 【0150】 "Information acquisition means" refers to a system or device for acquiring biometric information and environmental information, and includes hardware such as wearable devices and communication equipment. 【0151】 "Data protection and transmission means" refers to a mechanism or technology for protecting acquired information in accordance with security standards and transmitting it to a server or other device. 【0152】 "Data analysis means" refers to a series of processes and techniques for analyzing received information, and in particular includes means of processing data using machine learning algorithms to evaluate health status and emotional state. 【0153】 "Plan generation means" refers to methods and systems for creating health management plans and emotional state management plans optimized for the user based on analyzed data. 【0154】 "Notification means" refers to methods and systems for transmitting generated plans and information to users, and includes communication methods such as push notifications to terminals. 【0155】 This invention is a system for comprehensively managing an individual's health and emotional state, acquiring biometric and environmental information using wearable devices and smartphones. Specifically, the device acquires biometric information such as heart rate, activity level, and sleep quality in real time through sensors. It also collects voice and facial expression data using microphones and cameras and treats it as environmental information. 【0156】 The collected data is encrypted on the device and transmitted to the server via a secure communication protocol. The server analyzes the received data using machine learning algorithms and natural language processing techniques. The information obtained from the analysis is used to generate optimized health management plans and emotional management plans based on the user's health and emotional state. 【0157】 The generated plan is sent from the server to the user's device via push notification. This allows the user to receive real-time health and emotional advice, providing specific and effective support in their daily life. An example of a prompt might be, "Please suggest actions to take when the user's heart rate is recorded as higher than normal and signs of stress can be read from the emotional data." This allows the user to receive recommendations for deep breathing exercises or meditation, enabling them to work towards improving their health and emotional state. 【0158】 In this way, the present invention functions as a system that comprehensively supports the user's health and emotions, thereby improving their lifestyle and maintaining their mental health. 【0159】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0160】 Step 1: 【0161】 The terminal activates sensors on the user's wearable devices and smartphone to acquire biometric and environmental information. Inputs include signals from a heart rate sensor, data from an accelerometer, voice input from a microphone, and image data from a camera. Specifically, these devices periodically capture data and organize it into a format suitable for real-time analysis. The output is the acquired, raw biometric and environmental data dataset. 【0162】 Step 2: 【0163】 The terminal encrypts the acquired information using AES encryption for data protection. In this step, it receives the biometric and environmental data sets acquired in step 1 as input. Encryption ensures data confidentiality and prevents unauthorized access. The output is the encrypted data set. 【0164】 Step 3: 【0165】 The terminal uses a secure communication protocol (e.g., HTTPS) to send encrypted data to the server over the internet. The input here is the encrypted dataset. Specifically, the terminal uses a communication module to establish a connection with the server. The output is the data securely transferred to the server. 【0166】 Step 4: 【0167】 The server receives and decrypts encrypted data. It receives encrypted data sent from the terminal as input. After decryption, it analyzes the data using machine learning algorithms to evaluate the user's health and emotional state. The output is a health status report and emotional assessment based on the analysis results. 【0168】 Step 5: 【0169】 The server generates a health management plan and an emotional state management plan tailored to each user based on the analysis results. The input is the analysis results from step 4. Specifically, the server uses a generation AI model to generate personalized plans. The output is the generated health management plan and emotional state management plan. 【0170】 Step 6: 【0171】 The server sends the generated plan to the user's device via push notification. The input is the plan generated in step 5. Specifically, the server uses a notification system to send alerts to the user's device in real time. The output is specific advice on the user's health and emotional state. 【0172】 (Application Example 2) 【0173】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal". 【0174】 In modern society, personal health management and mental health improvement are crucial issues. However, traditional methods often manage physical health and emotional state separately, and there are few systems that integrate and analyze data from both areas to provide accurate advice. Furthermore, there is a lack of support methods that can respond to stress and emotional changes in real time. Solving these challenges is essential. 【0175】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0176】 In this invention, the server includes information acquisition means for collecting an individual's biometric and emotional data, data analysis means for analyzing the biometric and emotional data, and plan generation means for generating individual health management plans and emotional management plans based on the data analysis. This makes it possible to comprehensively manage the user's health and emotional state and provide appropriate advice through a home device. 【0177】 "Personal biometric information" refers to data measured to indicate a person's physical condition, such as heart rate, activity level, and sleep quality. 【0178】 "Emotional data" refers to data that indicates an individual's emotional state, based on information obtained from sources such as voice and facial expressions. 【0179】 "Information acquisition means" refers to a device or method for collecting an individual's biometric information or emotional data. 【0180】 "Data analysis means" refers to a device or method for analyzing collected biometric information and emotional data to evaluate health status and emotional state. 【0181】 "Plan generation means" refers to an apparatus or method for creating individual health management plans and emotional management plans based on analysis results. 【0182】 "Notification means" refers to a device or method for informing the user of the generated health management plan and emotional management plan. 【0183】 "Household appliances" refer to devices or methods used in a home environment to make suggestions based on individual emotional data. 【0184】 This invention is a system for the integrated management of an individual's health and emotional state. Users collect biometric and emotional data in their daily lives using wearable devices and smartphones. This data includes heart rate, activity level, sleep quality, and emotional data such as voice and facial expressions. This data is measured by sensors in the wearable device and by the smartphone's microphone and camera. 【0185】 The device encrypts the collected data and securely transmits it to a server in the cloud. The server uses machine learning libraries and natural language processing libraries (e.g., TENSORFLOW® and NLTK) based on Python to analyze biometric and emotional data. This allows for real-time evaluation of the user's health status and emotional changes, and generates personalized health and emotional management plans. 【0186】 The generated plan is sent to the user's device via a notification system from the server. Based on the received notification, the user can receive advice that helps with daily health management and emotional stabilization. Furthermore, if the server determines that the user's emotional state is unstable, it will also provide support by utilizing home devices to suggest relaxation techniques based on emotional data. 【0187】 For example, if the device detects a stressed state from emotional data along with a sudden change in the user's heart rate, the server will suggest, "Shall we play some relaxing music?" via the home device. Furthermore, using a generative AI model, it can generate and suggest responses when the user asks, "What kind of relaxing activities would be good for the weekend?" An example of a prompt might be, "Please suggest some relaxing activities for the weekend." 【0188】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0189】 Step 1: 【0190】 The device collects biometric and emotional data via wearable devices and smartphones. Specifically, it obtains heart rate, activity level, and sleep quality from sensors, and captures voice and facial expression data with the smartphone's microphone and camera. This input data is then processed and formatted in preparation for the next stage of processing. 【0191】 Step 2: 【0192】 The device encrypts the collected data and securely transmits it to the server over the internet. This process utilizes security protocols to maintain data confidentiality. The transmitted data is then input into the server's data analysis module. 【0193】 Step 3: 【0194】 The server analyzes the received data using machine learning algorithms and natural language processing techniques. Specifically, it uses the TensorFlow library to estimate stress levels and health status from biometric information, and the NLTK library to evaluate the tone and trends of emotional data. As a result of the analysis, a report is generated showing the user's health status assessment and emotional progression. 【0195】 Step 4: 【0196】 The server generates a personalized plan for the user's health and emotional management based on the analysis results. The generating AI model uses the suggested prompts to incorporate specific health activities and emotional stabilization measures into the plan. The resulting plan becomes customized advisory content for each user. 【0197】 Step 5: 【0198】 The server notifies the terminal of the generated health management plan and emotional management plan. The terminal presents the received plan to the user and allows them to utilize support tools from home devices. When the user senses stress, it makes specific suggestions such as, "Shall we play some relaxing music?" 【0199】 Step 6: 【0200】 Users begin taking actions to care for their health and mental well-being based on the provided plan. By following the plan, users are expected to experience improved health and mental state. Furthermore, by utilizing a generative AI model, the system responds to additional questions from the user, using "Please suggest some relaxing activities for the weekend" as an example prompt. 【0201】 The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data. 【0202】 Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0203】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14. 【0204】 [Second Embodiment] 【0205】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0206】 As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server. 【0207】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0208】 The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52. 【0209】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0210】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0211】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0212】 Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0213】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0214】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0215】 In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0216】 Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0217】 This invention is a system for effectively managing an individual's health, and includes a process for collecting and analyzing a user's biometric information in real time using wearable devices and communication equipment. The following describes embodiments for implementing this system. 【0218】 First, the device collects biometric information such as heart rate, steps taken, and sleep patterns from the wearable device worn by the user. For example, using a smartwatch, it can track the total number of steps taken in a day, activity level, and heart rate variability. This data is transmitted to a smartphone via Bluetooth or Wi-Fi. 【0219】 Next, the device securely encrypts the collected data and sends it to a server in the cloud. The server analyzes the received biometric information using data analysis tools. Here, algorithms are used to identify normal patterns and signs of abnormalities, and a model is created of the health status of each individual user. 【0220】 Based on the analysis results, the server uses a plan generation mechanism to create a health management plan tailored to the user. For example, if the user is not getting enough exercise, the server might suggest walking three times a week and advise increasing protein intake in terms of diet. 【0221】 The generated health management plan is sent from the server to the user's smartphone via a notification system. This allows the user to receive specific advice for maintaining and improving their daily health. In addition, if an abnormality is detected, the server will quickly issue an alert and prompt the user to take appropriate action. 【0222】 Thus, the present invention enables easy and effective management of users' health by providing a consistent service from the acquisition of biometric information to the provision of health plans. 【0223】 The following describes the processing flow. 【0224】 Step 1: 【0225】 The device acquires the user's biometric information from the wearable device. This includes the number of steps the user takes in a day, heart rate during exercise, and activity data during sleep. The data is periodically transmitted to the device via Bluetooth or Wi-Fi. 【0226】 Step 2: 【0227】 The device stores the acquired biometric information in a database and encrypts it to maintain data integrity. The data is then securely uploaded to a server via the internet. 【0228】 Step 3: 【0229】 The server applies AI algorithms to analyze the received data. By comparing it with past data, it identifies normal and abnormal patterns and analyzes the user's health status and lifestyle. 【0230】 Step 4: 【0231】 The server generates a health management plan based on the analysis results. This plan includes specific suggestions regarding the type and frequency of exercise, ways to improve diet, and appropriate sleep patterns. 【0232】 Step 5: 【0233】 The server sends notifications to the user's device based on the generated health management plan and analysis results. This allows the user to receive specific advice on maintaining and improving their health in their daily life. 【0234】 Step 6: 【0235】 The server monitors the data using a continuous monitoring function and immediately sends an alert to the user if an anomaly is detected. This alert allows the user to quickly address the anomaly. 