System

Abstract

A system is provided.SOLUTION: A system, comprising: means for collecting daily vital data from a wearable terminal; means for transmitting the vital data to a terminal; means for the terminal to transmit the vital data to a server; means for the server to integrate and analyze the vital data; means for generative artificial intelligence to generate a personalized life-style improvement proposal based on the integrated and analyzed vital data; and means for transmitting the generated life-style improvement proposal to the terminal to present it to a user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The present invention aims to provide an effective solution to the problem of a lack of appropriate health management methods for preventing lifestyle-related diseases such as diabetes and preventing their progression. Conventional methods have made it difficult to obtain lifestyle improvement plans suited to each individual, and also to maintain motivation to implement such plans. As a result, many potential patients and patients are unable to manage their health effectively, often resulting in a worsening of their condition. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems with the following configuration: A system including means for collecting daily vital data from a wearable device, means for transmitting the vital data to the device, means for the device to transmit the vital data to a server, means for the server to integrate and analyze the vital data, means for a generative artificial intelligence to generate personalized lifestyle improvement suggestions based on the integrated and analyzed vital data, and means for transmitting the generated lifestyle improvement suggestions to the device and presenting them to the user, can quickly and efficiently provide lifestyle improvement suggestions suited to individual users, thereby achieving effective health management.

[0006] A "wearable device" refers to a device that is worn on the body and collects daily vital data in real time.

[0007] "Vital data" refers to various data that reflect health and biological conditions, such as heart rate, amount of exercise, diet, sleep data, and stress level.

[0008] "Terminal" refers to a mobile device such as a smartphone or tablet that relays data sent from a wearable terminal and sends it to a server.

[0009] "Server" refers to a computer system that receives, integrates, and analyzes vital data sent from a device.

[0010] "Generative AI" refers to algorithms and models that analyze received vital data and generate lifestyle improvement suggestions suited to individual users.

[0011] "Lifestyle Improvement Suggestions" refers to specific diet, exercise, sleep, and stress management recommendations provided to improve a user's health.

[0012] "Personalized" means that it is customized based on the user's individual vital data and lifestyle.

[0013] "Presenting" refers to informing the user of the generated lifestyle improvement suggestions through screen display or notification functions. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0018] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0019] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0034] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0035] The present invention provides lifestyle improvement suggestions based on individual vital data using a system including a wearable device, a terminal, a server, and a generating artificial intelligence. Hereinafter, an embodiment of the present invention will be described in detail.

[0036] Users wear a wearable device in their daily lives. The device collects various vital data in real time, such as heart rate, exercise volume, dietary intake, sleep data, and stress levels. For example, when a user eats breakfast, the device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0037] The vital data collected by the wearable device is sent to the user's device (a mobile device such as a smartphone or tablet) via Bluetooth or Wi-Fi. The device then sends this data to a server at regular intervals. For example, the data is uploaded at the end of each day or after a specific event.

[0038] The server integrates and centrally manages the received vital data. The server is equipped with generative artificial intelligence that analyzes the integrated data. For example, it analyzes a user's exercise and diet data over the course of a week to detect patterns and abnormal values.

[0039] Based on the analysis results, the AI ​​generates personalized lifestyle improvement recommendations for each user, including specific instructions for diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods you eat at breakfast from now on" and exercise advice such as "Do 30 minutes of aerobic exercise every night" are generated.

[0040] The generated lifestyle improvement suggestions are sent from the server to the user's device, where they are presented to the user. The device displays the feedback in a visually easy-to-understand format, indicating the specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as, "Your recent dietary habits need improvement. Please check for detailed instructions."

[0041] After the user takes the recommended action based on the feedback, the wearable device again collects new vital signs and sends them back to the server. The generative AI re-evaluates the data to determine the effectiveness of the improvements and provides further feedback as needed, providing ongoing support for the user's health management.

[0042] The system of the present invention effectively utilizes individual vital data and provides lifestyle improvement suggestions tailored to each user, thereby contributing to the prevention of lifestyle-related diseases such as diabetes and their progression to more serious conditions. Furthermore, because the entire system functions in real time, it is possible to maintain the user's motivation in their daily lives and have their behavior reflected immediately.

[0043] The processing flow will be explained below.

[0044] Step 1:

[0045] Users wear a wearable device in their daily lives, which collects vital data such as heart rate, exercise volume, dietary intake, sleep data, and stress levels in real time. For example, when a user eats breakfast, the wearable device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0046] Step 2:

[0047] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. Once the device is connected, data is automatically synchronized. For example, heart rate and exercise data are sent to the device in real time.

[0048] Step 3:

[0049] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed.

[0050] Step 4:

[0051] The server integrates the received vital data and manages it centrally. For example, it integrates heart rate data, exercise data, dietary data, sleep data, and stress data and manages them as a single data set.

[0052] Step 5:

[0053] The server-based generative artificial intelligence analyzes the integrated vital data. For example, it analyzes data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume.

[0054] Step 6:

[0055] Based on the analysis results, the AI ​​generates personalized lifestyle improvement suggestions suited to each individual user. For example, if it determines that the user is not getting enough exercise, it will generate specific instructions such as "recommended 30 minutes of walking on the weekend." It also generates advice on diet and suggestions for improving sleep.

[0056] Step 7:

[0057] The server sends the generated lifestyle improvement suggestions to the device, which receives them and presents them to the user in a visually easy-to-understand format. For example, a notification function can be used to provide real-time feedback such as, "Your recent dietary habits need improvement. Please check for detailed instructions."

[0058] Step 8:

[0059] Based on the feedback, the user performs the recommended action, such as walking or exercising, and then the data is collected again by the wearable device.

[0060] Step 9:

[0061] The device then sends the newly collected vital data back to the server, which receives it and analyzes it again using the artificial intelligence.

[0062] Step 10:

[0063] The generative AI reassess the new vital data and determines whether improvements or new guidance are needed. For example, it evaluates the patient's condition after walking and provides feedback such as, "Your blood sugar level has improved. Continue to maintain good lifestyle habits."

[0064] Example 1

[0065] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0066] As the need for prevention and management of lifestyle-related diseases increases in modern times, there is a need to effectively utilize individual vital signs data and provide users with appropriate lifestyle improvement suggestions. However, existing systems do not adequately collect data in real time or provide personalized improvement suggestions, making it difficult to continuously support users' health management.

[0067] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0068] In this invention, the server includes a means for integrating and analyzing the received vital data and detecting patterns and abnormal values, a means for a generating artificial intelligence to generate personalized lifestyle improvement suggestions based on the integrated and analyzed vital data, and a means for re-evaluating the user's behavioral data and providing further feedback as necessary. This makes it possible to collect and analyze individual vital data in real time and provide the user with continuous and personalized lifestyle improvement suggestions.

[0069] A "wearable device" is a device worn by a user to collect vital data such as heart rate, exercise volume, dietary habits, sleep data, and stress levels in real time.

[0070] "Vital data" refers to data that indicates the user's physical and physiological condition, such as heart rate, amount of exercise, dietary content, sleep data, and stress level.

[0071] A "terminal" is a device that receives vital data sent from a wearable device and sends it to a server. Examples of such devices include smartphones and tablets.

[0072] The "server" is a computer system that consolidates and analyzes vital data sent from devices and detects patterns and abnormal values.

[0073] "Generative AI" is an AI model that generates individual lifestyle improvement suggestions based on integrated and analyzed vital data.

[0074] "Lifestyle Improvement Suggestions" are suggestions for improving the user's lifestyle, including specific instructions regarding diet, exercise, sleep, and stress management.

[0075] The "notification function" is a function that allows the device to visually present improvement suggestions and feedback to the user in real time.

[0076] "Feedback" is further instruction or advice provided to a user after they have taken a recommended action, based on additional data analysis.

[0077] The present invention provides lifestyle improvement suggestions based on individual vital data using a system including a wearable device, a terminal, a server, and a generating artificial intelligence. An embodiment of this system will be specifically described below.

[0078] Users wear a wearable device in their daily lives. The device collects various vital data in real time, such as heart rate, exercise volume, dietary intake, sleep data, and stress level. For example, when a user eats breakfast, the wearable device records the time and content of the meal. It also continuously collects data while the user is exercising or sleeping.

[0079] The vital data collected by the wearable device is sent to the user's device (a mobile device such as a smartphone or tablet) via Bluetooth or Wi-Fi. The device then sends the data to a server at regular intervals. For example, the data is uploaded at the end of each day or after a specific event.

[0080] The server uses cloud servers such as Amazon Web Services (AWS) and Google Cloud Platform (GCP) to integrate and centrally manage the received vital signs. The server is equipped with a generative artificial intelligence (AI model) that analyzes the integrated data and detects patterns and outliers. For example, it analyzes a user's exercise and diet data over the course of a week to detect lack of exercise or an unbalanced diet.

[0081] Based on the analysis results, the generative AI generates personalized lifestyle improvement suggestions for each user. These include specific instructions regarding diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods you eat at breakfast from now on" or exercise advice such as "Do 30 minutes of aerobic exercise every night" is generated. The generated lifestyle improvement suggestions are sent from the server to the user's device, where they are presented to the user. The device displays feedback in a visually easy-to-understand format, indicating specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as "Your recent dietary habits need improvement. Please check for detailed instructions."

[0082] After the user takes the recommended action based on the feedback, the wearable device again collects new vital signs and sends them back to the server. The generative AI re-evaluates the data to determine the effectiveness of the improvements and provides further feedback as needed, providing ongoing support for the user's health management.

[0083] Prompt Sentence Examples

[0084] "Please suggest appropriate exercise habits based on the user's exercise data for the week."

[0085] "Analyze the user's dietary data and generate recommendations for future dietary improvements."

[0086] The system of the present invention effectively utilizes individual vital data and provides lifestyle improvement suggestions tailored to the user, thereby contributing to the prevention of lifestyle-related diseases and maintaining motivation. In addition, because the entire system functions in real time, it is possible to immediately reflect the user's daily behavior.

[0087] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0088] Step 1:

[0089] Users wear a wearable device while going about their daily lives, and the device collects vital data such as heart rate, exercise volume, dietary habits, sleep data, and stress levels in real time.

[0090] Input: User activities

[0091] Data processing and output: Collected vital data is recorded in real time.

[0092] Step 2:

[0093] The vital data collected by the wearable device is sent to the user's device via Bluetooth or Wi-Fi.

[0094] Input: Vital data from a wearable device

[0095] Data processing and output: Vital data is periodically aggregated and transmitted to the device.

[0096] Step 3:

[0097] The terminal transmits the vital data received from the wearable terminal to the server at regular intervals.

[0098] Input: Vital data from a wearable device

[0099] Data processing and output: Organize data in the device and convert it into a format to send to the server.

[0100] Step 4:

[0101] The server integrates and centralizes the vital data it receives. The server is equipped with a generative artificial intelligence (AI model) that analyzes the integrated data to detect patterns and outliers.

[0102] Input: Vital data sent from the device

[0103] Data processing and output: Data is integrated and analyzed by AI models, and any patterns or anomalies detected are recorded.

[0104] Step 5:

[0105] Based on the analysis results, the generative artificial intelligence generates personalized lifestyle improvement suggestions.

[0106] Input: Integrated and analyzed data

[0107] Data processing and output: Generate lifestyle improvement suggestions based on the analysis results.

[0108] Step 6:

[0109] The server sends the generated lifestyle improvement suggestions to the terminal.

[0110] Input: AI-generated improvement suggestions

[0111] Data processing and output: Convert the improvement proposal into a format that can be sent to the terminal and send it.

[0112] Step 7:

[0113] The device presents improvement suggestions to the user in a visually easy-to-understand format.

[0114] Input: Improvement suggestions sent from the server

[0115] Data processing and output: Display improvement proposals in a format suitable for the user interface.

[0116] Step 8:

[0117] The user takes the recommended action based on the feedback, and the wearable device again collects new vital signs.

[0118] Input: User action

[0119] Data Processing and Output: New vital data is collected.

[0120] Step 9:

[0121] The device sends new vital data to the server, where the AI ​​reassess it, determines the effectiveness of any improvements, and provides further feedback as needed.

[0122] Input: New vitals

[0123] Data processing and output: Reassess the data and generate / send new feedback as needed.

[0124] (Application example 1)

[0125] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0126] While conventional wearable devices are effective for collecting vital data and improving lifestyle habits for individuals, they have not been applied to monitoring the health status and improving the efficiency of equipment in certain industries, particularly factories. Therefore, there is a need to monitor the health status of factory equipment in the same way as humans and provide specific improvement suggestions.

[0127] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0128] In this invention, the server comprises: means for collecting daily vital data from the wearable terminal; means for transmitting the vital data to the terminal; means for the terminal to transmit the vital data to the server; means for the server to integrate and analyze the vital data; means for a generating artificial intelligence to generate personalized lifestyle improvement suggestions based on the integrated and analyzed vital data; and means for transmitting the generated lifestyle improvement suggestions to the terminal and presenting them to the user.

[0129] a means for collecting operation data of the equipment from sensors attached to the equipment in the factory and analyzing the operation data;

[0130] A means for generating specific improvement plans to improve the operating efficiency of factory equipment based on the analyzed operation data by the generating artificial intelligence;

[0131] and a means for transmitting the generated improvement plan to a terminal of a factory manager and presenting it to the manager. This makes it possible to manage the health of users and improve the operating efficiency of factory equipment.

[0132] A "wearable device" is a device worn on the body to collect physiological data of the user.

[0133] "Vital data" refers to physiological data related to the health status of a user.

[0134] A "terminal" is an electronic device for receiving and processing vital data transmitted from a wearable terminal.

[0135] A "server" is a central control computer that integrates and analyzes data sent from the terminals.

[0136] "Generative AI" is an AI (artificial intelligence) technology that analyzes collected data and generates feedback and improvement suggestions tailored to specific purposes.

[0137] "Lifestyle improvement proposals" are specific action proposals that instruct changes or improvements to lifestyle habits, proposed based on vital data.

[0138] "Factory equipment" refers to industrial machines and devices used in production lines and work processes.

[0139] A "sensor" is a device that is attached to factory equipment and collects various operational data in real time.

[0140] "Operation data" refers to operational data generated when factory equipment is in operation.

[0141] "Improvement proposals" are specific instructions or suggestions for improving the operating efficiency of equipment based on analyzed data.

[0142] The "factory manager's terminal" is an electronic device used by the factory manager, and is a device for receiving and viewing improvement proposals.

[0143]

[0144] The present invention provides a system for integrating and analyzing data collected from wearable devices and sensors attached to factory equipment, thereby improving lifestyle habits and increasing the operating efficiency of factory equipment. A specific configuration for implementing the present invention will be described below.

[0145] First, the user puts on a wearable device, which collects various vital data in real time, such as heart rate, exercise volume, dietary habits, sleep data, and stress levels. The collected vital data is then sent to the user's smartphone, tablet, or other device via Bluetooth or Wi-Fi.

[0146] In factories, multiple sensors are attached to equipment to collect operational data in real time, such as temperature, vibration, operating frequency, and power consumption, which is also sent to a central server via the factory network.

[0147] The wearable device periodically transmits vital data collected from the device to a cloud server. The server is equipped with a generative artificial intelligence (generative AI model) that integrates and analyzes the received data. Based on the vital data, it generates specific improvement proposals to improve the user's lifestyle habits, and based on the operational data, it generates specific improvement proposals to improve the operating efficiency of equipment.

[0148] For example, by analyzing a week's worth of exercise and dietary data, the system can generate specific instructions for the user, such as "Increase the amount of high-protein foods you eat for breakfast in the future." It can also generate specific instructions for factory equipment, such as "The vibrations are too strong, so we recommend maintenance."

[0149] The generated improvement proposals are sent from the server to the user's device and the factory manager's device. The user and manager receive easy-to-understand visual feedback through their devices. For example, the user's device may receive a notification saying, "Your recent eating habits need improvement. Please check for detailed instructions." The factory manager's device may receive a notification saying, "We have detected an abnormality in Robot No. 1's motor temperature, exceeding 80 degrees. Please instruct immediate maintenance of the cooling system and motor."

[0150] To implement this system, the following hardware and software are used.

[0151] Hardware: Wearable devices, various sensors, smartphones, tablets, factory network equipment, and servers.

[0152] Software: Data collection module, cloud storage, generative artificial intelligence platform (e.g., Google Cloud AI, AWS SageMaker, Azure Machine Learning), feedback sharing app.

[0153] As a concrete example, if the sensor detects that the robot's motor temperature has exceeded 80 degrees, the prompt text would be as follows:

[0154] Prompt: "Robot #1's motor temperature has been detected to be above 80 degrees. Order immediate maintenance on the cooling system and motor."

[0155] In this way, the system of the present invention can continuously support user health management and improved operating efficiency of factory equipment by using wearable devices and factory sensors.

[0156] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0157] Step 1:

[0158] The user wears a wearable device, which collects various vital data in real time, such as heart rate, exercise volume, dietary content, sleep data, and stress level. The collected data is sent to the user's smartphone or tablet via Bluetooth or Wi-Fi. The input is the user's vital data, and the output is data sent to the device.