【0236】 (Example 1) 【0237】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0238】 Personal health management in modern society is becoming increasingly complex due to diverse lifestyles and environmental factors. Conventional health management systems suffer from insufficient real-time collection and analysis of biometric information, making it difficult to provide users with optimal health management plans. Furthermore, they struggle to respond quickly in the event of an abnormality. 【0239】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0240】 In this invention, the server includes information acquisition means for acquiring an individual's biometric information in real time; data transmission means for encrypting the biometric information and transmitting it via a communication network; data analysis means for decrypting and analyzing the biometric information and modeling the health status using a pattern recognition algorithm; plan generation means for generating an individual health management plan using a generated AI model based on the analyzed data; and notification means for notifying the user of the generated health management plan via a mobile communication device. This enables real-time collection and analysis of biometric information, rapid provision of personalized health management plans, and immediate alert generation in case of abnormalities. 【0241】 "Biometric information" refers to numerical values ​​and patterns that indicate the user's physical condition, including information such as heart rate, steps taken, and sleep patterns. 【0242】 "Information acquisition means" refers to devices and methods for collecting biometric information from users in real time, and includes wearable devices and sensors. 【0243】 "Data transmission means" refers to a technology or device that encrypts collected biometric information and transmits it to other devices or cloud servers via a communication network. 【0244】 "Data analysis means" refers to the process or technology of decoding received biometric information and modeling health status using a specific algorithm. 【0245】 "Plan generation means" refers to a method or system for creating individual health management plans using a generated AI model based on data analysis results. 【0246】 "Notification means" refers to a method or device for presenting generated health management plans and alerts in case of abnormalities to the user's device. 【0247】 The "alert function" is a mechanism that quickly alerts the user when an anomaly is detected during biometric information monitoring. 【0248】 A "wearable data collection device" is a device that, when worn by a user, can continuously collect data about their body. 【0249】 "Mobile communication devices" refer to devices such as smartphones and tablets that can communicate even while on the move. 【0250】 A "generative AI model" is an artificial intelligence model that includes algorithms used for data analysis and plan generation. 【0251】 This invention is a system for effectively managing an individual's health, utilizing various devices and data processing means to collect and analyze the user's biometric information in real time and provide a health management plan. 【0252】 First, the system uses a wearable device worn by the user as the terminal. This device collects biometric information such as heart rate, steps taken, and sleep patterns using sensors. A smartwatch is one example, which meticulously records the user's daily activities. This data is transferred to the user's smartphone via Bluetooth or Wi-Fi. 【0253】 Next, the device encrypts the biometric information received by the smartphone using encryption technology such as AES and sends it to a server in the cloud. The data arriving at the server is securely decrypted and analyzed using data analysis tools. Specifically, pattern recognition algorithms are used to model the user's normal health state, enabling the detection of anomalies. 【0254】 Based on the analyzed results, the server uses a generative AI model to generate a personalized health management plan. This plan provides optimal advice tailored to the user's lifestyle and health condition. For example, if a lack of exercise is detected, it might recommend walking three times a week or suggest ways to improve the nutritional balance of their diet. 【0255】 The generated health management plan is sent from the server to the user's smartphone via a notification system. Users can review and improve their daily habits based on the provided health management plan. In addition, if an abnormality is detected, the server will immediately issue a warning and, if necessary, send a notification prompting the user to seek medical attention. 【0256】 For example, if a user's heart rate is detected to be higher than normal one day, the device quickly transmits this information, the server determines it to be "temporary stress," and sends a notification to the user's smartphone recommending deep breathing. In this way, the user can take appropriate measures in real time. 【0257】 Examples of prompts for the generating AI model include: "Based on my current health data, please create exercise and nutrition advice. Include specific suggestions for insufficient exercise and dietary improvements." 【0258】 This invention enables users to easily understand their own health status and efficiently manage their health based on personalized advice. 【0259】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0260】 Step 1: 【0261】 The device acquires the user's biometric information in real time using a wearable device. Specifically, this includes heart rate, steps taken, and sleep patterns. This data is collected via sensors in the wearable device and transmitted to the user's smartphone via Bluetooth or Wi-Fi. At this stage, the input is the biometric information detected by the sensors, and the output is the biometric information sent to the smartphone. 【0262】 Step 2: 【0263】 The device encrypts biometric information using encryption technologies such as AES. The encrypted data is then transmitted to a server in the cloud via the internet. The input is the unprocessed biometric information present on the smartphone, and the output is the encrypted and transmitted biometric information. This process ensures that the data is transferred securely. 【0264】 Step 3: 【0265】 The server decrypts the received biometric information. This decryption is a crucial step preceding data analysis. Next, the server analyzes the decrypted information using data analysis tools. Pattern recognition algorithms are used for this analysis. The input is encrypted biometric information, and the output is the analysis result. Specifically, the server checks for normal patterns and signs of anomalies. 【0266】 Step 4: 【0267】 The server generates a health management plan using an AI model based on the analyzed data. The analysis results are input to the AI ​​as prompts, generating suggestions tailored to the individual's health condition. The input is the analysis results, and the output is a personalized health management plan. For example, if the system determines that the user is not getting enough exercise, an appropriate exercise plan will be generated. 【0268】 Step 5: 【0269】 The health management plan obtained from the server is sent to the user's smartphone by the server. The user is presented with the details of the plan using a notification method. The input is the generated health management plan, and the output is the notification message to the user. The user receives this notification and checks the health management advice that is appropriate for their daily life. 【0270】 Step 6: 【0271】 If an anomaly is detected, the server quickly generates an alert and warns the user. The input is the anomaly pattern detected during analysis, and the output is the warning message to the user. The user receives this warning and considers seeking medical attention if necessary. 【0272】 (Application Example 1) 【0273】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0274】 To effectively monitor the health status of the elderly and provide appropriate care support, it is necessary to collect and analyze biometric information in real time and provide continuous health management. However, current systems lack the functionality to efficiently aggregate this information and propose individualized health management plans. This creates a challenge in maintaining the health and providing care support for the elderly. 【0275】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0276】 In this invention, the server includes an information acquisition means for collecting an individual's biological data, a data analysis means for analyzing the biological data, a plan generation means for generating an individual health management plan based on the data analysis, a monitoring means having an alert function for issuing a warning when an abnormality is detected, a communication means for securely encrypting and transmitting the collected data, and a support means for proposing exercises and diets suitable for the care support of the elderly. Thereby, it becomes possible to monitor the real-time health status of the elderly, provide an individualized care plan, and respond promptly in case of an abnormality. 【0277】 The "information acquisition means" refers to a device or method for collecting an individual's biological data in real time. 【0278】 The "data analysis means" refers to a method or technology for processing and analyzing the acquired biological data and evaluating the health status. 【0279】 The "plan generation means" refers to a method for automatically creating an individual health management plan based on the results of data analysis. 【0280】 The "notification means" refers to a method or device for communicating the generated health management plan and abnormality warnings to the user. 【0281】 The "alert function" refers to a function for issuing a warning when an abnormality is detected by monitoring and prompting a prompt response. 【0282】 The "monitoring means" refers to a method or device for continuously observing biological data and determining the presence or absence of abnormalities. 【0283】 The "communication means" refers to a mechanism for securely encrypting the acquired biological data and transmitting it to the necessary servers and devices. 【0284】 The "support means" refers to a method or technology for proposing appropriate exercises and diets for the care support of the elderly and maintaining health. 【0285】 To implement this invention, it is necessary to build a series of systems that collect, analyze, and utilize personal biometric data for health management. The terminal uses a wearable data collection device to collect the user's heart rate, step count, sleep pattern, etc. in real time. This data is securely encrypted and transmitted to a server on the cloud through a mobile communication device. 【0286】 The server analyzes the data received on the cloud using data analysis means. For example, an algorithm is used for the collected heart rate data to evaluate an individual's health status and detect normal patterns and abnormalities. Based on the analysis results, the server generates an individual health management plan and proposes exercise and diet plans suitable for the user. 【0287】 In addition, the server has a monitoring function. When an abnormality is detected, it issues an alert and promptly notifies the user and the caregiver through the terminal. This enables the user to grasp their daily health status and respond immediately to abnormalities. As a specific example, it checks whether an elderly person is performing appropriate exercise daily and, if a lack of exercise is detected, proposes increasing walking. 【0288】 In the operation of this invention, the utilization of a generative AI model is also considered. As an example of a prompt sentence, data can be input into the AI model in a form such as "Propose an appropriate exercise program for an 80-year-old user after using a health management app and obtaining their daily activity history." 【0289】 In this way, detailed health management for individual users and early detection of abnormalities can be achieved, leading to overall health improvement. 【0290】 The flow of specific processing in Application Example 1 will be described using FIG. 12. 【0291】 Step 1: 【0292】 The device collects biometric data such as heart rate, steps taken, and sleep patterns from the user via a wearable data collection device. This biometric data serves as input for initial processing on the device. After that, the data is encrypted and prepared for secure communication. 【0293】 Step 2: 【0294】 The device transmits encrypted data to a server in the cloud using a mobile communication device. The input is encrypted biometric data, and the data that reaches the server is subject to analysis. 【0295】 Step 3: 【0296】 The server processes the received biometric data using data analysis tools. It analyzes heart rate data, step count data, and other data based on algorithms to evaluate the user's specific health status. This involves recognizing data patterns and detecting anomalies. 【0297】 Step 4: 【0298】 Based on the analysis results, the server generates an individualized health management plan. This plan includes guidelines for appropriate exercise and diet, indicating the optimal health maintenance measures for the user. The generated plan is output. 【0299】 Step 5: 【0300】 The server sends the generated health management plan to the terminal via a notification system and presents it to the user. Here, the analysis results and the generated health management plan are prepared as notification content for the terminal. 【0301】 Step 6: 【0302】 The server continuously checks for data anomalies through monitoring mechanisms and uses an alert function to promptly warn terminals if an anomaly is detected. The input is real-time updated biometric data, and the output is an alert issued when an anomaly occurs. 【0303】 Step 7: 【0304】 The user can utilize the generated AI model and use the prompt text to receive advice according to their health condition. Here, the prompt text is provided as input to the generated AI model, and the model can output specific health advice. 【0305】 Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion recognition model 59 and perform specific processing using the user's emotions. 【0306】 The present invention is a system for comprehensively managing an individual's health and mental state, which combines an emotion engine for recognizing the user's emotional state in addition to biometric information. Thereby, it is possible to optimize both the physical and emotional health of the user. 【0307】 First, the terminal continuously collects biometric information and environmental information via wearable devices or smartphones owned by the user. This collected data includes not only heart rate, activity level, and sleep quality but also emotional data using daily voice and facial expression features. These pieces of information are measured using sensors, microphones, and cameras on the device. 【0308】 Next, the terminal encrypts the collected information and transmits it to a server on the cloud via the Internet. The server uses machine learning algorithms and natural language processing to analyze the received data. Thereby, it is possible to diagnose the user's health condition and the transition of emotions such as stress and happiness. 