[0159] Step 2:

[0160] In factories, sensors attached to equipment collect operational data such as temperature, vibration, operating frequency, and power consumption in real time. The collected data is sent to a server via the factory network. The input is the equipment's operational data, and the output is data sent to the server.

[0161] Step 3:

[0162] The device periodically transmits vital data collected from the wearable device to a cloud server. The input is the vital data stored on the device, and the output is data sent to the cloud server.

[0163] Step 4:

[0164] The server integrates the vital data and operating data sent from the wearable devices and sensors and stores them in cloud storage. The input is the data sent to the server, and the output is the storage of the integrated data.

[0165] Step 5:

[0166] A generative artificial intelligence (generative AI model) installed on the server analyzes the integrated vital data and operational data. It generates lifestyle improvement suggestions based on the user's health condition, as well as improvement suggestions to improve the operating efficiency of the equipment. The input is the integrated data, and the output is improvement suggestions.

[0167] Step 6:

[0168] The generated improvement proposals are sent from the server to the user terminal and the factory manager's terminal. The input is the generated improvement proposal, and the output is the data sent to the terminal.

[0169] Step 7:

[0170] The user's device and the factory manager's device display improvement proposals in a visually easy-to-understand format and provide real-time feedback using a notification function. Specifically, the user's device displays a notification such as, "Your recent diet needs improvement. Please check for detailed instructions." The factory manager's device displays a notification such as, "An abnormality has been detected in Robot No. 1's motor temperature, exceeding 80 degrees. Please instruct immediate maintenance of the cooling system and motor." The input is improvement proposal data from the server, and the output is notifications to the user and factory manager.

[0171] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0172] The present invention provides lifestyle improvement suggestions based on individual vital data and emotion data using a system including a wearable device, a terminal, a server, generative artificial intelligence, and an emotion engine. The following describes specific embodiments of the present invention.

[0173] Users wear a wearable device in their daily lives. The device collects various vital data in real time, such as heart rate, exercise volume, dietary intake, sleep data, and stress levels. For example, when a user eats breakfast, the device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0174] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. When the device is connected, data is automatically synchronized. For example, heart rate and exercise volume data are sent to the device in real time.

[0175] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed.

[0176] The server integrates and centrally manages the received vital data. The server is equipped with generative artificial intelligence, which analyzes the integrated data. For example, it analyzes the user's data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume.

[0177] Based on the analysis results, the AI ​​generates personalized lifestyle improvement recommendations for each user, including specific instructions for diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods you eat at breakfast from now on" and exercise advice such as "Do 30 minutes of aerobic exercise every night" are generated.

[0178] Furthermore, the emotion engine recognizes the user's emotions. The emotion engine analyzes data such as the user's facial expressions, tone of voice, and physical movements to grasp the user's emotional state at that time. For example, while the user is operating the smartphone, the camera captures the face and analyzes the voice to determine emotions such as stress or joy.

[0179] The emotion data recognized by the emotion engine is also sent to the server, and the artificial intelligence combines it with vital data to generate further lifestyle improvement suggestions. For example, if stress levels are high, it will generate suggestions for relaxation exercises or advice on reconsidering the timing of work breaks.

[0180] The generated lifestyle improvement suggestions and emotional feedback are sent from the server to the user's device, where they are presented to the user. The device displays the feedback in a visually easy-to-understand format, suggesting specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as, "Your stress level seems high. Try doing some relaxation exercises."

[0181] After the user takes the recommended action based on the feedback, the wearable device again collects new vital data, which is again sent to the server via the device. The emotion engine also periodically collects emotional data and similarly sends it to the server. The generative AI reevaluates this data to determine the effectiveness of improvements and provides further feedback as needed. This provides ongoing support for the user's health management.

[0182] The system of the present invention effectively utilizes individual vital data and emotional data to provide lifestyle improvement suggestions tailored to the user, thereby contributing to the prevention of lifestyle-related diseases such as diabetes and their progression to more serious conditions. Furthermore, because the entire system functions in real time, it is possible to maintain the user's motivation in their daily lives and have their behavior reflected immediately.

[0183] The processing flow will be explained below.

[0184] Step 1:

[0185] Users wear a wearable device in their daily lives, which collects vital data such as heart rate, exercise volume, dietary intake, sleep data, and stress levels in real time. For example, when a user eats breakfast, the wearable device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0186] Step 2:

[0187] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. Once the device is connected, data is automatically synchronized. For example, heart rate and exercise data are sent to the device in real time.

[0188] Step 3:

[0189] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed.

[0190] Step 4:

[0191] The server integrates and centrally manages the received vital data, for example, heart rate data, exercise data, dietary data, sleep data, and stress data, and manages them as a single data set.

[0192] Step 5:

[0193] The server-based generative artificial intelligence analyzes the integrated vital data. For example, it analyzes data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume.

[0194] Step 6:

[0195] Based on the analysis results, the AI ​​generates personalized lifestyle improvement suggestions suited to each individual user. For example, if it determines that the user is not getting enough exercise, it will generate specific instructions such as "recommended 30 minutes of walking on the weekend." It also generates advice on diet and suggestions for improving sleep.

[0196] Step 7:

[0197] The device uses an emotion engine to recognize the user's emotions and collects emotion data from the user's facial expressions, tone of voice, and body movements. For example, if the user is feeling stressed, the emotion engine will detect this.

[0198] Step 8:

[0199] The emotional data collected by the device is sent to a server, where it is centrally managed and analyzed in combination with vital data. For example, it can analyze the time periods and situations in which the user feels stressed.

[0200] Step 9:

[0201] The generative AI will then analyze the emotional and vital data to generate more specific lifestyle improvement recommendations, such as "Perform relaxation exercises every night to reduce stress."

[0202] Step 10:

[0203] The server then sends the lifestyle improvement suggestions it has generated to the device, which then presents them to the user and displays feedback in a visually easy-to-understand format. For example, real-time feedback such as "Your stress level seems high. Try some relaxation exercises" is provided.

[0204] Step 11:

[0205] The user performs the recommended action based on the feedback, such as walking or exercising, and then the data is collected again by the wearable device.

[0206] Step 12:

[0207] The device again transmits the newly collected vital data and emotional data to the server, which receives it and analyzes it again using the artificial intelligence.

[0208] Step 13:

[0209] The generative AI reassess the new vital and emotional data to determine whether improvements or new guidance are needed. For example, it evaluates the patient's condition after a walk and provides feedback such as, "Your blood sugar level has improved. Continue to maintain good lifestyle habits."

[0210] Example 2

[0211] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0212] Conventional health management systems can only provide static advice based on a user's vital signs, and lack a dynamic approach that takes into account the user's emotional state. Furthermore, due to insufficient real-time feedback, it is difficult to provide timely improvement suggestions that are tailored to the user's daily life.

[0213] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for integrating and analyzing vital data, means for a generating artificial intelligence to generate personalized lifestyle improvement suggestions, means for an emotion engine to collect and analyze emotion data, and means for combining the emotion data with vital data to generate additional lifestyle improvement suggestions. This makes it possible to analyze the user's vital data and emotion data in an integrated manner, and to provide more personalized and appropriate lifestyle improvement suggestions in real time that are tailored to the user's health condition and emotions.

[0214] A "wearable device" is a compact electronic device that can be worn by the user and collects vital data such as heart rate, exercise volume, dietary content, sleep data, and stress level in real time.

[0215] "Vital data" refers to basic physiological data necessary to understand a user's health condition, and specifically refers to data such as heart rate, amount of exercise, diet, sleep data, and stress level.

[0216] A "terminal" is an electronic device that receives collected vital data from a user's wearable device, synchronizes the data, and transmits the data to a server, and includes smartphones, tablets, etc.

[0217] The "server" is a computer system that integrates and analyzes vital data and emotional data sent from terminals via the Internet.

[0218] "Generative AI" refers to an AI program that analyzes collected vital data and generates personalized lifestyle improvement suggestions.

[0219] An "emotion engine" refers to software or hardware that analyzes a user's emotional state from facial expressions, tone of voice, physical movements, etc., and collects this as emotional data.

[0220] "Personalized lifestyle changes" refers to specific suggestions for diet, exercise, sleep, and stress management that are generated based on a user's individual vital and emotional data.

[0221] "Emotion data" refers to data that indicates the user's emotional state, and is obtained by analyzing facial expressions, tone of voice, body movements, and the like using an emotion engine.

[0222] The present invention provides lifestyle improvement suggestions based on individual vital data and emotional data using a system including a wearable terminal, a terminal, a server, generative artificial intelligence, and an emotion engine.

[0223] Users wear a wearable device in their daily lives. The device collects vital data such as heart rate, exercise volume, dietary intake, sleep data, and stress levels in real time. For example, when a user eats breakfast, the wearable device records the time and content of the meal. It also continuously collects data while exercising or sleeping. Specific hardware used includes the Apple Watch and Fitbit.

[0224] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. When the device is connected, data is automatically synchronized. For example, heart rate and exercise data are sent to the device in real time. This device includes iPhones and Android smartphones.

[0225] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed. Specific transmission protocols used are HTTP / HTTPS, Bluetooth, and Wi-Fi.

[0226] The server consolidates the received vital data and manages it centrally. The server is equipped with generative artificial intelligence that analyzes the consolidated data. For example, it analyzes the user's data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume. The specific server environment used is Amazon Web Services (AWS) or Google Cloud.

[0227] Based on the analysis results, the generative AI generates personalized lifestyle improvement recommendations for each user. These include specific instructions regarding diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods at breakfast from now on" and exercise advice such as "Do 30 minutes of aerobic exercise every night" are generated. The generative AI model uses a Python-based model, and an example of a prompt for this model is, "Analyze one week's heart rate data and exercise records to create a graph showing health trends. Please also include suggestions for relaxation exercises if stress levels are high."

[0228] Furthermore, the emotion engine recognizes the user's emotions. The emotion engine analyzes data such as the user's facial expressions, tone of voice, and physical movements to understand their emotional state at that time. For example, while the user is operating the smartphone, the camera captures their face and analyzes their voice to determine emotions such as stress or joy. The emotion engine includes facial expression analysis using OpenCV and TensorFlow.

[0229] The emotion data recognized by the emotion engine is also sent to the server, and the artificial intelligence combines it with vital data to generate further lifestyle improvement suggestions. For example, if stress levels are high, it will generate suggestions for relaxation exercises or advice on reconsidering the timing of work breaks.

[0230] The generated lifestyle improvement suggestions and emotional feedback are sent from the server to the user's device, where they are presented to the user. The device displays the feedback in a visually easy-to-understand format, suggesting specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as, "Your stress level seems high. Try doing some relaxation exercises."

[0231] After the user takes the recommended action based on the feedback, the wearable device again collects new vital data, which is again sent to the server via the device. The emotion engine also periodically collects emotional data and similarly sends it to the server. The generative AI reevaluates this data to determine the effectiveness of improvements and provides further feedback as needed. This provides ongoing support for the user's health management.

[0232] The system of the present invention effectively utilizes individual vital data and emotional data to provide lifestyle improvement suggestions tailored to the user, thereby contributing to the prevention of lifestyle-related diseases such as diabetes and their progression to more serious conditions. Furthermore, because the entire system functions in real time, it is possible to maintain the user's motivation in their daily lives and have their behavior reflected immediately.

[0233] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0234] Step 1:

[0235] Users wear a wearable device in their daily lives, which collects vital data such as heart rate, exercise volume, dietary habits, sleep data, and stress levels in real time.

[0236] Input: User's daily activities and physiological status

[0237] Specific operation: Specifically, when the user eats breakfast, the time and contents of the meal are recorded. Data is also collected continuously during exercise and while sleeping.

[0238] Output: Collected vital data

[0239] Step 2:

[0240] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. Once the device is connected, data is automatically synchronized.

[0241] Input: Vital data collected by a wearable device

[0242] Specific operation: Heart rate and exercise data are sent to your smartphone in real time.

[0243] Output: Vital data stored on the user's device

[0244] Step 3:

[0245] The device periodically transmits vital data to the server at set intervals, such as at the end of each day or after a specific event, and the success status of the data transmission is confirmed.

[0246] Input: Vital data stored on the device

[0247] Specific operation: Heart rate and exercise data are uploaded to the server at midnight.

[0248] Output: Vital data stored on the server

[0249] Step 4:

[0250] The server integrates and centrally manages the received vital data. The server is equipped with a generative artificial intelligence that analyzes the integrated data.

[0251] Input: Vital data stored on the server

[0252] How it works: The AI ​​model analyzes heart rate data from the past week to detect outliers and health trends, and analyzes diet and exercise trends to assess fluctuations in health.

[0253] Output: Analysis results (detection of outliers, health trends, etc.)

[0254] Step 5:

[0255] Based on the analysis, the generative AI model generates personalized lifestyle recommendations for each user, including specific instructions for diet, exercise, sleep, and stress management.

[0256] Input: Analysis results

[0257] Specific actions: Guidance such as "Increase the amount of high-protein foods at breakfast" or "Do 30 minutes of aerobic exercise every night" is generated.

[0258] Output: Personalized lifestyle changes

[0259] Step 6:

[0260] To recognize the user's emotions, the emotion engine analyzes the user's facial expressions, tone of voice, body movements, etc. This data is collected to understand the user's emotional state.

[0261] Input: User's facial expressions, tone of voice, and physical movements

[0262] Specific actions: Captures faces, analyzes tone of voice, and determines emotions such as stress or joy.

[0263] Output: Emotion data

[0264] Step 7:

[0265] Emotional data recognized by the emotion engine is also sent to the server, and the generative AI model combines this with vital data to generate further lifestyle improvement suggestions.

[0266] Input: Emotion data, vital data

[0267] Specific actions: If stress levels are high, suggestions for relaxation exercises and advice on reconsidering work break timing will be generated.

[0268] Output: Additional lifestyle changes

[0269] Step 8:

[0270] The server sends the generated lifestyle improvement suggestions and emotion-based feedback to the user's device, which then presents them to the user. Real-time feedback is provided using a notification function.

[0271] Input: Additional lifestyle changes

[0272] Specific behavior: The device uses the notification function to notify you, "Your stress level seems high. Try some relaxation exercises."

[0273] Output: Presented feedback to the user

[0274] Step 9:

[0275] After the user takes action based on the feedback, the wearable device again collects new vital data, which is then sent to the server via the device. The emotion engine also periodically collects emotional data and sends it to the server in the same way.

[0276] Input: Vital data and emotional data after user actions

[0277] What happens: Heart rate data is collected after a relaxation exercise.

[0278] Output: New vital and emotional data collected

[0279] Step 10:

[0280] A generative AI model re-evaluates this data, determines the effectiveness of improvements, and provides further feedback as needed, supporting the user in managing their health on an ongoing basis.

[0281] Input: New vital and emotional data

[0282] Specific actions: Evaluate whether relaxation exercises have improved stress levels and provide new suggestions.

[0283] Output: Reevaluated results and further feedback

[0284] (Application example 2)

[0285] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0286] Health management is becoming increasingly important in modern society, but it is difficult to receive personalized advice in real time that takes into account individual lifestyle habits and health conditions. Furthermore, physical stores often lack the information necessary to provide optimal services to each individual customer. Therefore, there is a need for a system that provides personalized services to customers and supports health management based on vital signs and emotional data.

[0287] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting daily vital data from the wearable device, means for transmitting the vital data to the device, means for the device to transmit the vital data to the server, means for the server to integrate and analyze the vital data, means for a generative artificial intelligence to generate personalized lifestyle improvement suggestions based on the integrated and analyzed vital data, means for transmitting the generated lifestyle improvement suggestions to the device and presenting them to the user, and a brick-and-mortar store application that provides customized services based on the vital data and emotion data when a customer visits a brick-and-mortar store while wearing a wearable device. This makes it possible to provide lifestyle improvement suggestions tailored to individual users in real time, and to provide personalized services even in brick-and-mortar stores.

[0288] A "wearable device" is a device that can be worn by a user and collects and transmits vital data such as heart rate, amount of exercise, dietary content, sleep data, and stress level in real time.

[0289] "Vital data" refers to biological information such as heart rate, blood sugar level, amount of exercise, sleep data, and stress level that indicates the user's health condition.

[0290] A "terminal" is a device (such as a smartphone or tablet) that has the function of receiving collected vital data and sending it to a server.

[0291] The "server" is a computer that integrates and analyzes vital data sent from the device and generates personalized lifestyle improvement suggestions using generative artificial intelligence.

[0292] "Generative AI" is an algorithm that automatically generates optimal lifestyle improvement suggestions for users based on integrated and analyzed vital data.

[0293] "Lifestyle changes" are advice that includes specific instructions and recommendations regarding diet, exercise, sleep, and stress management.

[0294] "Emotion data" is information indicating the user's emotional state obtained from facial expressions, tone of voice, body movements, and the like.

[0295] The "physical store application" is software that provides customized services based on vital and emotional data when customers visit a physical store while wearing a wearable device.

[0296] The present invention provides a specific means for providing personalized services to customers using a system including a wearable terminal, a terminal, a server, a generative artificial intelligence, and an emotion engine. The following describes specific embodiments of the present invention.