【0309】 Based on the analysis results, the server generates a personalized health management plan and a mental health support plan based on the user's emotional state. For example, if signs of stress are detected through increased heart rate and analysis of the emotional engine, the server will suggest deep breathing and meditation exercises to promote relaxation. 【0310】 The generated plan is sent from the server to the user's device via a notification system. This allows the user to receive specific advice to help with daily health management, stress reduction, and emotional stabilization. Furthermore, if the user's emotional state becomes unstable, the server can issue an alert and prompt them to consult a professional. 【0311】 In this way, this system, which combines an emotional engine, comprehensively supports users' emotional well-being along with their physical health, enabling lifestyle improvements and the maintenance of mental health. 【0312】 The following describes the processing flow. 【0313】 Step 1: 【0314】 The device acquires biometric information from the wearable device worn by the user. This data includes heart rate, steps taken, calories burned, and sleep patterns. It also uses the device's microphone and camera to collect emotional data from voice tone and facial expressions. 【0315】 Step 2: 【0316】 The device analyzes the collected data in real time and performs initial processing. It converts biometric and emotional data into the optimal format, encrypts the data, and then transfers it to the server via the internet. 【0317】 Step 3: 【0318】 The server uses AI algorithms to analyze the received data. It detects health patterns and anomalies from biometric information and identifies the user's emotional state from emotional data. For example, it analyzes signs of increased stress based on the user's normal heart rate. 【0319】 Step 4: 【0320】 The server generates personalized health and mental health plans based on analyzed biometric and emotional information. These plans include exercise, dietary adjustments, and stress management activities. For example, if emotional analysis indicates high stress levels, relaxation exercises will be recommended. 【0321】 Step 5: 【0322】 The server sends the generated plan to the user's device via a notification system. The user can then use this to manage their daily health and emotions. They might receive notifications recommending specific action plans, such as deep breathing exercises every morning or evening walks. 【0323】 Step 6: 【0324】 The server continuously monitors user data and sends an alert to the user if an anomaly is detected. This alert prompts the user to immediately seek help from a medical institution or mental health professional. 【0325】 (Example 2) 【0326】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0327】 In modern society, managing individual health and mental well-being is crucial, but traditional methods struggle to comprehensively support both physical and emotional health. Furthermore, the lack of real-time health monitoring and the provision of appropriate health management plans prevents effective support tailored to individual user needs. 【0328】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0329】 In this invention, the server includes information acquisition means for acquiring biometric and environmental information, data protection and transmission means for encrypting and transmitting the biometric and environmental information, data analysis means for analyzing the received information using a machine learning algorithm, plan generation means for generating individual health management and emotional state management plans based on the analysis results, and notification means for notifying the generated plans. This enables comprehensive support for the user's physical and emotional health, real-time monitoring of health status, and provision of effective health management plans. 【0330】 "Biometric information" refers to data that indicates an individual's health status, including physical data such as heart rate, activity level, and sleep quality. 【0331】 "Environmental information" refers to information about the situation in which the user is placed, and includes data on external factors such as surrounding audio and video data. 【0332】 "Information acquisition means" refers to a system or device for acquiring biometric information and environmental information, and includes hardware such as wearable devices and communication equipment. 【0333】 "Data protection and transmission means" refers to a mechanism or technology for protecting acquired information in accordance with security standards and transmitting it to a server or other device. 【0334】 "Data analysis means" refers to a series of processes and techniques for analyzing received information, and in particular includes means of processing data using machine learning algorithms to evaluate health status and emotional state. 【0335】 "Plan generation means" refers to methods and systems for creating health management plans and emotional state management plans optimized for the user based on analyzed data. 【0336】 "Notification means" refers to methods and systems for transmitting generated plans and information to users, and includes communication methods such as push notifications to terminals. 【0337】 This invention is a system for comprehensively managing an individual's health and emotional state, acquiring biometric and environmental information using wearable devices and smartphones. Specifically, the device acquires biometric information such as heart rate, activity level, and sleep quality in real time through sensors. It also collects voice and facial expression data using microphones and cameras and treats it as environmental information. 【0338】 The collected data is encrypted on the device and transmitted to the server via a secure communication protocol. The server analyzes the received data using machine learning algorithms and natural language processing techniques. The information obtained from the analysis is used to generate optimized health management plans and emotional management plans based on the user's health and emotional state. 【0339】 The generated plan is sent from the server to the user's device via push notification. This allows the user to receive real-time health and emotional advice, providing specific and effective support in their daily life. An example of a prompt might be, "Please suggest actions to take when the user's heart rate is recorded as higher than normal and signs of stress can be read from the emotional data." This allows the user to receive recommendations for deep breathing exercises or meditation, enabling them to work towards improving their health and emotional state. 【0340】 In this way, the present invention functions as a system that comprehensively supports the user's health and emotions, thereby improving their lifestyle and maintaining their mental health. 【0341】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0342】 Step 1: 【0343】 The terminal activates sensors on the user's wearable devices and smartphone to acquire biometric and environmental information. Inputs include signals from a heart rate sensor, data from an accelerometer, voice input from a microphone, and image data from a camera. Specifically, these devices periodically capture data and organize it into a format suitable for real-time analysis. The output is the acquired, raw biometric and environmental data dataset. 【0344】 Step 2: 【0345】 The terminal encrypts the acquired information using AES encryption for data protection. In this step, it receives the biometric and environmental data sets acquired in step 1 as input. Encryption ensures data confidentiality and prevents unauthorized access. The output is the encrypted data set. 【0346】 Step 3: 【0347】 The terminal uses a secure communication protocol (e.g., HTTPS) to send encrypted data to the server over the internet. The input here is the encrypted dataset. Specifically, the terminal uses a communication module to establish a connection with the server. The output is the data securely transferred to the server. 【0348】 Step 4: 【0349】 The server receives and decrypts encrypted data. It receives encrypted data sent from the terminal as input. After decryption, it analyzes the data using machine learning algorithms to evaluate the user's health and emotional state. The output is a health status report and emotional assessment based on the analysis results. 【0350】 Step 5: 【0351】 The server generates a health management plan and an emotional state management plan tailored to each user based on the analysis results. The input is the analysis results from step 4. Specifically, the server uses a generation AI model to generate personalized plans. The output is the generated health management plan and emotional state management plan. 【0352】 Step 6: 【0353】 The server sends the generated plan to the user's device via push notification. The input is the plan generated in step 5. Specifically, the server uses a notification system to send alerts to the user's device in real time. The output is specific advice on the user's health and emotional state. 【0354】 (Application Example 2) 【0355】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal". 【0356】 In modern society, personal health management and mental health improvement are crucial issues. However, traditional methods often manage physical health and emotional state separately, and there are few systems that integrate and analyze data from both areas to provide accurate advice. Furthermore, there is a lack of support methods that can respond to stress and emotional changes in real time. Solving these challenges is essential. 【0357】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0358】 In this invention, the server includes information acquisition means for collecting an individual's biometric and emotional data, data analysis means for analyzing the biometric and emotional data, and plan generation means for generating individual health management plans and emotional management plans based on the data analysis. This makes it possible to comprehensively manage the user's health and emotional state and provide appropriate advice through a home device. 【0359】 "Personal biometric information" refers to data measured to indicate a person's physical condition, such as heart rate, activity level, and sleep quality. 【0360】 "Emotional data" refers to data that indicates an individual's emotional state, based on information obtained from sources such as voice and facial expressions. 【0361】 "Information acquisition means" refers to a device or method for collecting an individual's biometric information or emotional data. 【0362】 "Data analysis means" refers to a device or method for analyzing collected biometric information and emotional data to evaluate health status and emotional state. 【0363】 "Plan generation means" refers to an apparatus or method for creating individual health management plans and emotional management plans based on analysis results. 【0364】 "Notification means" refers to a device or method for informing the user of the generated health management plan and emotional management plan. 【0365】 "Household appliances" refer to devices or methods used in a home environment to make suggestions based on individual emotional data. 【0366】 This invention is a system for the integrated management of an individual's health and emotional state. Users collect biometric and emotional data in their daily lives using wearable devices and smartphones. This data includes heart rate, activity level, sleep quality, and emotional data such as voice and facial expressions. This data is measured by sensors in the wearable device and by the smartphone's microphone and camera. 【0367】 The device encrypts the collected data and securely transmits it to a server in the cloud. The server uses machine learning libraries and natural language processing libraries (e.g., TensorFlow and NLTK) based on Python to analyze biometric and emotional data. This allows for real-time evaluation of the user's health status and emotional changes, and generates personalized health and emotional management plans. 【0368】 The generated plan is sent to the user's device via a notification system from the server. Based on the received notification, the user can receive advice that helps with daily health management and emotional stabilization. Furthermore, if the server determines that the user's emotional state is unstable, it will also provide support by utilizing home devices to suggest relaxation techniques based on emotional data. 【0369】 For example, if the device detects a stressed state from emotional data along with a sudden change in the user's heart rate, the server will suggest, "Shall we play some relaxing music?" via the home device. Furthermore, using a generative AI model, it can generate and suggest responses when the user asks, "What kind of relaxing activities would be good for the weekend?" An example of a prompt might be, "Please suggest some relaxing activities for the weekend." 【0370】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0371】 Step 1: 【0372】 The device collects biometric and emotional data via wearable devices and smartphones. Specifically, it obtains heart rate, activity level, and sleep quality from sensors, and captures voice and facial expression data with the smartphone's microphone and camera. This input data is then processed and formatted in preparation for the next stage of processing. 【0373】 Step 2: 【0374】 The device encrypts the collected data and securely transmits it to the server over the internet. This process utilizes security protocols to maintain data confidentiality. The transmitted data is then input into the server's data analysis module. 【0375】 Step 3: 【0376】 The server analyzes the received data using machine learning algorithms and natural language processing techniques. Specifically, it uses the TensorFlow library to estimate stress levels and health status from biometric information, and the NLTK library to evaluate the tone and trends of emotional data. As a result of the analysis, a report is generated showing the user's health status assessment and emotional progression. 【0377】 Step 4: 【0378】 The server generates a personalized plan for the user's health and emotional management based on the analysis results. The generating AI model uses the suggested prompts to incorporate specific health activities and emotional stabilization measures into the plan. The resulting plan becomes customized advisory content for each user. 【0379】 Step 5: 【0380】 The server notifies the terminal of the generated health management plan and emotional management plan. The terminal presents the received plan to the user and allows them to utilize support tools from home devices. When the user senses stress, it makes specific suggestions such as, "Shall we play some relaxing music?" 【0381】 Step 6: 【0382】 Users begin taking actions to care for their health and mental well-being based on the provided plan. By following the plan, users are expected to experience improved health and mental state. Furthermore, by utilizing a generative AI model, the system responds to additional questions from the user, using "Please suggest some relaxing activities for the weekend" as an example prompt. 【0383】 The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0384】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0385】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214. 【0386】 [Third Embodiment] 【0387】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0388】 As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server. 