[0297] Users wear a wearable device in their daily lives. The device collects various vital data in real time, such as heart rate, exercise volume, dietary intake, sleep data, and stress levels. For example, when a user eats breakfast, the device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0298] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. When the device is connected, data is automatically synchronized. For example, heart rate and exercise volume data are sent to the device in real time.

[0299] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed.

[0300] The server integrates and centrally manages the received vital data. The server is equipped with generative artificial intelligence, which analyzes the integrated data. For example, it analyzes the user's data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume.

[0301] Based on the analysis results, the AI ​​generates personalized lifestyle improvement recommendations for each user, including specific instructions for diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods you eat at breakfast from now on" and exercise advice such as "Do 30 minutes of aerobic exercise every night" are generated.

[0302] Furthermore, the emotion engine recognizes the user's emotions. The emotion engine analyzes data such as the user's facial expressions, tone of voice, and physical movements to grasp the user's emotional state at that time. For example, while the user is operating the smartphone, the camera captures the face and analyzes the voice to determine emotions such as stress or joy.

[0303] The emotion data recognized by the emotion engine is also sent to the server, and the artificial intelligence combines it with vital data to generate further lifestyle improvement suggestions. For example, if stress levels are high, it will generate suggestions for relaxation exercises or advice on reconsidering the timing of work breaks.

[0304] In addition, an important component of the present invention is a store application that provides customized services based on vital data and emotional data when a customer wearing a wearable device visits a store. For example, if a user is determined to be in a high-stress state, the application can guide the user to a relaxing area in the store or provide products that will reduce stress.

[0305] The generated lifestyle improvement suggestions and emotional feedback are sent from the server to the user's device, where they are presented to the user. The device displays the feedback in a visually easy-to-understand format, suggesting specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as, "Your stress level seems high. Try doing some relaxation exercises."

[0306] Below is an example prompt that includes guidelines for providing customized services based on wearable device data when customers visit a store.

[0307] Example prompt sentence:

[0308] "Please suggest personalized in-store services based on the vital and emotional data of user ID: user12345."

[0309] The above is a specific description based on an embodiment of the present invention. This system configuration allows for real-time provision of lifestyle improvement suggestions tailored to individual users, and also makes it possible to provide personalized services in brick-and-mortar stores.

[0310] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0311] Step 1:

[0312] Users wear a wearable device and collect vital data during their daily lives. Specifically, the wearable device records heart rate, exercise, diet, sleep, stress level, etc. in real time. The input is the user's daily data, and the output is the collected vital data.

[0313] Step 2:

[0314] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. When the device is connected, data synchronization is performed automatically. The input is the collected vital data, and the output is the synchronized data sent to the device.

[0315] Step 3:

[0316] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed. The input is the vital data on the device, and the output is the data sent to the server.

[0317] Step 4:

[0318] The server integrates the received vital data and manages it centrally. The server is equipped with generative artificial intelligence that analyzes the integrated data. The input is the vital data sent to the server, and the output is the integrated and analyzed data.

[0319] Step 5:

[0320] The server's artificial intelligence generates personalized lifestyle improvement recommendations for each user based on the analyzed data. For example, it analyzes the user's data from the past week, detects abnormal values ​​and health trends, and generates specific advice. The input is the integrated and analyzed data, and the output is the generated improvement recommendations.

[0321] Step 6:

[0322] The emotion engine analyzes data such as facial expressions, tone of voice, and body movements to recognize the user's emotions. For example, while the user is operating a smartphone, a camera captures the face and analyzes the voice to determine the emotion. The input is the user's emotion-related data, and the output is the analyzed emotion data.

[0323] Step 7:

[0324] The server receives the emotional data from the emotion engine and combines it with vital data to generate further lifestyle improvement recommendations. For example, if stress levels are high, it will suggest relaxation exercises. The input is emotional data and vital data, and the output is further personalized improvement recommendations.

[0325] Step 8:

[0326] When a user visits a physical store while wearing a wearable device, the system provides customized services based on their vital and emotional data. Specifically, this includes guiding them to relaxation areas and recommending appropriate products based on the user's stress level. The input is the user's latest vital and emotional data, and the output is the provision of personalized services.

[0327] Step 9:

[0328] The generated lifestyle improvement suggestions and emotional feedback are sent from the server to the user's device and presented in a visually easy-to-understand format. Specifically, real-time feedback is provided using a notification function. The input is the generated improvement suggestions, and the output is the feedback displayed on the user's device.

[0329] The above is the processing flow of the system that provides personalized services using vital data and emotional data.

[0330] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0331] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0332] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0333] [Second embodiment]

[0334] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0335] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0336] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0337] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0338] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0339] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0340] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0341] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0342] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0343] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0344] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0345] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0346] The present invention provides lifestyle improvement suggestions based on individual vital data using a system including a wearable device, a terminal, a server, and a generating artificial intelligence. Hereinafter, an embodiment of the present invention will be described in detail.

[0347] Users wear a wearable device in their daily lives. The device collects various vital data in real time, such as heart rate, exercise volume, dietary intake, sleep data, and stress levels. For example, when a user eats breakfast, the device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0348] The vital data collected by the wearable device is sent to the user's device (a mobile device such as a smartphone or tablet) via Bluetooth or Wi-Fi. The device then sends this data to a server at regular intervals. For example, the data is uploaded at the end of each day or after a specific event.

[0349] The server integrates and centrally manages the received vital data. The server is equipped with generative artificial intelligence that analyzes the integrated data. For example, it analyzes a user's exercise and diet data over the course of a week to detect patterns and abnormal values.

[0350] Based on the analysis results, the AI ​​generates personalized lifestyle improvement recommendations for each user, including specific instructions for diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods you eat at breakfast from now on" and exercise advice such as "Do 30 minutes of aerobic exercise every night" are generated.

[0351] The generated lifestyle improvement suggestions are sent from the server to the user's device, where they are presented to the user. The device displays the feedback in a visually easy-to-understand format, indicating the specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as, "Your recent dietary habits need improvement. Please check for detailed instructions."

[0352] After the user takes the recommended action based on the feedback, the wearable device again collects new vital signs and sends them back to the server. The generative AI re-evaluates the data to determine the effectiveness of the improvements and provides further feedback as needed, providing ongoing support for the user's health management.

[0353] The system of the present invention effectively utilizes individual vital data and provides lifestyle improvement suggestions tailored to each user, thereby contributing to the prevention of lifestyle-related diseases such as diabetes and their progression to more serious conditions. Furthermore, because the entire system functions in real time, it is possible to maintain the user's motivation in their daily lives and have their behavior reflected immediately.

[0354] The processing flow will be explained below.

[0355] Step 1:

[0356] Users wear a wearable device in their daily lives, which collects vital data such as heart rate, exercise volume, dietary intake, sleep data, and stress levels in real time. For example, when a user eats breakfast, the wearable device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0357] Step 2:

[0358] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. Once the device is connected, data is automatically synchronized. For example, heart rate and exercise data are sent to the device in real time.

[0359] Step 3:

[0360] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed.

[0361] Step 4:

[0362] The server integrates the received vital data and manages it centrally. For example, it integrates heart rate data, exercise data, dietary data, sleep data, and stress data and manages them as a single data set.

[0363] Step 5:

[0364] The server-based generative artificial intelligence analyzes the integrated vital data. For example, it analyzes data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume.

[0365] Step 6:

[0366] Based on the analysis results, the AI ​​generates personalized lifestyle improvement suggestions suited to each individual user. For example, if it determines that the user is not getting enough exercise, it will generate specific instructions such as "recommended 30 minutes of walking on the weekend." It also generates advice on diet and suggestions for improving sleep.

[0367] Step 7:

[0368] The server sends the generated lifestyle improvement suggestions to the device, which receives them and presents them to the user in a visually easy-to-understand format. For example, a notification function can be used to provide real-time feedback such as, "Your recent dietary habits need improvement. Please check for detailed instructions."

[0369] Step 8:

[0370] Based on the feedback, the user performs the recommended action, such as walking or exercising, and then the data is collected again by the wearable device.

[0371] Step 9:

[0372] The device then sends the newly collected vital data back to the server, which receives it and analyzes it again using the artificial intelligence.

[0373] Step 10:

[0374] The generative AI reassess the new vital data and determines whether improvements or new guidance are needed. For example, it evaluates the patient's condition after walking and provides feedback such as, "Your blood sugar level has improved. Continue to maintain good lifestyle habits."

[0375] Example 1

[0376] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0377] As the need for prevention and management of lifestyle-related diseases increases in modern times, there is a need to effectively utilize individual vital signs data and provide users with appropriate lifestyle improvement suggestions. However, existing systems do not adequately collect data in real time or provide personalized improvement suggestions, making it difficult to continuously support users' health management.

[0378] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0379] In this invention, the server includes a means for integrating and analyzing the received vital data and detecting patterns and abnormal values, a means for a generating artificial intelligence to generate personalized lifestyle improvement suggestions based on the integrated and analyzed vital data, and a means for re-evaluating the user's behavioral data and providing further feedback as necessary. This makes it possible to collect and analyze individual vital data in real time and provide the user with continuous and personalized lifestyle improvement suggestions.

[0380] A "wearable device" is a device worn by a user to collect vital data such as heart rate, exercise volume, dietary habits, sleep data, and stress levels in real time.

[0381] "Vital data" refers to data that indicates the user's physical and physiological condition, such as heart rate, amount of exercise, dietary content, sleep data, and stress level.

[0382] A "terminal" is a device that receives vital data sent from a wearable device and sends it to a server. Examples of such devices include smartphones and tablets.

[0383] The "server" is a computer system that consolidates and analyzes vital data sent from devices and detects patterns and abnormal values.

[0384] "Generative AI" is an AI model that generates individual lifestyle improvement suggestions based on integrated and analyzed vital data.

[0385] "Lifestyle Improvement Suggestions" are suggestions for improving the user's lifestyle, including specific instructions regarding diet, exercise, sleep, and stress management.

[0386] The "notification function" is a function that allows the device to visually present improvement suggestions and feedback to the user in real time.

[0387] "Feedback" is further instruction or advice provided to a user after they have taken a recommended action, based on additional data analysis.

[0388] The present invention provides lifestyle improvement suggestions based on individual vital data using a system including a wearable device, a terminal, a server, and a generating artificial intelligence. An embodiment of this system will be specifically described below.

[0389] Users wear a wearable device in their daily lives. The device collects various vital data in real time, such as heart rate, exercise volume, dietary intake, sleep data, and stress level. For example, when a user eats breakfast, the wearable device records the time and content of the meal. It also continuously collects data while the user is exercising or sleeping.

[0390] The vital data collected by the wearable device is sent to the user's device (a mobile device such as a smartphone or tablet) via Bluetooth or Wi-Fi. The device then sends the data to a server at regular intervals. For example, the data is uploaded at the end of each day or after a specific event.

[0391] The server uses cloud servers such as Amazon Web Services (AWS) and Google Cloud Platform (GCP) to integrate and centrally manage the received vital signs. The server is equipped with a generative artificial intelligence (AI model) that analyzes the integrated data and detects patterns and outliers. For example, it analyzes a user's exercise and diet data over the course of a week to detect lack of exercise or an unbalanced diet.

[0392] Based on the analysis results, the generative AI generates personalized lifestyle improvement suggestions for each user. These include specific instructions regarding diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods you eat at breakfast from now on" or exercise advice such as "Do 30 minutes of aerobic exercise every night" is generated. The generated lifestyle improvement suggestions are sent from the server to the user's device, where they are presented to the user. The device displays feedback in a visually easy-to-understand format, indicating specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as "Your recent dietary habits need improvement. Please check for detailed instructions."

[0393] After the user takes the recommended action based on the feedback, the wearable device again collects new vital signs and sends them back to the server. The generative AI re-evaluates the data to determine the effectiveness of the improvements and provides further feedback as needed, providing ongoing support for the user's health management.

[0394] Prompt Sentence Examples

[0395] "Please suggest appropriate exercise habits based on the user's exercise data for the week."

[0396] "Analyze the user's dietary data and generate recommendations for future dietary improvements."

[0397] The system of the present invention effectively utilizes individual vital data and provides lifestyle improvement suggestions tailored to the user, thereby contributing to the prevention of lifestyle-related diseases and maintaining motivation. In addition, because the entire system functions in real time, it is possible to immediately reflect the user's daily behavior.

[0398] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0399] Step 1:

[0400] Users wear a wearable device while going about their daily lives, and the device collects vital data such as heart rate, exercise volume, dietary habits, sleep data, and stress levels in real time.

[0401] Input: User activities

[0402] Data processing and output: Collected vital data is recorded in real time.

[0403] Step 2:

[0404] The vital data collected by the wearable device is sent to the user's device via Bluetooth or Wi-Fi.

[0405] Input: Vital data from a wearable device

[0406] Data processing and output: Vital data is periodically aggregated and transmitted to the device.

[0407] Step 3:

[0408] The terminal transmits the vital data received from the wearable terminal to the server at regular intervals.

[0409] Input: Vital data from a wearable device

[0410] Data processing and output: Organize data in the device and convert it into a format to send to the server.

[0411] Step 4:

[0412] The server integrates and centralizes the vital data it receives. The server is equipped with a generative artificial intelligence (AI model) that analyzes the integrated data to detect patterns and outliers.

[0413] Input: Vital data sent from the device

[0414] Data processing and output: Data is integrated and analyzed by AI models, and any patterns or anomalies detected are recorded.

[0415] Step 5:

[0416] Based on the analysis results, the generative artificial intelligence generates personalized lifestyle improvement suggestions.

[0417] Input: Integrated and analyzed data

[0418] Data processing and output: Generate lifestyle improvement suggestions based on the analysis results.

[0419] Step 6:

[0420] The server sends the generated lifestyle improvement suggestions to the terminal.

[0421] Input: AI-generated improvement suggestions

[0422] Data processing and output: Convert the improvement proposal into a format that can be sent to the terminal and send it.

[0423] Step 7:

[0424] The device presents improvement suggestions to the user in a visually easy-to-understand format.

[0425] Input: Improvement suggestions sent from the server

[0426] Data processing and output: Display improvement proposals in a format suitable for the user interface.

[0427] Step 8:

[0428] The user takes the recommended action based on the feedback, and the wearable device again collects new vital signs.

[0429] Input: User action

[0430] Data Processing and Output: New vital data is collected.

[0431] Step 9:

[0432] The device sends new vital data to the server, where the AI ​​reassess it, determines the effectiveness of any improvements, and provides further feedback as needed.

[0433] Input: New vitals

[0434] Data processing and output: Reassess the data and generate / send new feedback as needed.

[0435] (Application example 1)

[0436] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0437] While conventional wearable devices are effective for collecting vital data and improving lifestyle habits for individuals, they have not been applied to monitoring the health status and improving the efficiency of equipment in certain industries, particularly factories. Therefore, there is a need to monitor the health status of factory equipment in the same way as humans and provide specific improvement suggestions.

[0438] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0439] In this invention, the server comprises: means for collecting daily vital data from the wearable terminal; means for transmitting the vital data to the terminal; means for the terminal to transmit the vital data to the server; means for the server to integrate and analyze the vital data; means for a generating artificial intelligence to generate personalized lifestyle improvement suggestions based on the integrated and analyzed vital data; and means for transmitting the generated lifestyle improvement suggestions to the terminal and presenting them to the user.

[0440] a means for collecting operation data of the equipment from sensors attached to the equipment in the factory and analyzing the operation data;

[0441] A means for generating specific improvement plans to improve the operating efficiency of factory equipment based on the analyzed operation data by the generating artificial intelligence;

[0442] and a means for transmitting the generated improvement plan to a terminal of a factory manager and presenting it to the manager. This makes it possible to manage the health of users and improve the operating efficiency of factory equipment.

[0443] A "wearable device" is a device worn on the body to collect physiological data of the user.

[0444] "Vital data" refers to physiological data related to the health status of a user.

[0445] A "terminal" is an electronic device for receiving and processing vital data transmitted from a wearable terminal.

[0446] A "server" is a central control computer that integrates and analyzes data sent from the terminals.

[0447] "Generative AI" is an AI (artificial intelligence) technology that analyzes collected data and generates feedback and improvement suggestions tailored to specific purposes.

[0448] "Lifestyle improvement proposals" are specific action proposals that instruct changes or improvements to lifestyle habits, proposed based on vital data.

[0449] "Factory equipment" refers to industrial machines and devices used in production lines and work processes.

[0450] A "sensor" is a device that is attached to factory equipment and collects various operational data in real time.

[0451] "Operation data" refers to operational data generated when factory equipment is in operation.

[0452] "Improvement proposals" are specific instructions or suggestions for improving the operating efficiency of equipment based on analyzed data.

[0453] The "factory manager's terminal" is an electronic device used by the factory manager, and is a device for receiving and viewing improvement proposals.

[0454]

[0455] The present invention provides a system for integrating and analyzing data collected from wearable devices and sensors attached to factory equipment, thereby improving lifestyle habits and increasing the operating efficiency of factory equipment. A specific configuration for implementing the present invention will be described below.

[0456] First, the user puts on a wearable device, which collects various vital data in real time, such as heart rate, exercise volume, dietary habits, sleep data, and stress levels. The collected vital data is then sent to the user's smartphone, tablet, or other device via Bluetooth or Wi-Fi.

[0457] In factories, multiple sensors are attached to equipment to collect operational data in real time, such as temperature, vibration, operating frequency, and power consumption, which is also sent to a central server via the factory network.

[0458] The wearable device periodically transmits vital data collected from the device to a cloud server. The server is equipped with a generative artificial intelligence (generative AI model) that integrates and analyzes the received data. Based on the vital data, it generates specific improvement proposals to improve the user's lifestyle habits, and based on the operational data, it generates specific improvement proposals to improve the operating efficiency of equipment.

[0459] For example, by analyzing a week's worth of exercise and dietary data, the system can generate specific instructions for the user, such as "Increase the amount of high-protein foods you eat for breakfast in the future." It can also generate specific instructions for factory equipment, such as "The vibrations are too strong, so we recommend maintenance."

[0460] The generated improvement proposals are sent from the server to the user's device and the factory manager's device. The user and manager receive easy-to-understand visual feedback through their devices. For example, the user's device may receive a notification saying, "Your recent eating habits need improvement. Please check for detailed instructions." The factory manager's device may receive a notification saying, "We have detected an abnormality in Robot No. 1's motor temperature, exceeding 80 degrees. Please instruct immediate maintenance of the cooling system and motor."

[0461] To implement this system, the following hardware and software are used.

[0462] Hardware: Wearable devices, various sensors, smartphones, tablets, factory network equipment, and servers.

[0463] Software: Data collection module, cloud storage, generative artificial intelligence platform (e.g., Google Cloud AI, AWS SageMaker, Azure Machine Learning), feedback sharing app.

[0464] As a concrete example, if the sensor detects that the robot's motor temperature has exceeded 80 degrees, the prompt text would be as follows:

[0465] Prompt: "Robot #1's motor temperature has been detected to be above 80 degrees. Order immediate maintenance on the cooling system and motor."

[0466] In this way, the system of the present invention can continuously support user health management and improved operating efficiency of factory equipment by using wearable devices and factory sensors.

[0467] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0468] Step 1:

[0469] The user wears a wearable device, which collects various vital data in real time, such as heart rate, exercise volume, dietary content, sleep data, and stress level. The collected data is sent to the user's smartphone or tablet via Bluetooth or Wi-Fi. The input is the user's vital data, and the output is data sent to the device.

[0470] Step 2:

[0471] In factories, sensors attached to equipment collect operational data such as temperature, vibration, operating frequency, and power consumption in real time. The collected data is sent to a server via the factory network. The input is the equipment's operational data, and the output is data sent to the server.

[0472] Step 3:

[0473] The device periodically transmits vital data collected from the wearable device to a cloud server. The input is the vital data stored on the device, and the output is data sent to the cloud server.

[0474] Step 4:

[0475] The server integrates the vital data and operating data sent from the wearable devices and sensors and stores them in cloud storage. The input is the data sent to the server, and the output is the storage of the integrated data.

[0476] Step 5:

[0477] A generative artificial intelligence (generative AI model) installed on the server analyzes the integrated vital data and operational data. It generates lifestyle improvement suggestions based on the user's health condition, as well as improvement suggestions to improve the operating efficiency of the equipment. The input is the integrated data, and the output is improvement suggestions.

[0478] Step 6:

[0479] The generated improvement proposals are sent from the server to the user terminal and the factory manager's terminal. The input is the generated improvement proposal, and the output is the data sent to the terminal.

[0480] Step 7:

[0481] The user's device and the factory manager's device display improvement proposals in a visually easy-to-understand format and provide real-time feedback using a notification function. Specifically, the user's device displays a notification such as, "Your recent diet needs improvement. Please check for detailed instructions." The factory manager's device displays a notification such as, "An abnormality has been detected in Robot No. 1's motor temperature, exceeding 80 degrees. Please instruct immediate maintenance of the cooling system and motor." The input is improvement proposal data from the server, and the output is notifications to the user and factory manager.

[0482] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0483] The present invention provides lifestyle improvement suggestions based on individual vital data and emotion data using a system including a wearable device, a terminal, a server, generative artificial intelligence, and an emotion engine. The following describes specific embodiments of the present invention.

[0484] Users wear a wearable device in their daily lives. The device collects various vital data in real time, such as heart rate, exercise volume, dietary intake, sleep data, and stress levels. For example, when a user eats breakfast, the device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0485] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. When the device is connected, data is automatically synchronized. For example, heart rate and exercise volume data are sent to the device in real time.

[0486] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed.

[0487] The server integrates and centrally manages the received vital data. The server is equipped with generative artificial intelligence, which analyzes the integrated data. For example, it analyzes the user's data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume.

[0488] Based on the analysis results, the AI ​​generates personalized lifestyle improvement recommendations for each user, including specific instructions for diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods you eat at breakfast from now on" and exercise advice such as "Do 30 minutes of aerobic exercise every night" are generated.

[0489] Furthermore, the emotion engine recognizes the user's emotions. The emotion engine analyzes data such as the user's facial expressions, tone of voice, and physical movements to grasp the user's emotional state at that time. For example, while the user is operating the smartphone, the camera captures the face and analyzes the voice to determine emotions such as stress or joy.

[0490] The emotion data recognized by the emotion engine is also sent to the server, and the artificial intelligence combines it with vital data to generate further lifestyle improvement suggestions. For example, if stress levels are high, it will generate suggestions for relaxation exercises or advice on reconsidering the timing of work breaks.

[0491] The generated lifestyle improvement suggestions and emotional feedback are sent from the server to the user's device, where they are presented to the user. The device displays the feedback in a visually easy-to-understand format, suggesting specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as, "Your stress level seems high. Try doing some relaxation exercises."

[0492] After the user takes the recommended action based on the feedback, the wearable device again collects new vital data, which is again sent to the server via the device. The emotion engine also periodically collects emotional data and similarly sends it to the server. The generative AI reevaluates this data to determine the effectiveness of improvements and provides further feedback as needed. This provides ongoing support for the user's health management.

[0493] The system of the present invention effectively utilizes individual vital data and emotional data to provide lifestyle improvement suggestions tailored to the user, thereby contributing to the prevention of lifestyle-related diseases such as diabetes and their progression to more serious conditions. Furthermore, because the entire system functions in real time, it is possible to maintain the user's motivation in their daily lives and have their behavior reflected immediately.

[0494] The processing flow will be explained below.

[0495] Step 1:

[0496] Users wear a wearable device in their daily lives, which collects vital data such as heart rate, exercise volume, dietary intake, sleep data, and stress levels in real time. For example, when a user eats breakfast, the wearable device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0497] Step 2:

[0498] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. Once the device is connected, data is automatically synchronized. For example, heart rate and exercise data are sent to the device in real time.

[0499] Step 3:

[0500] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed.

[0501] Step 4:

[0502] The server integrates and centrally manages the received vital data, for example, heart rate data, exercise data, dietary data, sleep data, and stress data, and manages them as a single data set.

[0503] Step 5:

[0504] The server-based generative artificial intelligence analyzes the integrated vital data. For example, it analyzes data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume.

[0505] Step 6:

[0506] Based on the analysis results, the AI ​​generates personalized lifestyle improvement suggestions suited to each individual user. For example, if it determines that the user is not getting enough exercise, it will generate specific instructions such as "recommended 30 minutes of walking on the weekend." It also generates advice on diet and suggestions for improving sleep.

[0507] Step 7:

[0508] The device uses an emotion engine to recognize the user's emotions and collects emotion data from the user's facial expressions, tone of voice, and body movements. For example, if the user is feeling stressed, the emotion engine will detect this.

[0509] Step 8:

[0510] The emotional data collected by the device is sent to a server, where it is centrally managed and analyzed in combination with vital data. For example, it can analyze the time periods and situations in which the user feels stressed.

[0511] Step 9:

[0512] The generative AI will then analyze the emotional and vital data to generate more specific lifestyle improvement recommendations, such as "Perform relaxation exercises every night to reduce stress."

[0513] Step 10:

[0514] The server then sends the lifestyle improvement suggestions it has generated to the device, which then presents them to the user and displays feedback in a visually easy-to-understand format. For example, real-time feedback such as "Your stress level seems high. Try some relaxation exercises" is provided.

[0515] Step 11:

[0516] The user performs the recommended action based on the feedback, such as walking or exercising, and then the data is collected again by the wearable device.

[0517] Step 12:

[0518] The device again transmits the newly collected vital data and emotional data to the server, which receives it and analyzes it again using the artificial intelligence.

[0519] Step 13:

[0520] The generative AI reassess the new vital and emotional data to determine whether improvements or new guidance are needed. For example, it evaluates the patient's condition after a walk and provides feedback such as, "Your blood sugar level has improved. Continue to maintain good lifestyle habits."

[0521] Example 2

[0522] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0523] Conventional health management systems can only provide static advice based on a user's vital signs, and lack a dynamic approach that takes into account the user's emotional state. Furthermore, due to insufficient real-time feedback, it is difficult to provide timely improvement suggestions that are tailored to the user's daily life.

[0524] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for integrating and analyzing vital data, means for a generating artificial intelligence to generate personalized lifestyle improvement suggestions, means for an emotion engine to collect and analyze emotion data, and means for combining the emotion data with vital data to generate additional lifestyle improvement suggestions. This makes it possible to analyze the user's vital data and emotion data in an integrated manner, and to provide more personalized and appropriate lifestyle improvement suggestions in real time that are tailored to the user's health condition and emotions.

[0525] A "wearable device" is a compact electronic device that can be worn by the user and collects vital data such as heart rate, exercise volume, dietary content, sleep data, and stress level in real time.

[0526] "Vital data" refers to basic physiological data necessary to understand a user's health condition, and specifically refers to data such as heart rate, amount of exercise, diet, sleep data, and stress level.

[0527] A "terminal" is an electronic device that receives collected vital data from a user's wearable device, synchronizes the data, and transmits the data to a server, and includes smartphones, tablets, etc.

[0528] The "server" is a computer system that integrates and analyzes vital data and emotional data sent from terminals via the Internet.

[0529] "Generative AI" refers to an AI program that analyzes collected vital data and generates personalized lifestyle improvement suggestions.

[0530] An "emotion engine" refers to software or hardware that analyzes a user's emotional state from facial expressions, tone of voice, physical movements, etc., and collects this as emotional data.

[0531] "Personalized lifestyle changes" refers to specific suggestions for diet, exercise, sleep, and stress management that are generated based on a user's individual vital and emotional data.

[0532] "Emotion data" refers to data that indicates the user's emotional state, and is obtained by analyzing facial expressions, tone of voice, body movements, and the like using an emotion engine.

[0533] The present invention provides lifestyle improvement suggestions based on individual vital data and emotional data using a system including a wearable terminal, a terminal, a server, generative artificial intelligence, and an emotion engine.

[0534] Users wear a wearable device in their daily lives. The device collects vital data such as heart rate, exercise volume, dietary intake, sleep data, and stress levels in real time. For example, when a user eats breakfast, the wearable device records the time and content of the meal. It also continuously collects data while exercising or sleeping. Specific hardware used includes the Apple Watch and Fitbit.

[0535] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. When the device is connected, data is automatically synchronized. For example, heart rate and exercise data are sent to the device in real time. This device includes iPhones and Android smartphones.

[0536] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed. Specific transmission protocols used are HTTP / HTTPS, Bluetooth, and Wi-Fi.

[0537] The server consolidates the received vital data and manages it centrally. The server is equipped with generative artificial intelligence that analyzes the consolidated data. For example, it analyzes the user's data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume. The specific server environment used is Amazon Web Services (AWS) or Google Cloud.

[0538] Based on the analysis results, the generative AI generates personalized lifestyle improvement recommendations for each user. These include specific instructions regarding diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods at breakfast from now on" and exercise advice such as "Do 30 minutes of aerobic exercise every night" are generated. The generative AI model uses a Python-based model, and an example of a prompt for this model is, "Analyze one week's heart rate data and exercise records to create a graph showing health trends. Please also include suggestions for relaxation exercises if stress levels are high."

[0539] Furthermore, the emotion engine recognizes the user's emotions. The emotion engine analyzes data such as the user's facial expressions, tone of voice, and physical movements to understand their emotional state at that time. For example, while the user is operating the smartphone, the camera captures their face and analyzes their voice to determine emotions such as stress or joy. The emotion engine includes facial expression analysis using OpenCV and TensorFlow.

[0540] The emotion data recognized by the emotion engine is also sent to the server, and the artificial intelligence combines it with vital data to generate further lifestyle improvement suggestions. For example, if stress levels are high, it will generate suggestions for relaxation exercises or advice on reconsidering the timing of work breaks.

[0541] The generated lifestyle improvement suggestions and emotional feedback are sent from the server to the user's device, where they are presented to the user. The device displays the feedback in a visually easy-to-understand format, suggesting specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as, "Your stress level seems high. Try doing some relaxation exercises."

[0542] After the user takes the recommended action based on the feedback, the wearable device again collects new vital data, which is again sent to the server via the device. The emotion engine also periodically collects emotional data and similarly sends it to the server. The generative AI reevaluates this data to determine the effectiveness of improvements and provides further feedback as needed. This provides ongoing support for the user's health management.

[0543] The system of the present invention effectively utilizes individual vital data and emotional data to provide lifestyle improvement suggestions tailored to the user, thereby contributing to the prevention of lifestyle-related diseases such as diabetes and their progression to more serious conditions. Furthermore, because the entire system functions in real time, it is possible to maintain the user's motivation in their daily lives and have their behavior reflected immediately.

[0544] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0545] Step 1:

[0546] Users wear a wearable device in their daily lives, which collects vital data such as heart rate, exercise volume, dietary habits, sleep data, and stress levels in real time.

[0547] Input: User's daily activities and physiological status

[0548] Specific operation: Specifically, when the user eats breakfast, the time and contents of the meal are recorded. Data is also collected continuously during exercise and while sleeping.

[0549] Output: Collected vital data

[0550] Step 2:

[0551] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. Once the device is connected, data is automatically synchronized.

[0552] Input: Vital data collected by a wearable device

[0553] Specific operation: Heart rate and exercise data are sent to your smartphone in real time.

[0554] Output: Vital data stored on the user's device

[0555] Step 3:

[0556] The device periodically transmits vital data to the server at set intervals, such as at the end of each day or after a specific event, and the success status of the data transmission is confirmed.

[0557] Input: Vital data stored on the device

[0558] Specific operation: Heart rate and exercise data are uploaded to the server at midnight.

[0559] Output: Vital data stored on the server

[0560] Step 4:

[0561] The server integrates and centrally manages the received vital data. The server is equipped with a generative artificial intelligence that analyzes the integrated data.

[0562] Input: Vital data stored on the server

[0563] How it works: The AI ​​model analyzes heart rate data from the past week to detect outliers and health trends, and analyzes diet and exercise trends to assess fluctuations in health.

[0564] Output: Analysis results (detection of outliers, health trends, etc.)

[0565] Step 5:

[0566] Based on the analysis, the generative AI model generates personalized lifestyle recommendations for each user, including specific instructions for diet, exercise, sleep, and stress management.

[0567] Input: Analysis results

[0568] Specific actions: Guidance such as "Increase the amount of high-protein foods at breakfast" or "Do 30 minutes of aerobic exercise every night" is generated.

[0569] Output: Personalized lifestyle changes

[0570] Step 6:

[0571] To recognize the user's emotions, the emotion engine analyzes the user's facial expressions, tone of voice, body movements, etc. This data is collected to understand the user's emotional state.

[0572] Input: User's facial expressions, tone of voice, and physical movements

[0573] Specific actions: Captures faces, analyzes tone of voice, and determines emotions such as stress or joy.

[0574] Output: Emotion data

[0575] Step 7:

[0576] Emotional data recognized by the emotion engine is also sent to the server, and the generative AI model combines this with vital data to generate further lifestyle improvement suggestions.

[0577] Input: Emotion data, vital data

[0578] Specific actions: If stress levels are high, suggestions for relaxation exercises and advice on reconsidering work break timing will be generated.

[0579] Output: Additional lifestyle changes

[0580] Step 8:

[0581] The server sends the generated lifestyle improvement suggestions and emotion-based feedback to the user's device, which then presents them to the user. Real-time feedback is provided using a notification function.

[0582] Input: Additional lifestyle changes

[0583] Specific behavior: The device uses the notification function to notify you, "Your stress level seems high. Try some relaxation exercises."

[0584] Output: Presented feedback to the user

[0585] Step 9:

[0586] After the user takes action based on the feedback, the wearable device again collects new vital data, which is then sent to the server via the device. The emotion engine also periodically collects emotional data and sends it to the server in the same way.

[0587] Input: Vital data and emotional data after user actions

[0588] What happens: Heart rate data is collected after a relaxation exercise.

[0589] Output: New vital and emotional data collected

[0590] Step 10:

[0591] A generative AI model re-evaluates this data, determines the effectiveness of improvements, and provides further feedback as needed, supporting the user in managing their health on an ongoing basis.