【0389】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0390】 The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52. 【0391】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0392】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0393】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0394】 Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0395】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0396】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0397】 In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0398】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal". 【0399】 This invention is a system for effectively managing an individual's health, and includes a process for collecting and analyzing a user's biometric information in real time using wearable devices and communication equipment. The following describes embodiments for implementing this system. 【0400】 First, the device collects biometric information such as heart rate, steps taken, and sleep patterns from the wearable device worn by the user. For example, using a smartwatch, it can track the total number of steps taken in a day, activity level, and heart rate variability. This data is transmitted to a smartphone via Bluetooth or Wi-Fi. 【0401】 Next, the device securely encrypts the collected data and sends it to a server in the cloud. The server analyzes the received biometric information using data analysis tools. Here, algorithms are used to identify normal patterns and signs of abnormalities, and a model is created of the health status of each individual user. 【0402】 Based on the analysis results, the server uses a plan generation mechanism to create a health management plan tailored to the user. For example, if the user is not getting enough exercise, the server might suggest walking three times a week and advise increasing protein intake in terms of diet. 【0403】 The generated health management plan is sent from the server to the user's smartphone via a notification system. This allows the user to receive specific advice for maintaining and improving their daily health. In addition, if an abnormality is detected, the server will quickly issue an alert and prompt the user to take appropriate action. 【0404】 Thus, the present invention enables easy and effective management of users' health by providing a consistent service from the acquisition of biometric information to the provision of health plans. 【0405】 The following describes the processing flow. 【0406】 Step 1: 【0407】 The device acquires the user's biometric information from the wearable device. This includes the number of steps the user takes in a day, heart rate during exercise, and activity data during sleep. The data is periodically transmitted to the device via Bluetooth or Wi-Fi. 【0408】 Step 2: 【0409】 The device stores the acquired biometric information in a database and encrypts it to maintain data integrity. The data is then securely uploaded to a server via the internet. 【0410】 Step 3: 【0411】 The server applies AI algorithms to analyze the received data. By comparing it with past data, it identifies normal and abnormal patterns and analyzes the user's health status and lifestyle. 【0412】 Step 4: 【0413】 The server generates a health management plan based on the analysis results. This plan includes specific suggestions regarding the type and frequency of exercise, ways to improve diet, and appropriate sleep patterns. 【0414】 Step 5: 【0415】 The server sends notifications to the user's device based on the generated health management plan and analysis results. This allows the user to receive specific advice on maintaining and improving their health in their daily life. 【0416】 Step 6: 【0417】 The server monitors the data using a continuous monitoring function and immediately sends an alert to the user if an anomaly is detected. This alert allows the user to quickly address the anomaly. 【0418】 (Example 1) 【0419】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0420】 Personal health management in modern society is becoming increasingly complex due to diverse lifestyles and environmental factors. Conventional health management systems suffer from insufficient real-time collection and analysis of biometric information, making it difficult to provide users with optimal health management plans. Furthermore, they struggle to respond quickly in the event of an abnormality. 【0421】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0422】 In this invention, the server includes information acquisition means for acquiring an individual's biometric information in real time; data transmission means for encrypting the biometric information and transmitting it via a communication network; data analysis means for decrypting and analyzing the biometric information and modeling the health status using a pattern recognition algorithm; plan generation means for generating an individual health management plan using a generated AI model based on the analyzed data; and notification means for notifying the user of the generated health management plan via a mobile communication device. This enables real-time collection and analysis of biometric information, rapid provision of personalized health management plans, and immediate alert generation in case of abnormalities. 【0423】 "Biometric information" refers to numerical values ​​and patterns that indicate the user's physical condition, including information such as heart rate, steps taken, and sleep patterns. 【0424】 "Information acquisition means" refers to devices and methods for collecting biometric information from users in real time, and includes wearable devices and sensors. 【0425】 "Data transmission means" refers to a technology or device that encrypts collected biometric information and transmits it to other devices or cloud servers via a communication network. 【0426】 "Data analysis means" refers to the process or technology of decoding received biometric information and modeling health status using a specific algorithm. 【0427】 "Plan generation means" refers to a method or system for creating individual health management plans using a generated AI model based on data analysis results. 【0428】 "Notification means" refers to a method or device for presenting generated health management plans and alerts in case of abnormalities to the user's device. 【0429】 The "alert function" is a mechanism that quickly alerts the user when an anomaly is detected during biometric information monitoring. 【0430】 A "wearable data collection device" is a device that, when worn by a user, can continuously collect data about their body. 【0431】 "Mobile communication devices" refer to devices such as smartphones and tablets that can communicate even while on the move. 【0432】 A "generative AI model" is an artificial intelligence model that includes algorithms used for data analysis and plan generation. 【0433】 This invention is a system for effectively managing an individual's health, utilizing various devices and data processing means to collect and analyze the user's biometric information in real time and provide a health management plan. 【0434】 First, the system uses a wearable device worn by the user as the terminal. This device collects biometric information such as heart rate, steps taken, and sleep patterns using sensors. A smartwatch is one example, which meticulously records the user's daily activities. This data is transferred to the user's smartphone via Bluetooth or Wi-Fi. 【0435】 Next, the device encrypts the biometric information received by the smartphone using encryption technology such as AES and sends it to a server in the cloud. The data arriving at the server is securely decrypted and analyzed using data analysis tools. Specifically, pattern recognition algorithms are used to model the user's normal health state, enabling the detection of anomalies. 【0436】 Based on the analyzed results, the server uses a generative AI model to generate a personalized health management plan. This plan provides optimal advice tailored to the user's lifestyle and health condition. For example, if a lack of exercise is detected, it might recommend walking three times a week or suggest ways to improve the nutritional balance of their diet. 【0437】 The generated health management plan is sent from the server to the user's smartphone via a notification system. Users can review and improve their daily habits based on the provided health management plan. In addition, if an abnormality is detected, the server will immediately issue a warning and, if necessary, send a notification prompting the user to seek medical attention. 【0438】 For example, if a user's heart rate is detected to be higher than normal one day, the device quickly transmits this information, the server determines it to be "temporary stress," and sends a notification to the user's smartphone recommending deep breathing. In this way, the user can take appropriate measures in real time. 【0439】 Examples of prompts for the generating AI model include: "Based on my current health data, please create exercise and nutrition advice. Include specific suggestions for insufficient exercise and dietary improvements." 【0440】 This invention enables users to easily understand their own health status and efficiently manage their health based on personalized advice. 【0441】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0442】 Step 1: 【0443】 The device acquires the user's biometric information in real time using a wearable device. Specifically, this includes heart rate, steps taken, and sleep patterns. This data is collected via sensors in the wearable device and transmitted to the user's smartphone via Bluetooth or Wi-Fi. At this stage, the input is the biometric information detected by the sensors, and the output is the biometric information sent to the smartphone. 【0444】 Step 2: 【0445】 The device encrypts biometric information using encryption technologies such as AES. The encrypted data is then transmitted to a server in the cloud via the internet. The input is the unprocessed biometric information present on the smartphone, and the output is the encrypted and transmitted biometric information. This process ensures that the data is transferred securely. 【0446】 Step 3: 【0447】 The server decrypts the received biometric information. This decryption is a crucial step preceding data analysis. Next, the server analyzes the decrypted information using data analysis tools. Pattern recognition algorithms are used for this analysis. The input is encrypted biometric information, and the output is the analysis result. Specifically, the server checks for normal patterns and signs of anomalies. 【0448】 Step 4: 【0449】 The server generates a health management plan using an AI model based on the analyzed data. The analysis results are input to the AI ​​as prompts, generating suggestions tailored to the individual's health condition. The input is the analysis results, and the output is a personalized health management plan. For example, if the system determines that the user is not getting enough exercise, an appropriate exercise plan will be generated. 【0450】 Step 5: 【0451】 The health management plan obtained from the server is sent to the user's smartphone by the server. The user is presented with the details of the plan using a notification method. The input is the generated health management plan, and the output is the notification message to the user. The user receives this notification and checks the health management advice that is appropriate for their daily life. 【0452】 Step 6: 【0453】 If an anomaly is detected, the server quickly generates an alert and warns the user. The input is the anomaly pattern detected during analysis, and the output is the warning message to the user. The user receives this warning and considers seeking medical attention if necessary. 【0454】 (Application Example 1) 【0455】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0456】 To effectively monitor the health status of the elderly and provide appropriate care support, it is necessary to collect and analyze biometric information in real time and provide continuous health management. However, current systems lack the functionality to efficiently aggregate this information and propose individualized health management plans. This creates a challenge in maintaining the health and providing care support for the elderly. 【0457】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0458】 In this invention, the server includes information acquisition means for collecting personal biometric data, data analysis means for analyzing the biometric data, plan generation means for generating individual health management plans based on the data analysis, monitoring means having an alert function for issuing warnings when abnormalities are detected, communication means for securely encrypting and transmitting the collected data, and support means for suggesting exercises and meals suitable for elderly care support. This enables real-time monitoring of the health status of elderly individuals, provision of individualized care plans, and rapid response in the event of abnormalities. 【0459】 "Information acquisition means" refers to devices and methods for collecting an individual's biometric data in real time. 【0460】 "Data analysis means" refers to methods and technologies for processing and analyzing acquired biological data to evaluate health status. 【0461】 "Plan generation method" refers to a method for automatically creating individual health management plans based on the results of data analysis. 【0462】 "Notification means" refers to methods or devices for communicating generated health management plans or warnings of abnormalities to the user. 【0463】 The "alert function" refers to a feature that issues a warning when an anomaly is detected through monitoring, prompting a quick response. 【0464】 "Monitoring means" refers to methods and devices for continuously observing biological data and determining whether or not there are any abnormalities. 【0465】 "Communication method" refers to a system for securely encrypting acquired biometric data and transmitting it to the necessary servers and devices. 【0466】 "Support measures" refer to methods and techniques for maintaining health, such as suggesting appropriate exercise and diet as part of care support for the elderly. 【0467】 To realize this invention, it is necessary to build a series of systems that collect, analyze, and utilize individual biometric data for health management. The terminal uses a wearable data collection device to collect the user's heart rate, steps, sleep patterns, etc., in real time. This data is securely encrypted and transmitted to a server in the cloud via a mobile communication device. 【0468】 The server analyzes data received on the cloud using data analysis tools. For example, it uses algorithms on collected heart rate data to evaluate an individual's health status and detect normal patterns and abnormalities. Based on the analysis results, the server generates a personalized health management plan and suggests exercise and diet plans suitable for the user. 【0469】 Furthermore, the server has a monitoring function that issues alerts if an anomaly is detected, quickly notifying users and caregivers via their terminals. This allows users to monitor their daily health status and respond immediately to any abnormalities. For example, it can be used to check whether elderly people are getting adequate exercise on a daily basis and, if insufficient exercise is detected, suggest increasing their walking. 