[0592] Input: New vital and emotional data

[0593] Specific actions: Evaluate whether relaxation exercises have improved stress levels and provide new suggestions.

[0594] Output: Reevaluated results and further feedback

[0595] (Application example 2)

[0596] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0597] Health management is becoming increasingly important in modern society, but it is difficult to receive personalized advice in real time that takes into account individual lifestyle habits and health conditions. Furthermore, physical stores often lack the information necessary to provide optimal services to each individual customer. Therefore, there is a need for a system that provides personalized services to customers and supports health management based on vital signs and emotional data.

[0598] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting daily vital data from the wearable device, means for transmitting the vital data to the device, means for the device to transmit the vital data to the server, means for the server to integrate and analyze the vital data, means for a generative artificial intelligence to generate personalized lifestyle improvement suggestions based on the integrated and analyzed vital data, means for transmitting the generated lifestyle improvement suggestions to the device and presenting them to the user, and a brick-and-mortar store application that provides customized services based on the vital data and emotion data when a customer visits a brick-and-mortar store while wearing a wearable device. This makes it possible to provide lifestyle improvement suggestions tailored to individual users in real time, and to provide personalized services even in brick-and-mortar stores.

[0599] A "wearable device" is a device that can be worn by a user and collects and transmits vital data such as heart rate, amount of exercise, dietary content, sleep data, and stress level in real time.

[0600] "Vital data" refers to biological information such as heart rate, blood sugar level, amount of exercise, sleep data, and stress level that indicates the user's health condition.

[0601] A "terminal" is a device (such as a smartphone or tablet) that has the function of receiving collected vital data and sending it to a server.

[0602] The "server" is a computer that integrates and analyzes vital data sent from the device and generates personalized lifestyle improvement suggestions using generative artificial intelligence.

[0603] "Generative AI" is an algorithm that automatically generates optimal lifestyle improvement suggestions for users based on integrated and analyzed vital data.

[0604] "Lifestyle changes" are advice that includes specific instructions and recommendations regarding diet, exercise, sleep, and stress management.

[0605] "Emotion data" is information indicating the user's emotional state obtained from facial expressions, tone of voice, body movements, and the like.

[0606] The "physical store application" is software that provides customized services based on vital and emotional data when customers visit a physical store while wearing a wearable device.

[0607] The present invention provides a specific means for providing personalized services to customers using a system including a wearable terminal, a terminal, a server, a generative artificial intelligence, and an emotion engine. The following describes specific embodiments of the present invention.

[0608] Users wear a wearable device in their daily lives. The device collects various vital data in real time, such as heart rate, exercise volume, dietary intake, sleep data, and stress levels. For example, when a user eats breakfast, the device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0609] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. When the device is connected, data is automatically synchronized. For example, heart rate and exercise volume data are sent to the device in real time.

[0610] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed.

[0611] The server integrates and centrally manages the received vital data. The server is equipped with generative artificial intelligence, which analyzes the integrated data. For example, it analyzes the user's data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume.

[0612] Based on the analysis results, the AI ​​generates personalized lifestyle improvement recommendations for each user, including specific instructions for diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods you eat at breakfast from now on" and exercise advice such as "Do 30 minutes of aerobic exercise every night" are generated.

[0613] Furthermore, the emotion engine recognizes the user's emotions. The emotion engine analyzes data such as the user's facial expressions, tone of voice, and physical movements to grasp the user's emotional state at that time. For example, while the user is operating the smartphone, the camera captures the face and analyzes the voice to determine emotions such as stress or joy.

[0614] The emotion data recognized by the emotion engine is also sent to the server, and the artificial intelligence combines it with vital data to generate further lifestyle improvement suggestions. For example, if stress levels are high, it will generate suggestions for relaxation exercises or advice on reconsidering the timing of work breaks.

[0615] In addition, an important component of the present invention is a store application that provides customized services based on vital data and emotional data when a customer wearing a wearable device visits a store. For example, if a user is determined to be in a high-stress state, the application can guide the user to a relaxing area in the store or provide products that will reduce stress.

[0616] The generated lifestyle improvement suggestions and emotional feedback are sent from the server to the user's device, where they are presented to the user. The device displays the feedback in a visually easy-to-understand format, suggesting specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as, "Your stress level seems high. Try doing some relaxation exercises."

[0617] Below is an example prompt that includes guidelines for providing customized services based on wearable device data when customers visit a store.

[0618] Example prompt sentence:

[0619] "Please suggest personalized in-store services based on the vital and emotional data of user ID: user12345."

[0620] The above is a specific description based on an embodiment of the present invention. This system configuration allows for real-time provision of lifestyle improvement suggestions tailored to individual users, and also makes it possible to provide personalized services in brick-and-mortar stores.

[0621] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0622] Step 1:

[0623] Users wear a wearable device and collect vital data during their daily lives. Specifically, the wearable device records heart rate, exercise, diet, sleep, stress level, etc. in real time. The input is the user's daily data, and the output is the collected vital data.

[0624] Step 2:

[0625] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. When the device is connected, data synchronization is performed automatically. The input is the collected vital data, and the output is the synchronized data sent to the device.

[0626] Step 3:

[0627] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed. The input is the vital data on the device, and the output is the data sent to the server.

[0628] Step 4:

[0629] The server integrates the received vital data and manages it centrally. The server is equipped with generative artificial intelligence that analyzes the integrated data. The input is the vital data sent to the server, and the output is the integrated and analyzed data.

[0630] Step 5:

[0631] The server's artificial intelligence generates personalized lifestyle improvement recommendations for each user based on the analyzed data. For example, it analyzes the user's data from the past week, detects abnormal values ​​and health trends, and generates specific advice. The input is the integrated and analyzed data, and the output is the generated improvement recommendations.

[0632] Step 6:

[0633] The emotion engine analyzes data such as facial expressions, tone of voice, and body movements to recognize the user's emotions. For example, while the user is operating a smartphone, a camera captures the face and analyzes the voice to determine the emotion. The input is the user's emotion-related data, and the output is the analyzed emotion data.

[0634] Step 7:

[0635] The server receives the emotional data from the emotion engine and combines it with vital data to generate further lifestyle improvement recommendations. For example, if stress levels are high, it will suggest relaxation exercises. The input is emotional data and vital data, and the output is further personalized improvement recommendations.

[0636] Step 8:

[0637] When a user visits a physical store while wearing a wearable device, the system provides customized services based on their vital and emotional data. Specifically, this includes guiding them to relaxation areas and recommending appropriate products based on the user's stress level. The input is the user's latest vital and emotional data, and the output is the provision of personalized services.

[0638] Step 9:

[0639] The generated lifestyle improvement suggestions and emotional feedback are sent from the server to the user's device and presented in a visually easy-to-understand format. Specifically, real-time feedback is provided using a notification function. The input is the generated improvement suggestions, and the output is the feedback displayed on the user's device.

[0640] The above is the processing flow of the system that provides personalized services using vital data and emotional data.

[0641] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0642] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0643] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0644] [Third embodiment]

[0645] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0646] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0647] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0648] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0649] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0650] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0651] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0652] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0653] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0654] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0655] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0656] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0657] The present invention provides lifestyle improvement suggestions based on individual vital data using a system including a wearable device, a terminal, a server, and a generating artificial intelligence. Hereinafter, an embodiment of the present invention will be described in detail.

[0658] Users wear a wearable device in their daily lives. The device collects various vital data in real time, such as heart rate, exercise volume, dietary intake, sleep data, and stress levels. For example, when a user eats breakfast, the device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0659] The vital data collected by the wearable device is sent to the user's device (a mobile device such as a smartphone or tablet) via Bluetooth or Wi-Fi. The device then sends this data to a server at regular intervals. For example, the data is uploaded at the end of each day or after a specific event.

[0660] The server integrates and centrally manages the received vital data. The server is equipped with generative artificial intelligence that analyzes the integrated data. For example, it analyzes a user's exercise and diet data over the course of a week to detect patterns and abnormal values.

[0661] Based on the analysis results, the AI ​​generates personalized lifestyle improvement recommendations for each user, including specific instructions for diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods you eat at breakfast from now on" and exercise advice such as "Do 30 minutes of aerobic exercise every night" are generated.

[0662] The generated lifestyle improvement suggestions are sent from the server to the user's device, where they are presented to the user. The device displays the feedback in a visually easy-to-understand format, indicating the specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as, "Your recent dietary habits need improvement. Please check for detailed instructions."

[0663] After the user takes the recommended action based on the feedback, the wearable device again collects new vital signs and sends them back to the server. The generative AI re-evaluates the data to determine the effectiveness of the improvements and provides further feedback as needed, providing ongoing support for the user's health management.

[0664] The system of the present invention effectively utilizes individual vital data and provides lifestyle improvement suggestions tailored to each user, thereby contributing to the prevention of lifestyle-related diseases such as diabetes and their progression to more serious conditions. Furthermore, because the entire system functions in real time, it is possible to maintain the user's motivation in their daily lives and have their behavior reflected immediately.

[0665] The processing flow will be explained below.

[0666] Step 1:

[0667] Users wear a wearable device in their daily lives, which collects vital data such as heart rate, exercise volume, dietary intake, sleep data, and stress levels in real time. For example, when a user eats breakfast, the wearable device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0668] Step 2:

[0669] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. Once the device is connected, data is automatically synchronized. For example, heart rate and exercise data are sent to the device in real time.

[0670] Step 3:

[0671] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed.

[0672] Step 4:

[0673] The server integrates the received vital data and manages it centrally. For example, it integrates heart rate data, exercise data, dietary data, sleep data, and stress data and manages them as a single data set.

[0674] Step 5:

[0675] The server-based generative artificial intelligence analyzes the integrated vital data. For example, it analyzes data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume.

[0676] Step 6:

[0677] Based on the analysis results, the AI ​​generates personalized lifestyle improvement suggestions suited to each individual user. For example, if it determines that the user is not getting enough exercise, it will generate specific instructions such as "recommended 30 minutes of walking on the weekend." It also generates advice on diet and suggestions for improving sleep.

[0678] Step 7:

[0679] The server sends the generated lifestyle improvement suggestions to the device, which receives them and presents them to the user in a visually easy-to-understand format. For example, a notification function can be used to provide real-time feedback such as, "Your recent dietary habits need improvement. Please check for detailed instructions."

[0680] Step 8:

[0681] Based on the feedback, the user performs the recommended action, such as walking or exercising, and then the data is collected again by the wearable device.

[0682] Step 9:

[0683] The device then sends the newly collected vital data back to the server, which receives it and analyzes it again using the artificial intelligence.

[0684] Step 10:

[0685] The generative AI reassess the new vital data and determines whether improvements or new guidance are needed. For example, it evaluates the patient's condition after walking and provides feedback such as, "Your blood sugar level has improved. Continue to maintain good lifestyle habits."

[0686] Example 1

[0687] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0688] As the need for prevention and management of lifestyle-related diseases increases in modern times, there is a need to effectively utilize individual vital signs data and provide users with appropriate lifestyle improvement suggestions. However, existing systems do not adequately collect data in real time or provide personalized improvement suggestions, making it difficult to continuously support users' health management.

[0689] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0690] In this invention, the server includes a means for integrating and analyzing the received vital data and detecting patterns and abnormal values, a means for a generating artificial intelligence to generate personalized lifestyle improvement suggestions based on the integrated and analyzed vital data, and a means for re-evaluating the user's behavioral data and providing further feedback as necessary. This makes it possible to collect and analyze individual vital data in real time and provide the user with continuous and personalized lifestyle improvement suggestions.

[0691] A "wearable device" is a device worn by a user to collect vital data such as heart rate, exercise volume, dietary habits, sleep data, and stress levels in real time.

[0692] "Vital data" refers to data that indicates the user's physical and physiological condition, such as heart rate, amount of exercise, dietary content, sleep data, and stress level.

[0693] A "terminal" is a device that receives vital data sent from a wearable device and sends it to a server. Examples of such devices include smartphones and tablets.

[0694] The "server" is a computer system that consolidates and analyzes vital data sent from devices and detects patterns and abnormal values.

[0695] "Generative AI" is an AI model that generates individual lifestyle improvement suggestions based on integrated and analyzed vital data.

[0696] "Lifestyle Improvement Suggestions" are suggestions for improving the user's lifestyle, including specific instructions regarding diet, exercise, sleep, and stress management.

[0697] The "notification function" is a function that allows the device to visually present improvement suggestions and feedback to the user in real time.

[0698] "Feedback" is further instruction or advice provided to a user after they have taken a recommended action, based on additional data analysis.

[0699] The present invention provides lifestyle improvement suggestions based on individual vital data using a system including a wearable device, a terminal, a server, and a generating artificial intelligence. An embodiment of this system will be specifically described below.

[0700] Users wear a wearable device in their daily lives. The device collects various vital data in real time, such as heart rate, exercise volume, dietary intake, sleep data, and stress level. For example, when a user eats breakfast, the wearable device records the time and content of the meal. It also continuously collects data while the user is exercising or sleeping.

[0701] The vital data collected by the wearable device is sent to the user's device (a mobile device such as a smartphone or tablet) via Bluetooth or Wi-Fi. The device then sends the data to a server at regular intervals. For example, the data is uploaded at the end of each day or after a specific event.

[0702] The server uses cloud servers such as Amazon Web Services (AWS) and Google Cloud Platform (GCP) to integrate and centrally manage the received vital signs. The server is equipped with a generative artificial intelligence (AI model) that analyzes the integrated data and detects patterns and outliers. For example, it analyzes a user's exercise and diet data over the course of a week to detect lack of exercise or an unbalanced diet.

[0703] Based on the analysis results, the generative AI generates personalized lifestyle improvement suggestions for each user. These include specific instructions regarding diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods you eat at breakfast from now on" or exercise advice such as "Do 30 minutes of aerobic exercise every night" is generated. The generated lifestyle improvement suggestions are sent from the server to the user's device, where they are presented to the user. The device displays feedback in a visually easy-to-understand format, indicating specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as "Your recent dietary habits need improvement. Please check for detailed instructions."

[0704] After the user takes the recommended action based on the feedback, the wearable device again collects new vital signs and sends them back to the server. The generative AI re-evaluates the data to determine the effectiveness of the improvements and provides further feedback as needed, providing ongoing support for the user's health management.

[0705] Prompt Sentence Examples

[0706] "Please suggest appropriate exercise habits based on the user's exercise data for the week."

[0707] "Analyze the user's dietary data and generate recommendations for future dietary improvements."

[0708] The system of the present invention effectively utilizes individual vital data and provides lifestyle improvement suggestions tailored to the user, thereby contributing to the prevention of lifestyle-related diseases and maintaining motivation. In addition, because the entire system functions in real time, it is possible to immediately reflect the user's daily behavior.

[0709] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0710] Step 1:

[0711] Users wear a wearable device while going about their daily lives, and the device collects vital data such as heart rate, exercise volume, dietary habits, sleep data, and stress levels in real time.

[0712] Input: User activities

[0713] Data processing and output: Collected vital data is recorded in real time.

[0714] Step 2:

[0715] The vital data collected by the wearable device is sent to the user's device via Bluetooth or Wi-Fi.

[0716] Input: Vital data from a wearable device

[0717] Data processing and output: Vital data is periodically aggregated and transmitted to the device.

[0718] Step 3:

[0719] The terminal transmits the vital data received from the wearable terminal to the server at regular intervals.

[0720] Input: Vital data from a wearable device

[0721] Data processing and output: Organize data in the device and convert it into a format to send to the server.

[0722] Step 4:

[0723] The server integrates and centralizes the vital data it receives. The server is equipped with a generative artificial intelligence (AI model) that analyzes the integrated data to detect patterns and outliers.

[0724] Input: Vital data sent from the device

[0725] Data processing and output: Data is integrated and analyzed by AI models, and any patterns or anomalies detected are recorded.

[0726] Step 5:

[0727] Based on the analysis results, the generative artificial intelligence generates personalized lifestyle improvement suggestions.

[0728] Input: Integrated and analyzed data

[0729] Data processing and output: Generate lifestyle improvement suggestions based on the analysis results.

[0730] Step 6:

[0731] The server sends the generated lifestyle improvement suggestions to the terminal.

[0732] Input: AI-generated improvement suggestions

[0733] Data processing and output: Convert the improvement proposal into a format that can be sent to the terminal and send it.

[0734] Step 7:

[0735] The device presents improvement suggestions to the user in a visually easy-to-understand format.

[0736] Input: Improvement suggestions sent from the server

[0737] Data processing and output: Display improvement proposals in a format suitable for the user interface.

[0738] Step 8:

[0739] The user takes the recommended action based on the feedback, and the wearable device again collects new vital signs.

[0740] Input: User action

[0741] Data Processing and Output: New vital data is collected.

[0742] Step 9:

[0743] The device sends new vital data to the server, where the AI ​​reassess it, determines the effectiveness of any improvements, and provides further feedback as needed.

[0744] Input: New vitals

[0745] Data processing and output: Reassess the data and generate / send new feedback as needed.

[0746] (Application example 1)

[0747] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0748] While conventional wearable devices are effective for collecting vital data and improving lifestyle habits for individuals, they have not been applied to monitoring the health status and improving the efficiency of equipment in certain industries, particularly factories. Therefore, there is a need to monitor the health status of factory equipment in the same way as humans and provide specific improvement suggestions.

[0749] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0750] In this invention, the server comprises: means for collecting daily vital data from the wearable terminal; means for transmitting the vital data to the terminal; means for the terminal to transmit the vital data to the server; means for the server to integrate and analyze the vital data; means for a generating artificial intelligence to generate personalized lifestyle improvement suggestions based on the integrated and analyzed vital data; and means for transmitting the generated lifestyle improvement suggestions to the terminal and presenting them to the user.

[0751] a means for collecting operation data of the equipment from sensors attached to the equipment in the factory and analyzing the operation data;

[0752] A means for generating specific improvement plans to improve the operating efficiency of factory equipment based on the analyzed operation data by the generating artificial intelligence;

[0753] and a means for transmitting the generated improvement plan to a terminal of a factory manager and presenting it to the manager. This makes it possible to manage the health of users and improve the operating efficiency of factory equipment.

[0754] A "wearable device" is a device worn on the body to collect physiological data of the user.

[0755] "Vital data" refers to physiological data related to the health status of a user.

[0756] A "terminal" is an electronic device for receiving and processing vital data transmitted from a wearable terminal.

[0757] A "server" is a central control computer that integrates and analyzes data sent from the terminals.

[0758] "Generative AI" is an AI (artificial intelligence) technology that analyzes collected data and generates feedback and improvement suggestions tailored to specific purposes.

[0759] "Lifestyle improvement proposals" are specific action proposals that instruct changes or improvements to lifestyle habits, proposed based on vital data.

[0760] "Factory equipment" refers to industrial machines and devices used in production lines and work processes.

[0761] A "sensor" is a device that is attached to factory equipment and collects various operational data in real time.

[0762] "Operation data" refers to operational data generated when factory equipment is in operation.

[0763] "Improvement proposals" are specific instructions or suggestions for improving the operating efficiency of equipment based on analyzed data.

[0764] The "factory manager's terminal" is an electronic device used by the factory manager, and is a device for receiving and viewing improvement proposals.

[0765]

[0766] The present invention provides a system for integrating and analyzing data collected from wearable devices and sensors attached to factory equipment, thereby improving lifestyle habits and increasing the operating efficiency of factory equipment. A specific configuration for implementing the present invention will be described below.

[0767] First, the user puts on a wearable device, which collects various vital data in real time, such as heart rate, exercise volume, dietary habits, sleep data, and stress levels. The collected vital data is then sent to the user's smartphone, tablet, or other device via Bluetooth or Wi-Fi.

[0768] In factories, multiple sensors are attached to equipment to collect operational data in real time, such as temperature, vibration, operating frequency, and power consumption, which is also sent to a central server via the factory network.

[0769] The wearable device periodically transmits vital data collected from the device to a cloud server. The server is equipped with a generative artificial intelligence (generative AI model) that integrates and analyzes the received data. Based on the vital data, it generates specific improvement proposals to improve the user's lifestyle habits, and based on the operational data, it generates specific improvement proposals to improve the operating efficiency of equipment.

[0770] For example, by analyzing a week's worth of exercise and dietary data, the system can generate specific instructions for the user, such as "Increase the amount of high-protein foods you eat for breakfast in the future." It can also generate specific instructions for factory equipment, such as "The vibrations are too strong, so we recommend maintenance."

[0771] The generated improvement proposals are sent from the server to the user's device and the factory manager's device. The user and manager receive easy-to-understand visual feedback through their devices. For example, the user's device may receive a notification saying, "Your recent eating habits need improvement. Please check for detailed instructions." The factory manager's device may receive a notification saying, "We have detected an abnormality in Robot No. 1's motor temperature, exceeding 80 degrees. Please instruct immediate maintenance of the cooling system and motor."

[0772] To implement this system, the following hardware and software are used.

[0773] Hardware: Wearable devices, various sensors, smartphones, tablets, factory network equipment, and servers.

[0774] Software: Data collection module, cloud storage, generative artificial intelligence platform (e.g., Google Cloud AI, AWS SageMaker, Azure Machine Learning), feedback sharing app.

[0775] As a concrete example, if the sensor detects that the robot's motor temperature has exceeded 80 degrees, the prompt text would be as follows:

[0776] Prompt: "Robot #1's motor temperature has been detected to be above 80 degrees. Order immediate maintenance on the cooling system and motor."

[0777] In this way, the system of the present invention can continuously support user health management and improved operating efficiency of factory equipment by using wearable devices and factory sensors.

[0778] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0779] Step 1:

[0780] The user wears a wearable device, which collects various vital data in real time, such as heart rate, exercise volume, dietary content, sleep data, and stress level. The collected data is sent to the user's smartphone or tablet via Bluetooth or Wi-Fi. The input is the user's vital data, and the output is data sent to the device.

[0781] Step 2:

[0782] In factories, sensors attached to equipment collect operational data such as temperature, vibration, operating frequency, and power consumption in real time. The collected data is sent to a server via the factory network. The input is the equipment's operational data, and the output is data sent to the server.

[0783] Step 3:

[0784] The device periodically transmits vital data collected from the wearable device to a cloud server. The input is the vital data stored on the device, and the output is data sent to the cloud server.

[0785] Step 4:

[0786] The server integrates the vital data and operating data sent from the wearable devices and sensors and stores them in cloud storage. The input is the data sent to the server, and the output is the storage of the integrated data.

[0787] Step 5:

[0788] A generative artificial intelligence (generative AI model) installed on the server analyzes the integrated vital data and operational data. It generates lifestyle improvement suggestions based on the user's health condition, as well as improvement suggestions to improve the operating efficiency of the equipment. The input is the integrated data, and the output is improvement suggestions.

[0789] Step 6:

[0790] The generated improvement proposals are sent from the server to the user terminal and the factory manager's terminal. The input is the generated improvement proposal, and the output is the data sent to the terminal.

[0791] Step 7:

[0792] The user's device and the factory manager's device display improvement proposals in a visually easy-to-understand format and provide real-time feedback using a notification function. Specifically, the user's device displays a notification such as, "Your recent diet needs improvement. Please check for detailed instructions." The factory manager's device displays a notification such as, "An abnormality has been detected in Robot No. 1's motor temperature, exceeding 80 degrees. Please instruct immediate maintenance of the cooling system and motor." The input is improvement proposal data from the server, and the output is notifications to the user and factory manager.

[0793] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0794] The present invention provides lifestyle improvement suggestions based on individual vital data and emotion data using a system including a wearable device, a terminal, a server, generative artificial intelligence, and an emotion engine. The following describes specific embodiments of the present invention.

[0795] Users wear a wearable device in their daily lives. The device collects various vital data in real time, such as heart rate, exercise volume, dietary intake, sleep data, and stress levels. For example, when a user eats breakfast, the device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0796] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. When the device is connected, data is automatically synchronized. For example, heart rate and exercise volume data are sent to the device in real time.

[0797] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed.

[0798] The server integrates and centrally manages the received vital data. The server is equipped with generative artificial intelligence, which analyzes the integrated data. For example, it analyzes the user's data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume.

[0799] Based on the analysis results, the AI ​​generates personalized lifestyle improvement recommendations for each user, including specific instructions for diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods you eat at breakfast from now on" and exercise advice such as "Do 30 minutes of aerobic exercise every night" are generated.

[0800] Furthermore, the emotion engine recognizes the user's emotions. The emotion engine analyzes data such as the user's facial expressions, tone of voice, and physical movements to grasp the user's emotional state at that time. For example, while the user is operating the smartphone, the camera captures the face and analyzes the voice to determine emotions such as stress or joy.

[0801] The emotion data recognized by the emotion engine is also sent to the server, and the artificial intelligence combines it with vital data to generate further lifestyle improvement suggestions. For example, if stress levels are high, it will generate suggestions for relaxation exercises or advice on reconsidering the timing of work breaks.

[0802] The generated lifestyle improvement suggestions and emotional feedback are sent from the server to the user's device, where they are presented to the user. The device displays the feedback in a visually easy-to-understand format, suggesting specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as, "Your stress level seems high. Try doing some relaxation exercises."

[0803] After the user takes the recommended action based on the feedback, the wearable device again collects new vital data, which is again sent to the server via the device. The emotion engine also periodically collects emotional data and similarly sends it to the server. The generative AI reevaluates this data to determine the effectiveness of improvements and provides further feedback as needed. This provides ongoing support for the user's health management.

[0804] The system of the present invention effectively utilizes individual vital data and emotional data to provide lifestyle improvement suggestions tailored to the user, thereby contributing to the prevention of lifestyle-related diseases such as diabetes and their progression to more serious conditions. Furthermore, because the entire system functions in real time, it is possible to maintain the user's motivation in their daily lives and have their behavior reflected immediately.

[0805] The processing flow will be explained below.

[0806] Step 1:

[0807] Users wear a wearable device in their daily lives, which collects vital data such as heart rate, exercise volume, dietary intake, sleep data, and stress levels in real time. For example, when a user eats breakfast, the wearable device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0808] Step 2:

[0809] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. Once the device is connected, data is automatically synchronized. For example, heart rate and exercise data are sent to the device in real time.

[0810] Step 3:

[0811] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed.

[0812] Step 4:

[0813] The server integrates and centrally manages the received vital data, for example, heart rate data, exercise data, dietary data, sleep data, and stress data, and manages them as a single data set.

[0814] Step 5:

[0815] The server-based generative artificial intelligence analyzes the integrated vital data. For example, it analyzes data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume.

[0816] Step 6:

[0817] Based on the analysis results, the AI ​​generates personalized lifestyle improvement suggestions suited to each individual user. For example, if it determines that the user is not getting enough exercise, it will generate specific instructions such as "recommended 30 minutes of walking on the weekend." It also generates advice on diet and suggestions for improving sleep.

[0818] Step 7:

[0819] The device uses an emotion engine to recognize the user's emotions and collects emotion data from the user's facial expressions, tone of voice, and body movements. For example, if the user is feeling stressed, the emotion engine will detect this.

[0820] Step 8:

[0821] The emotional data collected by the device is sent to a server, where it is centrally managed and analyzed in combination with vital data. For example, it can analyze the time periods and situations in which the user feels stressed.

[0822] Step 9:

[0823] The generative AI will then analyze the emotional and vital data to generate more specific lifestyle improvement recommendations, such as "Perform relaxation exercises every night to reduce stress."

[0824] Step 10:

[0825] The server then sends the lifestyle improvement suggestions it has generated to the device, which then presents them to the user and displays feedback in a visually easy-to-understand format. For example, real-time feedback such as "Your stress level seems high. Try some relaxation exercises" is provided.

[0826] Step 11:

[0827] The user performs the recommended action based on the feedback, such as walking or exercising, and then the data is collected again by the wearable device.

[0828] Step 12:

[0829] The device again transmits the newly collected vital data and emotional data to the server, which receives it and analyzes it again using the artificial intelligence.

[0830] Step 13:

[0831] The generative AI reassess the new vital and emotional data to determine whether improvements or new guidance are needed. For example, it evaluates the patient's condition after a walk and provides feedback such as, "Your blood sugar level has improved. Continue to maintain good lifestyle habits."

[0832] Example 2

[0833] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0834] Conventional health management systems can only provide static advice based on a user's vital signs, and lack a dynamic approach that takes into account the user's emotional state. Furthermore, due to insufficient real-time feedback, it is difficult to provide timely improvement suggestions that are tailored to the user's daily life.

[0835] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for integrating and analyzing vital data, means for a generating artificial intelligence to generate personalized lifestyle improvement suggestions, means for an emotion engine to collect and analyze emotion data, and means for combining the emotion data with vital data to generate additional lifestyle improvement suggestions. This makes it possible to analyze the user's vital data and emotion data in an integrated manner, and to provide more personalized and appropriate lifestyle improvement suggestions in real time that are tailored to the user's health condition and emotions.

[0836] A "wearable device" is a compact electronic device that can be worn by the user and collects vital data such as heart rate, exercise volume, dietary content, sleep data, and stress level in real time.

[0837] "Vital data" refers to basic physiological data necessary to understand a user's health condition, and specifically refers to data such as heart rate, amount of exercise, diet, sleep data, and stress level.

[0838] A "terminal" is an electronic device that receives collected vital data from a user's wearable device, synchronizes the data, and transmits the data to a server, and includes smartphones, tablets, etc.

[0839] The "server" is a computer system that integrates and analyzes vital data and emotional data sent from terminals via the Internet.

[0840] "Generative AI" refers to an AI program that analyzes collected vital data and generates personalized lifestyle improvement suggestions.

[0841] An "emotion engine" refers to software or hardware that analyzes a user's emotional state from facial expressions, tone of voice, physical movements, etc., and collects this as emotional data.

[0842] "Personalized lifestyle changes" refers to specific suggestions for diet, exercise, sleep, and stress management that are generated based on a user's individual vital and emotional data.

[0843] "Emotion data" refers to data that indicates the user's emotional state, and is obtained by analyzing facial expressions, tone of voice, body movements, and the like using an emotion engine.

[0844] The present invention provides lifestyle improvement suggestions based on individual vital data and emotional data using a system including a wearable terminal, a terminal, a server, generative artificial intelligence, and an emotion engine.

[0845] Users wear a wearable device in their daily lives. The device collects vital data such as heart rate, exercise volume, dietary intake, sleep data, and stress levels in real time. For example, when a user eats breakfast, the wearable device records the time and content of the meal. It also continuously collects data while exercising or sleeping. Specific hardware used includes the Apple Watch and Fitbit.

[0846] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. When the device is connected, data is automatically synchronized. For example, heart rate and exercise data are sent to the device in real time. This device includes iPhones and Android smartphones.

[0847] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed. Specific transmission protocols used are HTTP / HTTPS, Bluetooth, and Wi-Fi.

[0848] The server consolidates the received vital data and manages it centrally. The server is equipped with generative artificial intelligence that analyzes the consolidated data. For example, it analyzes the user's data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume. The specific server environment used is Amazon Web Services (AWS) or Google Cloud.

[0849] Based on the analysis results, the generative AI generates personalized lifestyle improvement recommendations for each user. These include specific instructions regarding diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods at breakfast from now on" and exercise advice such as "Do 30 minutes of aerobic exercise every night" are generated. The generative AI model uses a Python-based model, and an example of a prompt for this model is, "Analyze one week's heart rate data and exercise records to create a graph showing health trends. Please also include suggestions for relaxation exercises if stress levels are high."

[0850] Furthermore, the emotion engine recognizes the user's emotions. The emotion engine analyzes data such as the user's facial expressions, tone of voice, and physical movements to understand their emotional state at that time. For example, while the user is operating the smartphone, the camera captures their face and analyzes their voice to determine emotions such as stress or joy. The emotion engine includes facial expression analysis using OpenCV and TensorFlow.

[0851] The emotion data recognized by the emotion engine is also sent to the server, and the artificial intelligence combines it with vital data to generate further lifestyle improvement suggestions. For example, if stress levels are high, it will generate suggestions for relaxation exercises or advice on reconsidering the timing of work breaks.

[0852] The generated lifestyle improvement suggestions and emotional feedback are sent from the server to the user's device, where they are presented to the user. The device displays the feedback in a visually easy-to-understand format, suggesting specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as, "Your stress level seems high. Try doing some relaxation exercises."

[0853] After the user takes the recommended action based on the feedback, the wearable device again collects new vital data, which is again sent to the server via the device. The emotion engine also periodically collects emotional data and similarly sends it to the server. The generative AI reevaluates this data to determine the effectiveness of improvements and provides further feedback as needed. This provides ongoing support for the user's health management.

[0854] The system of the present invention effectively utilizes individual vital data and emotional data to provide lifestyle improvement suggestions tailored to the user, thereby contributing to the prevention of lifestyle-related diseases such as diabetes and their progression to more serious conditions. Furthermore, because the entire system functions in real time, it is possible to maintain the user's motivation in their daily lives and have their behavior reflected immediately.

[0855] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0856] Step 1:

[0857] Users wear a wearable device in their daily lives, which collects vital data such as heart rate, exercise volume, dietary habits, sleep data, and stress levels in real time.

[0858] Input: User's daily activities and physiological status

[0859] Specific operation: Specifically, when the user eats breakfast, the time and contents of the meal are recorded. Data is also collected continuously during exercise and while sleeping.

[0860] Output: Collected vital data

[0861] Step 2:

[0862] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. Once the device is connected, data is automatically synchronized.

[0863] Input: Vital data collected by a wearable device

[0864] Specific operation: Heart rate and exercise data are sent to your smartphone in real time.

[0865] Output: Vital data stored on the user's device

[0866] Step 3:

[0867] The device periodically transmits vital data to the server at set intervals, such as at the end of each day or after a specific event, and the success status of the data transmission is confirmed.

[0868] Input: Vital data stored on the device

[0869] Specific operation: Heart rate and exercise data are uploaded to the server at midnight.