【0470】 In the application of this invention, the use of a generative AI model is also being considered. As an example of a prompt, data can be input to the AI ​​model in the form of, "An 80-year-old user uses a health management app and, after obtaining a history of their daily activities, should be suggested an appropriate exercise program." 【0471】 In this way, detailed health management and early detection of abnormalities can be achieved for individual users, leading to overall health improvement. 【0472】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0473】 Step 1: 【0474】 The device collects biometric data such as heart rate, steps taken, and sleep patterns from the user via a wearable data collection device. This biometric data serves as input for initial processing on the device. After that, the data is encrypted and prepared for secure communication. 【0475】 Step 2: 【0476】 The device transmits encrypted data to a server in the cloud using a mobile communication device. The input is encrypted biometric data, and the data that reaches the server is subject to analysis. 【0477】 Step 3: 【0478】 The server processes the received biometric data using data analysis tools. It analyzes heart rate data, step count data, and other data based on algorithms to evaluate the user's specific health status. This involves recognizing data patterns and detecting anomalies. 【0479】 Step 4: 【0480】 Based on the analysis results, the server generates an individualized health management plan. This plan includes guidelines for appropriate exercise and diet, indicating the optimal health maintenance measures for the user. The generated plan is output. 【0481】 Step 5: 【0482】 The server sends the generated health management plan to the terminal via a notification system and presents it to the user. Here, the analysis results and the generated health management plan are prepared as notification content for the terminal. 【0483】 Step 6: 【0484】 The server continuously checks for data anomalies through monitoring mechanisms and uses an alert function to promptly warn terminals if an anomaly is detected. The input is real-time updated biometric data, and the output is an alert issued when an anomaly occurs. 【0485】 Step 7: 【0486】 Users can utilize the generated AI model to receive advice tailored to their health condition using prompt messages. Here, prompt messages are provided as input to the generated AI model, allowing the model to output specific health advice. 【0487】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0488】 This invention is a system that comprehensively manages an individual's health and mental state, combining biometric information with an emotion engine that recognizes the user's emotional state. This makes it possible to optimize both the user's physical and emotional health. 【0489】 First, the device continuously collects biometric and environmental information via the user's wearable device or smartphone. This collected data includes not only heart rate, activity level, and sleep quality, but also emotional data using daily voice and facial characteristics. This information is measured using sensors, microphones, and cameras on the device. 【0490】 Next, the device encrypts the collected information and sends it to a server in the cloud via the internet. The server uses machine learning algorithms and natural language processing to analyze the received data. This allows for the diagnosis of the user's health status and changes in emotions such as stress and well-being. 【0491】 Based on the analysis results, the server generates a personalized health management plan and a mental health support plan based on the user's emotional state. For example, if signs of stress are detected through increased heart rate and analysis of the emotional engine, the server will suggest deep breathing and meditation exercises to promote relaxation. 【0492】 The generated plan is sent from the server to the user's device via a notification system. This allows the user to receive specific advice to help with daily health management, stress reduction, and emotional stabilization. Furthermore, if the user's emotional state becomes unstable, the server can issue an alert and prompt them to consult a professional. 【0493】 In this way, this system, which combines an emotional engine, comprehensively supports users' emotional well-being along with their physical health, enabling lifestyle improvements and the maintenance of mental health. 【0494】 The following describes the processing flow. 【0495】 Step 1: 【0496】 The device acquires biometric information from the wearable device worn by the user. This data includes heart rate, steps taken, calories burned, and sleep patterns. It also uses the device's microphone and camera to collect emotional data from voice tone and facial expressions. 【0497】 Step 2: 【0498】 The device analyzes the collected data in real time and performs initial processing. It converts biometric and emotional data into the optimal format, encrypts the data, and then transfers it to the server via the internet. 【0499】 Step 3: 【0500】 The server uses AI algorithms to analyze the received data. It detects health patterns and anomalies from biometric information and identifies the user's emotional state from emotional data. For example, it analyzes signs of increased stress based on the user's normal heart rate. 【0501】 Step 4: 【0502】 The server generates personalized health and mental health plans based on analyzed biometric and emotional information. These plans include exercise, dietary adjustments, and stress management activities. For example, if emotional analysis indicates high stress levels, relaxation exercises will be recommended. 【0503】 Step 5: 【0504】 The server sends the generated plan to the user's device via a notification system. The user can then use this to manage their daily health and emotions. They might receive notifications recommending specific action plans, such as deep breathing exercises every morning or evening walks. 【0505】 Step 6: 【0506】 The server continuously monitors user data and sends an alert to the user if an anomaly is detected. This alert prompts the user to immediately seek help from a medical institution or mental health professional. 【0507】 (Example 2) 【0508】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0509】 In modern society, managing individual health and mental well-being is crucial, but traditional methods struggle to comprehensively support both physical and emotional health. Furthermore, the lack of real-time health monitoring and the provision of appropriate health management plans prevents effective support tailored to individual user needs. 【0510】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0511】 In this invention, the server includes information acquisition means for acquiring biometric and environmental information, data protection and transmission means for encrypting and transmitting the biometric and environmental information, data analysis means for analyzing the received information using a machine learning algorithm, plan generation means for generating individual health management and emotional state management plans based on the analysis results, and notification means for notifying the generated plans. This enables comprehensive support for the user's physical and emotional health, real-time monitoring of health status, and provision of effective health management plans. 【0512】 "Biometric information" refers to data that indicates an individual's health status, including physical data such as heart rate, activity level, and sleep quality. 【0513】 "Environmental information" refers to information about the situation in which the user is placed, and includes data on external factors such as surrounding audio and video data. 【0514】 "Information acquisition means" refers to a system or device for acquiring biometric information and environmental information, and includes hardware such as wearable devices and communication equipment. 【0515】 "Data protection and transmission means" refers to a mechanism or technology for protecting acquired information in accordance with security standards and transmitting it to a server or other device. 【0516】 "Data analysis means" refers to a series of processes and techniques for analyzing received information, and in particular includes means of processing data using machine learning algorithms to evaluate health status and emotional state. 【0517】 "Plan generation means" refers to methods and systems for creating health management plans and emotional state management plans optimized for the user based on analyzed data. 【0518】 "Notification means" refers to methods and systems for transmitting generated plans and information to users, and includes communication methods such as push notifications to terminals. 【0519】 This invention is a system for comprehensively managing an individual's health and emotional state, acquiring biometric and environmental information using wearable devices and smartphones. Specifically, the device acquires biometric information such as heart rate, activity level, and sleep quality in real time through sensors. It also collects voice and facial expression data using microphones and cameras and treats it as environmental information. 【0520】 The collected data is encrypted on the device and transmitted to the server via a secure communication protocol. The server analyzes the received data using machine learning algorithms and natural language processing techniques. The information obtained from the analysis is used to generate optimized health management plans and emotional management plans based on the user's health and emotional state. 【0521】 The generated plan is sent from the server to the user's device via push notification. This allows the user to receive real-time health and emotional advice, providing specific and effective support in their daily life. An example of a prompt might be, "Please suggest actions to take when the user's heart rate is recorded as higher than normal and signs of stress can be read from the emotional data." This allows the user to receive recommendations for deep breathing exercises or meditation, enabling them to work towards improving their health and emotional state. 【0522】 In this way, the present invention functions as a system that comprehensively supports the user's health and emotions, thereby improving their lifestyle and maintaining their mental health. 【0523】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0524】 Step 1: 【0525】 The terminal activates sensors on the user's wearable devices and smartphone to acquire biometric and environmental information. Inputs include signals from a heart rate sensor, data from an accelerometer, voice input from a microphone, and image data from a camera. Specifically, these devices periodically capture data and organize it into a format suitable for real-time analysis. The output is the acquired, raw biometric and environmental data dataset. 【0526】 Step 2: 【0527】 The terminal encrypts the acquired information using AES encryption for data protection. In this step, it receives the biometric and environmental data sets acquired in step 1 as input. Encryption ensures data confidentiality and prevents unauthorized access. The output is the encrypted data set. 【0528】 Step 3: 【0529】 The terminal uses a secure communication protocol (e.g., HTTPS) to send encrypted data to the server over the internet. The input here is the encrypted dataset. Specifically, the terminal uses a communication module to establish a connection with the server. The output is the data securely transferred to the server. 【0530】 Step 4: 【0531】 The server receives and decrypts encrypted data. It receives encrypted data sent from the terminal as input. After decryption, it analyzes the data using machine learning algorithms to evaluate the user's health and emotional state. The output is a health status report and emotional assessment based on the analysis results. 【0532】 Step 5: 【0533】 The server generates a health management plan and an emotional state management plan tailored to each user based on the analysis results. The input is the analysis results from step 4. Specifically, the server uses a generation AI model to generate personalized plans. The output is the generated health management plan and emotional state management plan. 【0534】 Step 6: 【0535】 The server sends the generated plan to the user's device via push notification. The input is the plan generated in step 5. Specifically, the server uses a notification system to send alerts to the user's device in real time. The output is specific advice on the user's health and emotional state. 【0536】 (Application Example 2) 【0537】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0538】 In modern society, personal health management and mental health improvement are crucial issues. However, traditional methods often manage physical health and emotional state separately, and there are few systems that integrate and analyze data from both areas to provide accurate advice. Furthermore, there is a lack of support methods that can respond to stress and emotional changes in real time. Solving these challenges is essential. 【0539】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0540】 In this invention, the server includes information acquisition means for collecting an individual's biometric and emotional data, data analysis means for analyzing the biometric and emotional data, and plan generation means for generating individual health management plans and emotional management plans based on the data analysis. This makes it possible to comprehensively manage the user's health and emotional state and provide appropriate advice through a home device. 【0541】 "Personal biometric information" refers to data measured to indicate a person's physical condition, such as heart rate, activity level, and sleep quality. 【0542】 "Emotional data" refers to data that indicates an individual's emotional state, based on information obtained from sources such as voice and facial expressions. 【0543】 "Information acquisition means" refers to a device or method for collecting an individual's biometric information or emotional data. 【0544】 "Data analysis means" refers to a device or method for analyzing collected biometric information and emotional data to evaluate health status and emotional state. 【0545】 "Plan generation means" refers to an apparatus or method for creating individual health management plans and emotional management plans based on analysis results. 【0546】 "Notification means" refers to a device or method for informing the user of the generated health management plan and emotional management plan. 【0547】 "Household appliances" refer to devices or methods used in a home environment to make suggestions based on individual emotional data. 【0548】 This invention is a system for the integrated management of an individual's health and emotional state. Users collect biometric and emotional data in their daily lives using wearable devices and smartphones. This data includes heart rate, activity level, sleep quality, and emotional data such as voice and facial expressions. This data is measured by sensors in the wearable device and by the smartphone's microphone and camera. 