[0870] Output: Vital data stored on the server

[0871] Step 4:

[0872] The server integrates and centrally manages the received vital data. The server is equipped with a generative artificial intelligence that analyzes the integrated data.

[0873] Input: Vital data stored on the server

[0874] How it works: The AI ​​model analyzes heart rate data from the past week to detect outliers and health trends, and analyzes diet and exercise trends to assess fluctuations in health.

[0875] Output: Analysis results (detection of outliers, health trends, etc.)

[0876] Step 5:

[0877] Based on the analysis, the generative AI model generates personalized lifestyle recommendations for each user, including specific instructions for diet, exercise, sleep, and stress management.

[0878] Input: Analysis results

[0879] Specific actions: Guidance such as "Increase the amount of high-protein foods at breakfast" or "Do 30 minutes of aerobic exercise every night" is generated.

[0880] Output: Personalized lifestyle changes

[0881] Step 6:

[0882] To recognize the user's emotions, the emotion engine analyzes the user's facial expressions, tone of voice, body movements, etc. This data is collected to understand the user's emotional state.

[0883] Input: User's facial expressions, tone of voice, and physical movements

[0884] Specific actions: Captures faces, analyzes tone of voice, and determines emotions such as stress or joy.

[0885] Output: Emotion data

[0886] Step 7:

[0887] Emotional data recognized by the emotion engine is also sent to the server, and the generative AI model combines this with vital data to generate further lifestyle improvement suggestions.

[0888] Input: Emotion data, vital data

[0889] Specific actions: If stress levels are high, suggestions for relaxation exercises and advice on reconsidering work break timing will be generated.

[0890] Output: Additional lifestyle changes

[0891] Step 8:

[0892] The server sends the generated lifestyle improvement suggestions and emotion-based feedback to the user's device, which then presents them to the user. Real-time feedback is provided using a notification function.

[0893] Input: Additional lifestyle changes

[0894] Specific behavior: The device uses the notification function to notify you, "Your stress level seems high. Try some relaxation exercises."

[0895] Output: Presented feedback to the user

[0896] Step 9:

[0897] After the user takes action based on the feedback, the wearable device again collects new vital data, which is then sent to the server via the device. The emotion engine also periodically collects emotional data and sends it to the server in the same way.

[0898] Input: Vital data and emotional data after user actions

[0899] What happens: Heart rate data is collected after a relaxation exercise.

[0900] Output: New vital and emotional data collected

[0901] Step 10:

[0902] A generative AI model re-evaluates this data, determines the effectiveness of improvements, and provides further feedback as needed, supporting the user in managing their health on an ongoing basis.

[0903] Input: New vital and emotional data

[0904] Specific actions: Evaluate whether relaxation exercises have improved stress levels and provide new suggestions.

[0905] Output: Reevaluated results and further feedback

[0906] (Application example 2)

[0907] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0908] Health management is becoming increasingly important in modern society, but it is difficult to receive personalized advice in real time that takes into account individual lifestyle habits and health conditions. Furthermore, physical stores often lack the information necessary to provide optimal services to each individual customer. Therefore, there is a need for a system that provides personalized services to customers and supports health management based on vital signs and emotional data.

[0909] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting daily vital data from the wearable device, means for transmitting the vital data to the device, means for the device to transmit the vital data to the server, means for the server to integrate and analyze the vital data, means for a generative artificial intelligence to generate personalized lifestyle improvement suggestions based on the integrated and analyzed vital data, means for transmitting the generated lifestyle improvement suggestions to the device and presenting them to the user, and a brick-and-mortar store application that provides customized services based on the vital data and emotion data when a customer visits a brick-and-mortar store while wearing a wearable device. This makes it possible to provide lifestyle improvement suggestions tailored to individual users in real time, and to provide personalized services even in brick-and-mortar stores.

[0910] A "wearable device" is a device that can be worn by a user and collects and transmits vital data such as heart rate, amount of exercise, dietary content, sleep data, and stress level in real time.

[0911] "Vital data" refers to biological information such as heart rate, blood sugar level, amount of exercise, sleep data, and stress level that indicates the user's health condition.

[0912] A "terminal" is a device (such as a smartphone or tablet) that has the function of receiving collected vital data and sending it to a server.

[0913] The "server" is a computer that integrates and analyzes vital data sent from the device and generates personalized lifestyle improvement suggestions using generative artificial intelligence.

[0914] "Generative AI" is an algorithm that automatically generates optimal lifestyle improvement suggestions for users based on integrated and analyzed vital data.

[0915] "Lifestyle changes" are advice that includes specific instructions and recommendations regarding diet, exercise, sleep, and stress management.

[0916] "Emotion data" is information indicating the user's emotional state obtained from facial expressions, tone of voice, body movements, and the like.

[0917] The "physical store application" is software that provides customized services based on vital and emotional data when customers visit a physical store while wearing a wearable device.

[0918] The present invention provides a specific means for providing personalized services to customers using a system including a wearable terminal, a terminal, a server, a generative artificial intelligence, and an emotion engine. The following describes specific embodiments of the present invention.

[0919] Users wear a wearable device in their daily lives. The device collects various vital data in real time, such as heart rate, exercise volume, dietary intake, sleep data, and stress levels. For example, when a user eats breakfast, the device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0920] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. When the device is connected, data is automatically synchronized. For example, heart rate and exercise volume data are sent to the device in real time.

[0921] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed.

[0922] The server integrates and centrally manages the received vital data. The server is equipped with generative artificial intelligence, which analyzes the integrated data. For example, it analyzes the user's data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume.

[0923] Based on the analysis results, the AI ​​generates personalized lifestyle improvement recommendations for each user, including specific instructions for diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods you eat at breakfast from now on" and exercise advice such as "Do 30 minutes of aerobic exercise every night" are generated.

[0924] Furthermore, the emotion engine recognizes the user's emotions. The emotion engine analyzes data such as the user's facial expressions, tone of voice, and physical movements to grasp the user's emotional state at that time. For example, while the user is operating the smartphone, the camera captures the face and analyzes the voice to determine emotions such as stress or joy.

[0925] The emotion data recognized by the emotion engine is also sent to the server, and the artificial intelligence combines it with vital data to generate further lifestyle improvement suggestions. For example, if stress levels are high, it will generate suggestions for relaxation exercises or advice on reconsidering the timing of work breaks.

[0926] In addition, an important component of the present invention is a store application that provides customized services based on vital data and emotional data when a customer wearing a wearable device visits a store. For example, if a user is determined to be in a high-stress state, the application can guide the user to a relaxing area in the store or provide products that will reduce stress.

[0927] The generated lifestyle improvement suggestions and emotional feedback are sent from the server to the user's device, where they are presented to the user. The device displays the feedback in a visually easy-to-understand format, suggesting specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as, "Your stress level seems high. Try doing some relaxation exercises."

[0928] Below is an example prompt that includes guidelines for providing customized services based on wearable device data when customers visit a store.

[0929] Example prompt sentence:

[0930] "Please suggest personalized in-store services based on the vital and emotional data of user ID: user12345."

[0931] The above is a specific description based on an embodiment of the present invention. This system configuration allows for real-time provision of lifestyle improvement suggestions tailored to individual users, and also makes it possible to provide personalized services in brick-and-mortar stores.

[0932] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0933] Step 1:

[0934] Users wear a wearable device and collect vital data during their daily lives. Specifically, the wearable device records heart rate, exercise, diet, sleep, stress level, etc. in real time. The input is the user's daily data, and the output is the collected vital data.

[0935] Step 2:

[0936] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. When the device is connected, data synchronization is performed automatically. The input is the collected vital data, and the output is the synchronized data sent to the device.

[0937] Step 3:

[0938] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed. The input is the vital data on the device, and the output is the data sent to the server.

[0939] Step 4:

[0940] The server integrates the received vital data and manages it centrally. The server is equipped with generative artificial intelligence that analyzes the integrated data. The input is the vital data sent to the server, and the output is the integrated and analyzed data.

[0941] Step 5:

[0942] The server's artificial intelligence generates personalized lifestyle improvement recommendations for each user based on the analyzed data. For example, it analyzes the user's data from the past week, detects abnormal values ​​and health trends, and generates specific advice. The input is the integrated and analyzed data, and the output is the generated improvement recommendations.

[0943] Step 6:

[0944] The emotion engine analyzes data such as facial expressions, tone of voice, and body movements to recognize the user's emotions. For example, while the user is operating a smartphone, a camera captures the face and analyzes the voice to determine the emotion. The input is the user's emotion-related data, and the output is the analyzed emotion data.

[0945] Step 7:

[0946] The server receives the emotional data from the emotion engine and combines it with vital data to generate further lifestyle improvement recommendations. For example, if stress levels are high, it will suggest relaxation exercises. The input is emotional data and vital data, and the output is further personalized improvement recommendations.

[0947] Step 8:

[0948] When a user visits a physical store while wearing a wearable device, the system provides customized services based on their vital and emotional data. Specifically, this includes guiding them to relaxation areas and recommending appropriate products based on the user's stress level. The input is the user's latest vital and emotional data, and the output is the provision of personalized services.

[0949] Step 9:

[0950] The generated lifestyle improvement suggestions and emotional feedback are sent from the server to the user's device and presented in a visually easy-to-understand format. Specifically, real-time feedback is provided using a notification function. The input is the generated improvement suggestions, and the output is the feedback displayed on the user's device.

[0951] The above is the processing flow of the system that provides personalized services using vital data and emotional data.

[0952] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0953] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0954] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[0955] [Fourth embodiment]

[0956] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0957] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0958] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0959] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0960] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0961] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0962] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0963] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0964] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0965] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0966] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0967] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0968] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[0969] The present invention provides lifestyle improvement suggestions based on individual vital data using a system including a wearable device, a terminal, a server, and a generating artificial intelligence. Hereinafter, an embodiment of the present invention will be described in detail.

[0970] Users wear a wearable device in their daily lives. The device collects various vital data in real time, such as heart rate, exercise volume, dietary intake, sleep data, and stress levels. For example, when a user eats breakfast, the device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0971] The vital data collected by the wearable device is sent to the user's device (a mobile device such as a smartphone or tablet) via Bluetooth or Wi-Fi. The device then sends this data to a server at regular intervals. For example, the data is uploaded at the end of each day or after a specific event.

[0972] The server integrates and centrally manages the received vital data. The server is equipped with generative artificial intelligence that analyzes the integrated data. For example, it analyzes a user's exercise and diet data over the course of a week to detect patterns and abnormal values.

[0973] Based on the analysis results, the AI ​​generates personalized lifestyle improvement recommendations for each user, including specific instructions for diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods you eat at breakfast from now on" and exercise advice such as "Do 30 minutes of aerobic exercise every night" are generated.

[0974] The generated lifestyle improvement suggestions are sent from the server to the user's device, where they are presented to the user. The device displays the feedback in a visually easy-to-understand format, indicating the specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as, "Your recent dietary habits need improvement. Please check for detailed instructions."

[0975] After the user takes the recommended action based on the feedback, the wearable device again collects new vital signs and sends them back to the server. The generative AI re-evaluates the data to determine the effectiveness of the improvements and provides further feedback as needed, providing ongoing support for the user's health management.

[0976] The system of the present invention effectively utilizes individual vital data and provides lifestyle improvement suggestions tailored to each user, thereby contributing to the prevention of lifestyle-related diseases such as diabetes and their progression to more serious conditions. Furthermore, because the entire system functions in real time, it is possible to maintain the user's motivation in their daily lives and have their behavior reflected immediately.

[0977] The processing flow will be explained below.

[0978] Step 1:

[0979] Users wear a wearable device in their daily lives, which collects vital data such as heart rate, exercise volume, dietary intake, sleep data, and stress levels in real time. For example, when a user eats breakfast, the wearable device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[0980] Step 2:

[0981] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. Once the device is connected, data is automatically synchronized. For example, heart rate and exercise data are sent to the device in real time.

[0982] Step 3:

[0983] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed.

[0984] Step 4:

[0985] The server integrates the received vital data and manages it centrally. For example, it integrates heart rate data, exercise data, dietary data, sleep data, and stress data and manages them as a single data set.

[0986] Step 5:

[0987] The server-based generative artificial intelligence analyzes the integrated vital data. For example, it analyzes data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume.

[0988] Step 6:

[0989] Based on the analysis results, the AI ​​generates personalized lifestyle improvement suggestions suited to each individual user. For example, if it determines that the user is not getting enough exercise, it will generate specific instructions such as "recommended 30 minutes of walking on the weekend." It also generates advice on diet and suggestions for improving sleep.

[0990] Step 7:

[0991] The server sends the generated lifestyle improvement suggestions to the device, which receives them and presents them to the user in a visually easy-to-understand format. For example, a notification function can be used to provide real-time feedback such as, "Your recent dietary habits need improvement. Please check for detailed instructions."

[0992] Step 8:

[0993] Based on the feedback, the user performs the recommended action, such as walking or exercising, and then the data is collected again by the wearable device.

[0994] Step 9:

[0995] The device then sends the newly collected vital data back to the server, which receives it and analyzes it again using the artificial intelligence.

[0996] Step 10:

[0997] The generative AI reassess the new vital data and determines whether improvements or new guidance are needed. For example, it evaluates the patient's condition after walking and provides feedback such as, "Your blood sugar level has improved. Continue to maintain good lifestyle habits."

[0998] Example 1

[0999] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1000] As the need for prevention and management of lifestyle-related diseases increases in modern times, there is a need to effectively utilize individual vital signs data and provide users with appropriate lifestyle improvement suggestions. However, existing systems do not adequately collect data in real time or provide personalized improvement suggestions, making it difficult to continuously support users' health management.

[1001] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1002] In this invention, the server includes a means for integrating and analyzing the received vital data and detecting patterns and abnormal values, a means for a generating artificial intelligence to generate personalized lifestyle improvement suggestions based on the integrated and analyzed vital data, and a means for re-evaluating the user's behavioral data and providing further feedback as necessary. This makes it possible to collect and analyze individual vital data in real time and provide the user with continuous and personalized lifestyle improvement suggestions.

[1003] A "wearable device" is a device worn by a user to collect vital data such as heart rate, exercise volume, dietary habits, sleep data, and stress levels in real time.

[1004] "Vital data" refers to data that indicates the user's physical and physiological condition, such as heart rate, amount of exercise, dietary content, sleep data, and stress level.

[1005] A "terminal" is a device that receives vital data sent from a wearable device and sends it to a server. Examples of such devices include smartphones and tablets.

[1006] The "server" is a computer system that consolidates and analyzes vital data sent from devices and detects patterns and abnormal values.

[1007] "Generative AI" is an AI model that generates individual lifestyle improvement suggestions based on integrated and analyzed vital data.

[1008] "Lifestyle Improvement Suggestions" are suggestions for improving the user's lifestyle, including specific instructions regarding diet, exercise, sleep, and stress management.

[1009] The "notification function" is a function that allows the device to visually present improvement suggestions and feedback to the user in real time.

[1010] "Feedback" is further instruction or advice provided to a user after they have taken a recommended action, based on additional data analysis.

[1011] The present invention provides lifestyle improvement suggestions based on individual vital data using a system including a wearable device, a terminal, a server, and a generating artificial intelligence. An embodiment of this system will be specifically described below.

[1012] Users wear a wearable device in their daily lives. The device collects various vital data in real time, such as heart rate, exercise volume, dietary intake, sleep data, and stress level. For example, when a user eats breakfast, the wearable device records the time and content of the meal. It also continuously collects data while the user is exercising or sleeping.

[1013] The vital data collected by the wearable device is sent to the user's device (a mobile device such as a smartphone or tablet) via Bluetooth or Wi-Fi. The device then sends the data to a server at regular intervals. For example, the data is uploaded at the end of each day or after a specific event.

[1014] The server uses cloud servers such as Amazon Web Services (AWS) and Google Cloud Platform (GCP) to integrate and centrally manage the received vital signs. The server is equipped with a generative artificial intelligence (AI model) that analyzes the integrated data and detects patterns and outliers. For example, it analyzes a user's exercise and diet data over the course of a week to detect lack of exercise or an unbalanced diet.

[1015] Based on the analysis results, the generative AI generates personalized lifestyle improvement suggestions for each user. These include specific instructions regarding diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods you eat at breakfast from now on" or exercise advice such as "Do 30 minutes of aerobic exercise every night" is generated. The generated lifestyle improvement suggestions are sent from the server to the user's device, where they are presented to the user. The device displays feedback in a visually easy-to-understand format, indicating specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as "Your recent dietary habits need improvement. Please check for detailed instructions."

[1016] After the user takes the recommended action based on the feedback, the wearable device again collects new vital signs and sends them back to the server. The generative AI re-evaluates the data to determine the effectiveness of the improvements and provides further feedback as needed, providing ongoing support for the user's health management.

[1017] Prompt Sentence Examples

[1018] "Please suggest appropriate exercise habits based on the user's exercise data for the week."

[1019] "Analyze the user's dietary data and generate recommendations for future dietary improvements."

[1020] The system of the present invention effectively utilizes individual vital data and provides lifestyle improvement suggestions tailored to the user, thereby contributing to the prevention of lifestyle-related diseases and maintaining motivation. In addition, because the entire system functions in real time, it is possible to immediately reflect the user's daily behavior.