【0549】 The device encrypts the collected data and securely transmits it to a server in the cloud. The server uses machine learning libraries and natural language processing libraries (e.g., TensorFlow and NLTK) based on Python to analyze biometric and emotional data. This allows for real-time evaluation of the user's health status and emotional changes, and generates personalized health and emotional management plans. 【0550】 The generated plan is sent to the user's device via a notification system from the server. Based on the received notification, the user can receive advice that helps with daily health management and emotional stabilization. Furthermore, if the server determines that the user's emotional state is unstable, it will also provide support by utilizing home devices to suggest relaxation techniques based on emotional data. 【0551】 For example, if the device detects a stressed state from emotional data along with a sudden change in the user's heart rate, the server will suggest, "Shall we play some relaxing music?" via the home device. Furthermore, using a generative AI model, it can generate and suggest responses when the user asks, "What kind of relaxing activities would be good for the weekend?" An example of a prompt might be, "Please suggest some relaxing activities for the weekend." 【0552】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0553】 Step 1: 【0554】 The device collects biometric and emotional data via wearable devices and smartphones. Specifically, it obtains heart rate, activity level, and sleep quality from sensors, and captures voice and facial expression data with the smartphone's microphone and camera. This input data is then processed and formatted in preparation for the next stage of processing. 【0555】 Step 2: 【0556】 The device encrypts the collected data and securely transmits it to the server over the internet. This process utilizes security protocols to maintain data confidentiality. The transmitted data is then input into the server's data analysis module. 【0557】 Step 3: 【0558】 The server analyzes the received data using machine learning algorithms and natural language processing techniques. Specifically, it uses the TensorFlow library to estimate stress levels and health status from biometric information, and the NLTK library to evaluate the tone and trends of emotional data. As a result of the analysis, a report is generated showing the user's health status assessment and emotional progression. 【0559】 Step 4: 【0560】 The server generates a personalized plan for the user's health and emotional management based on the analysis results. The generating AI model uses the suggested prompts to incorporate specific health activities and emotional stabilization measures into the plan. The resulting plan becomes customized advisory content for each user. 【0561】 Step 5: 【0562】 The server notifies the terminal of the generated health management plan and emotional management plan. The terminal presents the received plan to the user and allows them to utilize support tools from home devices. When the user senses stress, it makes specific suggestions such as, "Shall we play some relaxing music?" 【0563】 Step 6: 【0564】 Users begin taking actions to care for their health and mental well-being based on the provided plan. By following the plan, users are expected to experience improved health and mental state. Furthermore, by utilizing a generative AI model, the system responds to additional questions from the user, using "Please suggest some relaxing activities for the weekend" as an example prompt. 【0565】 The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0566】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0567】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314. 【0568】 [Fourth Embodiment] 【0569】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0570】 As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server. 【0571】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0572】 The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52. 【0573】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0574】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0575】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0576】 The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes. 【0577】 Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0578】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0579】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0580】 In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0581】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0582】 This invention is a system for effectively managing an individual's health, and includes a process for collecting and analyzing a user's biometric information in real time using wearable devices and communication equipment. The following describes embodiments for implementing this system. 【0583】 First, the device collects biometric information such as heart rate, steps taken, and sleep patterns from the wearable device worn by the user. For example, using a smartwatch, it can track the total number of steps taken in a day, activity level, and heart rate variability. This data is transmitted to a smartphone via Bluetooth or Wi-Fi. 【0584】 Next, the device securely encrypts the collected data and sends it to a server in the cloud. The server analyzes the received biometric information using data analysis tools. Here, algorithms are used to identify normal patterns and signs of abnormalities, and a model is created of the health status of each individual user. 【0585】 Based on the analysis results, the server uses a plan generation mechanism to create a health management plan tailored to the user. For example, if the user is not getting enough exercise, the server might suggest walking three times a week and advise increasing protein intake in terms of diet. 【0586】 The generated health management plan is sent from the server to the user's smartphone via a notification system. This allows the user to receive specific advice for maintaining and improving their daily health. In addition, if an abnormality is detected, the server will quickly issue an alert and prompt the user to take appropriate action. 【0587】 Thus, the present invention enables easy and effective management of users' health by providing a consistent service from the acquisition of biometric information to the provision of health plans. 【0588】 The following describes the processing flow. 【0589】 Step 1: 【0590】 The device acquires the user's biometric information from the wearable device. This includes the number of steps the user takes in a day, heart rate during exercise, and activity data during sleep. The data is periodically transmitted to the device via Bluetooth or Wi-Fi. 【0591】 Step 2: 【0592】 The device stores the acquired biometric information in a database and encrypts it to maintain data integrity. The data is then securely uploaded to a server via the internet. 【0593】 Step 3: 【0594】 The server applies AI algorithms to analyze the received data. By comparing it with past data, it identifies normal and abnormal patterns and analyzes the user's health status and lifestyle. 【0595】 Step 4: 【0596】 The server generates a health management plan based on the analysis results. This plan includes specific suggestions regarding the type and frequency of exercise, ways to improve diet, and appropriate sleep patterns. 【0597】 Step 5: 【0598】 The server sends notifications to the user's device based on the generated health management plan and analysis results. This allows the user to receive specific advice on maintaining and improving their health in their daily life. 【0599】 Step 6: 【0600】 The server monitors the data using a continuous monitoring function and immediately sends an alert to the user if an anomaly is detected. This alert allows the user to quickly address the anomaly. 【0601】 (Example 1) 【0602】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0603】 Personal health management in modern society is becoming increasingly complex due to diverse lifestyles and environmental factors. Conventional health management systems suffer from insufficient real-time collection and analysis of biometric information, making it difficult to provide users with optimal health management plans. Furthermore, they struggle to respond quickly in the event of an abnormality. 【0604】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0605】 In this invention, the server includes information acquisition means for acquiring an individual's biometric information in real time; data transmission means for encrypting the biometric information and transmitting it via a communication network; data analysis means for decrypting and analyzing the biometric information and modeling the health status using a pattern recognition algorithm; plan generation means for generating an individual health management plan using a generated AI model based on the analyzed data; and notification means for notifying the user of the generated health management plan via a mobile communication device. This enables real-time collection and analysis of biometric information, rapid provision of personalized health management plans, and immediate alert generation in case of abnormalities. 【0606】 "Biometric information" refers to numerical values ​​and patterns that indicate the user's physical condition, including information such as heart rate, steps taken, and sleep patterns. 【0607】 "Information acquisition means" refers to devices and methods for collecting biometric information from users in real time, and includes wearable devices and sensors. 【0608】 "Data transmission means" refers to a technology or device that encrypts collected biometric information and transmits it to other devices or cloud servers via a communication network. 【0609】 "Data analysis means" refers to the process or technology of decoding received biometric information and modeling health status using a specific algorithm. 【0610】 "Plan generation means" refers to a method or system for creating individual health management plans using a generated AI model based on data analysis results. 【0611】 "Notification means" refers to a method or device for presenting generated health management plans and alerts in case of abnormalities to the user's device. 【0612】 The "alert function" is a mechanism that quickly alerts the user when an anomaly is detected during biometric information monitoring. 【0613】 A "wearable data collection device" is a device that, when worn by a user, can continuously collect data about their body. 【0614】 "Mobile communication devices" refer to devices such as smartphones and tablets that can communicate even while on the move. 【0615】 A "generative AI model" is an artificial intelligence model that includes algorithms used for data analysis and plan generation. 【0616】 This invention is a system for effectively managing an individual's health, utilizing various devices and data processing means to collect and analyze the user's biometric information in real time and provide a health management plan. 【0617】 First, the system uses a wearable device worn by the user as the terminal. This device collects biometric information such as heart rate, steps taken, and sleep patterns using sensors. A smartwatch is one example, which meticulously records the user's daily activities. This data is transferred to the user's smartphone via Bluetooth or Wi-Fi. 【0618】 Next, the device encrypts the biometric information received by the smartphone using encryption technology such as AES and sends it to a server in the cloud. The data arriving at the server is securely decrypted and analyzed using data analysis tools. Specifically, pattern recognition algorithms are used to model the user's normal health state, enabling the detection of anomalies. 【0619】 Based on the analyzed results, the server uses a generative AI model to generate a personalized health management plan. This plan provides optimal advice tailored to the user's lifestyle and health condition. For example, if a lack of exercise is detected, it might recommend walking three times a week or suggest ways to improve the nutritional balance of their diet. 【0620】 The generated health management plan is sent from the server to the user's smartphone via a notification system. Users can review and improve their daily habits based on the provided health management plan. In addition, if an abnormality is detected, the server will immediately issue a warning and, if necessary, send a notification prompting the user to seek medical attention. 【0621】 For example, if a user's heart rate is detected to be higher than normal one day, the device quickly transmits this information, the server determines it to be "temporary stress," and sends a notification to the user's smartphone recommending deep breathing. In this way, the user can take appropriate measures in real time. 【0622】 Examples of prompts for the generating AI model include: "Based on my current health data, please create exercise and nutrition advice. Include specific suggestions for insufficient exercise and dietary improvements." 【0623】 This invention enables users to easily understand their own health status and efficiently manage their health based on personalized advice. 【0624】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0625】 Step 1: 【0626】 The device acquires the user's biometric information in real time using a wearable device. Specifically, this includes heart rate, steps taken, and sleep patterns. This data is collected via sensors in the wearable device and transmitted to the user's smartphone via Bluetooth or Wi-Fi. At this stage, the input is the biometric information detected by the sensors, and the output is the biometric information sent to the smartphone. 【0627】 Step 2: 【0628】 The device encrypts biometric information using encryption technologies such as AES. The encrypted data is then transmitted to a server in the cloud via the internet. The input is the unprocessed biometric information present on the smartphone, and the output is the encrypted and transmitted biometric information. This process ensures that the data is transferred securely. 【0629】 Step 3: 【0630】 The server decrypts the received biometric information. This decryption is a crucial step preceding data analysis. Next, the server analyzes the decrypted information using data analysis tools. Pattern recognition algorithms are used for this analysis. The input is encrypted biometric information, and the output is the analysis result. Specifically, the server checks for normal patterns and signs of anomalies. 【0631】 Step 4: 【0632】 The server generates a health management plan using an AI model based on the analyzed data. The analysis results are input to the AI ​​as prompts, generating suggestions tailored to the individual's health condition. The input is the analysis results, and the output is a personalized health management plan. For example, if the system determines that the user is not getting enough exercise, an appropriate exercise plan will be generated. 【0633】 Step 5: 【0634】 The health management plan obtained from the server is sent to the user's smartphone by the server. The user is presented with the details of the plan using a notification method. The input is the generated health management plan, and the output is the notification message to the user. The user receives this notification and checks the health management advice that is appropriate for their daily life. 【0635】 Step 6: 【0636】 If an anomaly is detected, the server quickly generates an alert and warns the user. The input is the anomaly pattern detected during analysis, and the output is the warning message to the user. The user receives this warning and considers seeking medical attention if necessary. 【0637】 (Application Example 1) 【0638】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0639】 To effectively monitor the health status of the elderly and provide appropriate care support, it is necessary to collect and analyze biometric information in real time and provide continuous health management. However, current systems lack the functionality to efficiently aggregate this information and propose individualized health management plans. This creates a challenge in maintaining the health and providing care support for the elderly. 【0640】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0641】 In this invention, the server includes information acquisition means for collecting personal biometric data, data analysis means for analyzing the biometric data, plan generation means for generating individual health management plans based on the data analysis, monitoring means having an alert function for issuing warnings when abnormalities are detected, communication means for securely encrypting and transmitting the collected data, and support means for suggesting exercises and meals suitable for elderly care support. This enables real-time monitoring of the health status of elderly individuals, provision of individualized care plans, and rapid response in the event of abnormalities. 【0642】 "Information acquisition means" refers to devices and methods for collecting an individual's biometric data in real time. 【0643】 "Data analysis means" refers to methods and technologies for processing and analyzing acquired biological data to evaluate health status. 【0644】 "Plan generation method" refers to a method for automatically creating individual health management plans based on the results of data analysis. 【0645】 "Notification means" refers to methods or devices for communicating generated health management plans or warnings of abnormalities to the user. 【0646】 The "alert function" refers to a feature that issues a warning when an anomaly is detected through monitoring, prompting a quick response. 【0647】 "Monitoring means" refers to methods and devices for continuously observing biological data and determining whether or not there are any abnormalities. 【0648】 "Communication method" refers to a system for securely encrypting acquired biometric data and transmitting it to the necessary servers and devices. 【0649】 "Support measures" refer to methods and techniques for maintaining health, such as suggesting appropriate exercise and diet as part of care support for the elderly. 【0650】 To realize this invention, it is necessary to build a series of systems that collect, analyze, and utilize individual biometric data for health management. The terminal uses a wearable data collection device to collect the user's heart rate, steps, sleep patterns, etc., in real time. This data is securely encrypted and transmitted to a server in the cloud via a mobile communication device. 【0651】 The server analyzes data received on the cloud using data analysis tools. For example, it uses algorithms on collected heart rate data to evaluate an individual's health status and detect normal patterns and abnormalities. Based on the analysis results, the server generates a personalized health management plan and suggests exercise and diet plans suitable for the user. 【0652】 Furthermore, the server has a monitoring function that issues alerts if an anomaly is detected, quickly notifying users and caregivers via their terminals. This allows users to monitor their daily health status and respond immediately to any abnormalities. For example, it can be used to check whether elderly people are getting adequate exercise on a daily basis and, if insufficient exercise is detected, suggest increasing their walking. 【0653】 In the application of this invention, the use of a generative AI model is also being considered. As an example of a prompt, data can be input to the AI ​​model in the form of, "An 80-year-old user uses a health management app and, after obtaining a history of their daily activities, should be suggested an appropriate exercise program." 【0654】 In this way, detailed health management and early detection of abnormalities can be achieved for individual users, leading to overall health improvement. 【0655】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0656】 Step 1: 【0657】 The device collects biometric data such as heart rate, steps taken, and sleep patterns from the user via a wearable data collection device. This biometric data serves as input for initial processing on the device. After that, the data is encrypted and prepared for secure communication. 【0658】 Step 2: 【0659】 The device transmits encrypted data to a server in the cloud using a mobile communication device. The input is encrypted biometric data, and the data that reaches the server is subject to analysis. 【0660】 Step 3: 【0661】 The server processes the received biometric data using data analysis tools. It analyzes heart rate data, step count data, and other data based on algorithms to evaluate the user's specific health status. This involves recognizing data patterns and detecting anomalies. 【0662】 Step 4: 【0663】 Based on the analysis results, the server generates an individualized health management plan. This plan includes guidelines for appropriate exercise and diet, indicating the optimal health maintenance measures for the user. The generated plan is output. 【0664】 Step 5: 【0665】 The server sends the generated health management plan to the terminal via a notification system and presents it to the user. Here, the analysis results and the generated health management plan are prepared as notification content for the terminal. 【0666】 Step 6: 【0667】 The server continuously checks for data anomalies through monitoring mechanisms and uses an alert function to promptly warn terminals if an anomaly is detected. The input is real-time updated biometric data, and the output is an alert issued when an anomaly occurs. 【0668】 Step 7: 【0669】 Users can utilize the generated AI model to receive advice tailored to their health condition using prompt messages. Here, prompt messages are provided as input to the generated AI model, allowing the model to output specific health advice. 【0670】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0671】 This invention is a system that comprehensively manages an individual's health and mental state, combining biometric information with an emotion engine that recognizes the user's emotional state. This makes it possible to optimize both the user's physical and emotional health. 【0672】 First, the device continuously collects biometric and environmental information via the user's wearable device or smartphone. This collected data includes not only heart rate, activity level, and sleep quality, but also emotional data using daily voice and facial characteristics. This information is measured using sensors, microphones, and cameras on the device. 【0673】 Next, the device encrypts the collected information and sends it to a server in the cloud via the internet. The server uses machine learning algorithms and natural language processing to analyze the received data. This allows for the diagnosis of the user's health status and changes in emotions such as stress and well-being. 【0674】 Based on the analysis results, the server generates a personalized health management plan and a mental health support plan based on the user's emotional state. For example, if signs of stress are detected through increased heart rate and analysis of the emotional engine, the server will suggest deep breathing and meditation exercises to promote relaxation. 【0675】 The generated plan is sent from the server to the user's device via a notification system. This allows the user to receive specific advice to help with daily health management, stress reduction, and emotional stabilization. Furthermore, if the user's emotional state becomes unstable, the server can issue an alert and prompt them to consult a professional. 【0676】 In this way, this system, which combines an emotional engine, comprehensively supports users' emotional well-being along with their physical health, enabling lifestyle improvements and the maintenance of mental health. 【0677】 The following describes the processing flow. 【0678】 Step 1: 【0679】 The device acquires biometric information from the wearable device worn by the user. This data includes heart rate, steps taken, calories burned, and sleep patterns. It also uses the device's microphone and camera to collect emotional data from voice tone and facial expressions. 【0680】 Step 2: 【0681】 The device analyzes the collected data in real time and performs initial processing. It converts biometric and emotional data into the optimal format, encrypts the data, and then transfers it to the server via the internet. 【0682】 Step 3: 【0683】 The server uses AI algorithms to analyze the received data. It detects health patterns and anomalies from biometric information and identifies the user's emotional state from emotional data. For example, it analyzes signs of increased stress based on the user's normal heart rate. 【0684】 Step 4: 【0685】 The server generates personalized health and mental health plans based on analyzed biometric and emotional information. These plans include exercise, dietary adjustments, and stress management activities. For example, if emotional analysis indicates high stress levels, relaxation exercises will be recommended. 【0686】 Step 5: 【0687】 The server sends the generated plan to the user's device via a notification system. The user can then use this to manage their daily health and emotions. They might receive notifications recommending specific action plans, such as deep breathing exercises every morning or evening walks. 【0688】 Step 6: 【0689】 The server continuously monitors user data and sends an alert to the user if an anomaly is detected. This alert prompts the user to immediately seek help from a medical institution or mental health professional. 【0690】 (Example 2) 【0691】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0692】 In modern society, managing individual health and mental well-being is crucial, but traditional methods struggle to comprehensively support both physical and emotional health. Furthermore, the lack of real-time health monitoring and the provision of appropriate health management plans prevents effective support tailored to individual user needs. 【0693】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0694】 In this invention, the server includes information acquisition means for acquiring biometric and environmental information, data protection and transmission means for encrypting and transmitting the biometric and environmental information, data analysis means for analyzing the received information using a machine learning algorithm, plan generation means for generating individual health management and emotional state management plans based on the analysis results, and notification means for notifying the generated plans. This enables comprehensive support for the user's physical and emotional health, real-time monitoring of health status, and provision of effective health management plans. 【0695】 "Biometric information" refers to data that indicates an individual's health status, including physical data such as heart rate, activity level, and sleep quality. 【0696】 "Environmental information" refers to information about the situation in which the user is placed, and includes data on external factors such as surrounding audio and video data. 【0697】 "Information acquisition means" refers to a system or device for acquiring biometric information and environmental information, and includes hardware such as wearable devices and communication equipment. 【0698】 "Data protection and transmission means" refers to a mechanism or technology for protecting acquired information in accordance with security standards and transmitting it to a server or other device. 【0699】 "Data analysis means" refers to a series of processes and techniques for analyzing received information, and in particular includes means of processing data using machine learning algorithms to evaluate health status and emotional state. 【0700】 "Plan generation means" refers to methods and systems for creating health management plans and emotional state management plans optimized for the user based on analyzed data. 【0701】 "Notification means" refers to methods and systems for transmitting generated plans and information to users, and includes communication methods such as push notifications to terminals. 【0702】 This invention is a system for comprehensively managing an individual's health and emotional state, acquiring biometric and environmental information using wearable devices and smartphones. Specifically, the device acquires biometric information such as heart rate, activity level, and sleep quality in real time through sensors. It also collects voice and facial expression data using microphones and cameras and treats it as environmental information. 【0703】 The collected data is encrypted on the device and transmitted to the server via a secure communication protocol. The server analyzes the received data using machine learning algorithms and natural language processing techniques. The information obtained from the analysis is used to generate optimized health management plans and emotional management plans based on the user's health and emotional state. 【0704】 The generated plan is sent from the server to the user's device via push notification. This allows the user to receive real-time health and emotional advice, providing specific and effective support in their daily life. An example of a prompt might be, "Please suggest actions to take when the user's heart rate is recorded as higher than normal and signs of stress can be read from the emotional data." This allows the user to receive recommendations for deep breathing exercises or meditation, enabling them to work towards improving their health and emotional state. 【0705】 In this way, the present invention functions as a system that comprehensively supports the user's health and emotions, thereby improving their lifestyle and maintaining their mental health. 【0706】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0707】 Step 1: 【0708】 The terminal activates sensors on the user's wearable devices and smartphone to acquire biometric and environmental information. Inputs include signals from a heart rate sensor, data from an accelerometer, voice input from a microphone, and image data from a camera. Specifically, these devices periodically capture data and organize it into a format suitable for real-time analysis. The output is the acquired, raw biometric and environmental data dataset. 【0709】 Step 2: 【0710】 The terminal encrypts the acquired information using AES encryption for data protection. In this step, it receives the biometric and environmental data sets acquired in step 1 as input. Encryption ensures data confidentiality and prevents unauthorized access. The output is the encrypted data set. 【0711】 Step 3: 【0712】 The terminal uses a secure communication protocol (e.g., HTTPS) to send encrypted data to the server over the internet. The input here is the encrypted dataset. Specifically, the terminal uses a communication module to establish a connection with the server. The output is the data securely transferred to the server. 【0713】 Step 4: 【0714】 The server receives and decrypts encrypted data. It receives encrypted data sent from the terminal as input. After decryption, it analyzes the data using machine learning algorithms to evaluate the user's health and emotional state. The output is a health status report and emotional assessment based on the analysis results. 【0715】 Step 5: 【0716】 The server generates a health management plan and an emotional state management plan tailored to each user based on the analysis results. The input is the analysis results from step 4. Specifically, the server uses a generation AI model to generate personalized plans. The output is the generated health management plan and emotional state management plan. 【0717】 Step 6: 【0718】 The server sends the generated plan to the user's device via push notification. The input is the plan generated in step 5. Specifically, the server uses a notification system to send alerts to the user's device in real time. The output is specific advice on the user's health and emotional state. 【0719】 (Application Example 2) 【0720】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0721】 In modern society, personal health management and mental health improvement are crucial issues. However, traditional methods often manage physical health and emotional state separately, and there are few systems that integrate and analyze data from both areas to provide accurate advice. Furthermore, there is a lack of support methods that can respond to stress and emotional changes in real time. Solving these challenges is essential. 【0722】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0723】 In this invention, the server includes information acquisition means for collecting an individual's biometric and emotional data, data analysis means for analyzing the biometric and emotional data, and plan generation means for generating individual health management plans and emotional management plans based on the data analysis. This makes it possible to comprehensively manage the user's health and emotional state and provide appropriate advice through a home device. 【0724】 "Personal biometric information" refers to data measured to indicate a person's physical condition, such as heart rate, activity level, and sleep quality. 【0725】 "Emotional data" refers to data that indicates an individual's emotional state, based on information obtained from sources such as voice and facial expressions. 【0726】 "Information acquisition means" refers to a device or method for collecting an individual's biometric information or emotional data. 【0727】 "Data analysis means" refers to a device or method for analyzing collected biometric information and emotional data to evaluate health status and emotional state. 【0728】 "Plan generation means" refers to an apparatus or method for creating individual health management plans and emotional management plans based on analysis results. 【0729】 "Notification means" refers to a device or method for informing the user of the generated health management plan and emotional management plan. 【0730】 "Household appliances" refer to devices or methods used in a home environment to make suggestions based on individual emotional data. 【0731】 This invention is a system for the integrated management of an individual's health and emotional state. Users collect biometric and emotional data in their daily lives using wearable devices and smartphones. This data includes heart rate, activity level, sleep quality, and emotional data such as voice and facial expressions. This data is measured by sensors in the wearable device and by the smartphone's microphone and camera. 【0732】 The device encrypts the collected data and securely transmits it to a server in the cloud. The server uses machine learning libraries and natural language processing libraries (e.g., TensorFlow and NLTK) based on Python to analyze biometric and emotional data. This allows for real-time evaluation of the user's health status and emotional changes, and generates personalized health and emotional management plans. 【0733】 The generated plan is sent to the user's device via a notification system from the server. Based on the received notification, the user can receive advice that helps with daily health management and emotional stabilization. Furthermore, if the server determines that the user's emotional state is unstable, it will also provide support by utilizing home devices to suggest relaxation techniques based on emotional data. 【0734】 For example, if the device detects a stressed state from emotional data along with a sudden change in the user's heart rate, the server will suggest, "Shall we play some relaxing music?" via the home device. Furthermore, using a generative AI model, it can generate and suggest responses when the user asks, "What kind of relaxing activities would be good for the weekend?" An example of a prompt might be, "Please suggest some relaxing activities for the weekend." 【0735】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0736】 Step 1: 【0737】 The device collects biometric and emotional data via wearable devices and smartphones. Specifically, it obtains heart rate, activity level, and sleep quality from sensors, and captures voice and facial expression data with the smartphone's microphone and camera. This input data is then processed and formatted in preparation for the next stage of processing. 【0738】 Step 2: 【0739】 The device encrypts the collected data and securely transmits it to the server over the internet. This process utilizes security protocols to maintain data confidentiality. The transmitted data is then input into the server's data analysis module. 【0740】 Step 3: 【0741】 The server analyzes the received data using machine learning algorithms and natural language processing techniques. Specifically, it uses the TensorFlow library to estimate stress levels and health status from biometric information, and the NLTK library to evaluate the tone and trends of emotional data. As a result of the analysis, a report is generated showing the user's health status assessment and emotional progression. 【0742】 Step 4: 【0743】 The server generates a personalized plan for the user's health and emotional management based on the analysis results. The generating AI model uses the suggested prompts to incorporate specific health activities and emotional stabilization measures into the plan. The resulting plan becomes customized advisory content for each user. 【0744】 Step 5: 【0745】 The server notifies the terminal of the generated health management plan and emotional management plan. The terminal presents the received plan to the user and allows them to utilize support tools from home devices. When the user senses stress, it makes specific suggestions such as, "Shall we play some relaxing music?" 【0746】 Step 6: 【0747】 Users begin taking actions to care for their health and mental well-being based on the provided plan. By following the plan, users are expected to experience improved health and mental state. Furthermore, by utilizing a generative AI model, the system responds to additional questions from the user, using "Please suggest some relaxing activities for the weekend" as an example prompt. 【0748】 The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0749】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0750】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0751】 Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion. 【0752】 Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together. 【0753】 These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression. 【0754】 The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become. 【0755】 Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant. 【0756】 The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more." 【0757】 The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values. 【0758】 The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format. 【0759】 In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data. 【0760】 In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56. 【0761】 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. 【0762】 Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56. 【0763】 The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using this memory. 【0764】 The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor. 【0765】 Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources. 【0766】 Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose. 【0767】 The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above. 【0768】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference. 【0769】 The following is further disclosed regarding the embodiments described above. 【0770】 (Claim 1) 【0771】 Information acquisition means for collecting personal biometric information, 【0772】 A data analysis means for analyzing the aforementioned biological information, 【0773】 A plan generation means that generates individual health management plans based on the aforementioned data analysis, 【0774】 A notification means for presenting the generated health management plan, 【0775】 A system that includes this. 【0776】 (Claim 2) 【0777】 The system according to claim 1, further comprising monitoring means for detecting abnormalities in the aforementioned biological information, and having an alert function that issues a warning when an abnormality is detected. 【0778】 (Claim 3) 【0779】 The system according to claim 1, characterized in that the information acquisition means acquires biometric information via a wearable data collection device and a mobile communication device. 【0780】 "Example 1" 【0781】 (Claim 1) 【0782】 A means of acquiring information to obtain an individual's biometric information in real time, 【0783】 A data transmission means for encrypting the aforementioned biometric information and transmitting it over a communication network, 【0784】 A data analysis means for decoding and analyzing the aforementioned biological information and modeling the health status using a pattern recognition algorithm, 【0785】 A plan generation means that generates individual health management plans using a generated AI model based on the analyzed data, 【0786】 A notification means for notifying the user of the generated health management plan via a mobile communication device, 【0787】 A system that includes this. 【0788】 (Claim 2) 【0789】 The system according to claim 1, characterized in that it has an alert function that monitors the aforementioned biological information and promptly issues a warning when an abnormality is detected. 【0790】 (Claim 3) 【0791】 The system according to claim 1, characterized in that it acquires biometric information using a wearable data collection device and presents specific health maintenance measures using a generating AI model based on the analyzed information. 【0792】 "Application Example 1" 【0793】 (Claim 1) 【0794】 Information acquisition methods for collecting personal biometric data, 【0795】 A data analysis means for analyzing the aforementioned biological data, 【0796】 A plan generation means for generating individual health management plans based on the aforementioned data analysis, 【0797】 A notification means for presenting the generated health management plan, 【0798】 A monitoring means having an alert function that issues a warning when an abnormality is detected, 【0799】 A means of communication for securely encrypting and transmitting the collected data, 【0800】 Support methods that offer suggestions for exercise and diet suitable for elderly care support, 【0801】 A system that includes this. 【0802】 (Claim 2) 【0803】 The system according to claim 1, characterized in that the information acquisition means acquires biological data via a wearable data collection device and a mobile communication device. 【0804】 (Claim 3) 【0805】 The system according to claim 1, characterized by generating individualized care plans tailored to the health condition of elderly individuals. 【0806】 "Example 2 of combining an emotion engine" 【0807】 (Claim 1) 【0808】 Information acquisition means for acquiring biological information and environmental information, 【0809】 Data protection and transmission means for encrypting and transmitting the aforementioned biometric and environmental information, 【0810】 A data analysis means for analyzing the received information using a machine learning algorithm, 【0811】 A plan generation means that generates individual health management and emotional state management plans based on the aforementioned analysis results, 【0812】 A notification means for notifying the generated plan, 【0813】 A system that includes this. 【0814】 (Claim 2) 【0815】 The system according to claim 1, further comprising monitoring means for detecting abnormalities in biological information acquired by the information acquisition means, and having an alert function that issues a warning when an abnormality is detected. 【0816】 (Claim 3) 【0817】 The system according to claim 1, characterized in that the information acquisition means acquires biological information and environmental information via a portable data collection device and a communication device. 【0818】 "Application example 2 when combining with an emotional engine" 【0819】 (Claim 1) 【0820】 Information acquisition means for collecting personal biometric information and emotional data, 【0821】 Data analysis means for analyzing the aforementioned biometric information and emotional data, 【0822】 A plan generation means that generates individual health management plans and emotional management plans based on the aforementioned data analysis, 【0823】 A notification means for presenting the generated health management plan and emotional management plan, 【0824】 A support method that uses home devices to provide suggestions based on emotional data, 【0825】 A system that includes this. 【0826】 (Claim 2) 【0827】 The system according to claim 1, further comprising monitoring means for detecting anomalies in the biometric information and emotional data, and having an alert function for issuing a warning when an anomaly is detected. 【0828】 (Claim 3) 【0829】 The system according to claim 1, characterized in that the information acquisition means acquires biometric information and emotional data via a wearable data collection device and a mobile communication device. [Explanation of symbols] 【0830】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] Information acquisition means for collecting personal biometric information, A data analysis means for analyzing the aforementioned biological information, A plan generation means that generates individual health management plans based on the aforementioned data analysis, A notification means for presenting the generated health management plan, A system that includes this. [Claim 2] The system according to claim 1, further comprising monitoring means for detecting abnormalities in the aforementioned biological information, and having an alert function that issues a warning when an abnormality is detected. [Claim 3] The system according to claim 1, characterized in that the information acquisition means acquires biometric information via a wearable data collection device and a mobile communication device.

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