[1021] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1022] Step 1:

[1023] Users wear a wearable device while going about their daily lives, and the device collects vital data such as heart rate, exercise volume, dietary habits, sleep data, and stress levels in real time.

[1024] Input: User activities

[1025] Data processing and output: Collected vital data is recorded in real time.

[1026] Step 2:

[1027] The vital data collected by the wearable device is sent to the user's device via Bluetooth or Wi-Fi.

[1028] Input: Vital data from a wearable device

[1029] Data processing and output: Vital data is periodically aggregated and transmitted to the device.

[1030] Step 3:

[1031] The terminal transmits the vital data received from the wearable terminal to the server at regular intervals.

[1032] Input: Vital data from a wearable device

[1033] Data processing and output: Organize data in the device and convert it into a format to send to the server.

[1034] Step 4:

[1035] The server integrates and centralizes the vital data it receives. The server is equipped with a generative artificial intelligence (AI model) that analyzes the integrated data to detect patterns and outliers.

[1036] Input: Vital data sent from the device

[1037] Data processing and output: Data is integrated and analyzed by AI models, and any patterns or anomalies detected are recorded.

[1038] Step 5:

[1039] Based on the analysis results, the generative artificial intelligence generates personalized lifestyle improvement suggestions.

[1040] Input: Integrated and analyzed data

[1041] Data processing and output: Generate lifestyle improvement suggestions based on the analysis results.

[1042] Step 6:

[1043] The server sends the generated lifestyle improvement suggestions to the terminal.

[1044] Input: AI-generated improvement suggestions

[1045] Data processing and output: Convert the improvement proposal into a format that can be sent to the terminal and send it.

[1046] Step 7:

[1047] The device presents improvement suggestions to the user in a visually easy-to-understand format.

[1048] Input: Improvement suggestions sent from the server

[1049] Data processing and output: Display improvement proposals in a format suitable for the user interface.

[1050] Step 8:

[1051] The user takes the recommended action based on the feedback, and the wearable device again collects new vital signs.

[1052] Input: User action

[1053] Data Processing and Output: New vital data is collected.

[1054] Step 9:

[1055] The device sends new vital data to the server, where the AI ​​reassess it, determines the effectiveness of any improvements, and provides further feedback as needed.

[1056] Input: New vitals

[1057] Data processing and output: Reassess the data and generate / send new feedback as needed.

[1058] (Application example 1)

[1059] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1060] While conventional wearable devices are effective for collecting vital data and improving lifestyle habits for individuals, they have not been applied to monitoring the health status and improving the efficiency of equipment in certain industries, particularly factories. Therefore, there is a need to monitor the health status of factory equipment in the same way as humans and provide specific improvement suggestions.

[1061] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1062] In this invention, the server comprises: means for collecting daily vital data from the wearable terminal; means for transmitting the vital data to the terminal; means for the terminal to transmit the vital data to the server; means for the server to integrate and analyze the vital data; means for a generating artificial intelligence to generate personalized lifestyle improvement suggestions based on the integrated and analyzed vital data; and means for transmitting the generated lifestyle improvement suggestions to the terminal and presenting them to the user.

[1063] a means for collecting operation data of the equipment from sensors attached to the equipment in the factory and analyzing the operation data;

[1064] A means for generating specific improvement plans to improve the operating efficiency of factory equipment based on the analyzed operation data by the generating artificial intelligence;

[1065] and a means for transmitting the generated improvement plan to a terminal of a factory manager and presenting it to the manager. This makes it possible to manage the health of users and improve the operating efficiency of factory equipment.

[1066] A "wearable device" is a device worn on the body to collect physiological data of the user.

[1067] "Vital data" refers to physiological data related to the health status of a user.

[1068] A "terminal" is an electronic device for receiving and processing vital data transmitted from a wearable terminal.

[1069] A "server" is a central control computer that integrates and analyzes data sent from the terminals.

[1070] "Generative AI" is an AI (artificial intelligence) technology that analyzes collected data and generates feedback and improvement suggestions tailored to specific purposes.

[1071] "Lifestyle improvement proposals" are specific action proposals that instruct changes or improvements to lifestyle habits, proposed based on vital data.

[1072] "Factory equipment" refers to industrial machines and devices used in production lines and work processes.

[1073] A "sensor" is a device that is attached to factory equipment and collects various operational data in real time.

[1074] "Operation data" refers to operational data generated when factory equipment is in operation.

[1075] "Improvement proposals" are specific instructions or suggestions for improving the operating efficiency of equipment based on analyzed data.

[1076] The "factory manager's terminal" is an electronic device used by the factory manager, and is a device for receiving and viewing improvement proposals.

[1077]

[1078] The present invention provides a system for integrating and analyzing data collected from wearable devices and sensors attached to factory equipment, thereby improving lifestyle habits and increasing the operating efficiency of factory equipment. A specific configuration for implementing the present invention will be described below.

[1079] First, the user puts on a wearable device, which collects various vital data in real time, such as heart rate, exercise volume, dietary habits, sleep data, and stress levels. The collected vital data is then sent to the user's smartphone, tablet, or other device via Bluetooth or Wi-Fi.

[1080] In factories, multiple sensors are attached to equipment to collect operational data in real time, such as temperature, vibration, operating frequency, and power consumption, which is also sent to a central server via the factory network.

[1081] The wearable device periodically transmits vital data collected from the device to a cloud server. The server is equipped with a generative artificial intelligence (generative AI model) that integrates and analyzes the received data. Based on the vital data, it generates specific improvement proposals to improve the user's lifestyle habits, and based on the operational data, it generates specific improvement proposals to improve the operating efficiency of equipment.

[1082] For example, by analyzing a week's worth of exercise and dietary data, the system can generate specific instructions for the user, such as "Increase the amount of high-protein foods you eat for breakfast in the future." It can also generate specific instructions for factory equipment, such as "The vibrations are too strong, so we recommend maintenance."

[1083] The generated improvement proposals are sent from the server to the user's device and the factory manager's device. The user and manager receive easy-to-understand visual feedback through their devices. For example, the user's device may receive a notification saying, "Your recent eating habits need improvement. Please check for detailed instructions." The factory manager's device may receive a notification saying, "We have detected an abnormality in Robot No. 1's motor temperature, exceeding 80 degrees. Please instruct immediate maintenance of the cooling system and motor."

[1084] To implement this system, the following hardware and software are used.

[1085] Hardware: Wearable devices, various sensors, smartphones, tablets, factory network equipment, and servers.

[1086] Software: Data collection module, cloud storage, generative artificial intelligence platform (e.g., Google Cloud AI, AWS SageMaker, Azure Machine Learning), feedback sharing app.

[1087] As a concrete example, if the sensor detects that the robot's motor temperature has exceeded 80 degrees, the prompt text would be as follows:

[1088] Prompt: "Robot #1's motor temperature has been detected to be above 80 degrees. Order immediate maintenance on the cooling system and motor."

[1089] In this way, the system of the present invention can continuously support user health management and improved operating efficiency of factory equipment by using wearable devices and factory sensors.

[1090] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1091] Step 1:

[1092] The user wears a wearable device, which collects various vital data in real time, such as heart rate, exercise volume, dietary content, sleep data, and stress level. The collected data is sent to the user's smartphone or tablet via Bluetooth or Wi-Fi. The input is the user's vital data, and the output is data sent to the device.

[1093] Step 2:

[1094] In factories, sensors attached to equipment collect operational data such as temperature, vibration, operating frequency, and power consumption in real time. The collected data is sent to a server via the factory network. The input is the equipment's operational data, and the output is data sent to the server.

[1095] Step 3:

[1096] The device periodically transmits vital data collected from the wearable device to a cloud server. The input is the vital data stored on the device, and the output is data sent to the cloud server.

[1097] Step 4:

[1098] The server integrates the vital data and operating data sent from the wearable devices and sensors and stores them in cloud storage. The input is the data sent to the server, and the output is the storage of the integrated data.

[1099] Step 5:

[1100] A generative artificial intelligence (generative AI model) installed on the server analyzes the integrated vital data and operational data. It generates lifestyle improvement suggestions based on the user's health condition, as well as improvement suggestions to improve the operating efficiency of the equipment. The input is the integrated data, and the output is improvement suggestions.

[1101] Step 6:

[1102] The generated improvement proposals are sent from the server to the user terminal and the factory manager's terminal. The input is the generated improvement proposal, and the output is the data sent to the terminal.

[1103] Step 7:

[1104] The user's device and the factory manager's device display improvement proposals in a visually easy-to-understand format and provide real-time feedback using a notification function. Specifically, the user's device displays a notification such as, "Your recent diet needs improvement. Please check for detailed instructions." The factory manager's device displays a notification such as, "An abnormality has been detected in Robot No. 1's motor temperature, exceeding 80 degrees. Please instruct immediate maintenance of the cooling system and motor." The input is improvement proposal data from the server, and the output is notifications to the user and factory manager.

[1105] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1106] The present invention provides lifestyle improvement suggestions based on individual vital data and emotion data using a system including a wearable device, a terminal, a server, generative artificial intelligence, and an emotion engine. The following describes specific embodiments of the present invention.

[1107] Users wear a wearable device in their daily lives. The device collects various vital data in real time, such as heart rate, exercise volume, dietary intake, sleep data, and stress levels. For example, when a user eats breakfast, the device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[1108] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. When the device is connected, data is automatically synchronized. For example, heart rate and exercise volume data are sent to the device in real time.

[1109] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed.

[1110] The server integrates and centrally manages the received vital data. The server is equipped with generative artificial intelligence, which analyzes the integrated data. For example, it analyzes the user's data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume.

[1111] Based on the analysis results, the AI ​​generates personalized lifestyle improvement recommendations for each user, including specific instructions for diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods you eat at breakfast from now on" and exercise advice such as "Do 30 minutes of aerobic exercise every night" are generated.

[1112] Furthermore, the emotion engine recognizes the user's emotions. The emotion engine analyzes data such as the user's facial expressions, tone of voice, and physical movements to grasp the user's emotional state at that time. For example, while the user is operating the smartphone, the camera captures the face and analyzes the voice to determine emotions such as stress or joy.

[1113] The emotion data recognized by the emotion engine is also sent to the server, and the artificial intelligence combines it with vital data to generate further lifestyle improvement suggestions. For example, if stress levels are high, it will generate suggestions for relaxation exercises or advice on reconsidering the timing of work breaks.

[1114] The generated lifestyle improvement suggestions and emotional feedback are sent from the server to the user's device, where they are presented to the user. The device displays the feedback in a visually easy-to-understand format, suggesting specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as, "Your stress level seems high. Try doing some relaxation exercises."

[1115] After the user takes the recommended action based on the feedback, the wearable device again collects new vital data, which is again sent to the server via the device. The emotion engine also periodically collects emotional data and similarly sends it to the server. The generative AI reevaluates this data to determine the effectiveness of improvements and provides further feedback as needed. This provides ongoing support for the user's health management.

[1116] The system of the present invention effectively utilizes individual vital data and emotional data to provide lifestyle improvement suggestions tailored to the user, thereby contributing to the prevention of lifestyle-related diseases such as diabetes and their progression to more serious conditions. Furthermore, because the entire system functions in real time, it is possible to maintain the user's motivation in their daily lives and have their behavior reflected immediately.

[1117] The processing flow will be explained below.

[1118] Step 1:

[1119] Users wear a wearable device in their daily lives, which collects vital data such as heart rate, exercise volume, dietary intake, sleep data, and stress levels in real time. For example, when a user eats breakfast, the wearable device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[1120] Step 2:

[1121] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. Once the device is connected, data is automatically synchronized. For example, heart rate and exercise data are sent to the device in real time.

[1122] Step 3:

[1123] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed.

[1124] Step 4:

[1125] The server integrates and centrally manages the received vital data, for example, heart rate data, exercise data, dietary data, sleep data, and stress data, and manages them as a single data set.

[1126] Step 5:

[1127] The server-based generative artificial intelligence analyzes the integrated vital data. For example, it analyzes data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume.

[1128] Step 6:

[1129] Based on the analysis results, the AI ​​generates personalized lifestyle improvement suggestions suited to each individual user. For example, if it determines that the user is not getting enough exercise, it will generate specific instructions such as "recommended 30 minutes of walking on the weekend." It also generates advice on diet and suggestions for improving sleep.

[1130] Step 7:

[1131] The device uses an emotion engine to recognize the user's emotions and collects emotion data from the user's facial expressions, tone of voice, and body movements. For example, if the user is feeling stressed, the emotion engine will detect this.

[1132] Step 8:

[1133] The emotional data collected by the device is sent to a server, where it is centrally managed and analyzed in combination with vital data. For example, it can analyze the time periods and situations in which the user feels stressed.

[1134] Step 9:

[1135] The generative AI will then analyze the emotional and vital data to generate more specific lifestyle improvement recommendations, such as "Perform relaxation exercises every night to reduce stress."

[1136] Step 10:

[1137] The server then sends the lifestyle improvement suggestions it has generated to the device, which then presents them to the user and displays feedback in a visually easy-to-understand format. For example, real-time feedback such as "Your stress level seems high. Try some relaxation exercises" is provided.

[1138] Step 11:

[1139] The user performs the recommended action based on the feedback, such as walking or exercising, and then the data is collected again by the wearable device.

[1140] Step 12:

[1141] The device again transmits the newly collected vital data and emotional data to the server, which receives it and analyzes it again using the artificial intelligence.

[1142] Step 13:

[1143] The generative AI reassess the new vital and emotional data to determine whether improvements or new guidance are needed. For example, it evaluates the patient's condition after a walk and provides feedback such as, "Your blood sugar level has improved. Continue to maintain good lifestyle habits."

[1144] Example 2

[1145] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1146] Conventional health management systems can only provide static advice based on a user's vital signs, and lack a dynamic approach that takes into account the user's emotional state. Furthermore, due to insufficient real-time feedback, it is difficult to provide timely improvement suggestions that are tailored to the user's daily life.

[1147] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for integrating and analyzing vital data, means for a generating artificial intelligence to generate personalized lifestyle improvement suggestions, means for an emotion engine to collect and analyze emotion data, and means for combining the emotion data with vital data to generate additional lifestyle improvement suggestions. This makes it possible to analyze the user's vital data and emotion data in an integrated manner, and to provide more personalized and appropriate lifestyle improvement suggestions in real time that are tailored to the user's health condition and emotions.

[1148] A "wearable device" is a compact electronic device that can be worn by the user and collects vital data such as heart rate, exercise volume, dietary content, sleep data, and stress level in real time.

[1149] "Vital data" refers to basic physiological data necessary to understand a user's health condition, and specifically refers to data such as heart rate, amount of exercise, diet, sleep data, and stress level.

[1150] A "terminal" is an electronic device that receives collected vital data from a user's wearable device, synchronizes the data, and transmits the data to a server, and includes smartphones, tablets, etc.

[1151] The "server" is a computer system that integrates and analyzes vital data and emotional data sent from terminals via the Internet.

[1152] "Generative AI" refers to an AI program that analyzes collected vital data and generates personalized lifestyle improvement suggestions.

[1153] An "emotion engine" refers to software or hardware that analyzes a user's emotional state from facial expressions, tone of voice, physical movements, etc., and collects this as emotional data.

[1154] "Personalized lifestyle changes" refers to specific suggestions for diet, exercise, sleep, and stress management that are generated based on a user's individual vital and emotional data.

[1155] "Emotion data" refers to data that indicates the user's emotional state, and is obtained by analyzing facial expressions, tone of voice, body movements, and the like using an emotion engine.

[1156] The present invention provides lifestyle improvement suggestions based on individual vital data and emotional data using a system including a wearable terminal, a terminal, a server, generative artificial intelligence, and an emotion engine.

[1157] Users wear a wearable device in their daily lives. The device collects vital data such as heart rate, exercise volume, dietary intake, sleep data, and stress levels in real time. For example, when a user eats breakfast, the wearable device records the time and content of the meal. It also continuously collects data while exercising or sleeping. Specific hardware used includes the Apple Watch and Fitbit.

[1158] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. When the device is connected, data is automatically synchronized. For example, heart rate and exercise data are sent to the device in real time. This device includes iPhones and Android smartphones.

[1159] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed. Specific transmission protocols used are HTTP / HTTPS, Bluetooth, and Wi-Fi.

[1160] The server consolidates the received vital data and manages it centrally. The server is equipped with generative artificial intelligence that analyzes the consolidated data. For example, it analyzes the user's data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume. The specific server environment used is Amazon Web Services (AWS) or Google Cloud.

[1161] Based on the analysis results, the generative AI generates personalized lifestyle improvement recommendations for each user. These include specific instructions regarding diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods at breakfast from now on" and exercise advice such as "Do 30 minutes of aerobic exercise every night" are generated. The generative AI model uses a Python-based model, and an example of a prompt for this model is, "Analyze one week's heart rate data and exercise records to create a graph showing health trends. Please also include suggestions for relaxation exercises if stress levels are high."

[1162] Furthermore, the emotion engine recognizes the user's emotions. The emotion engine analyzes data such as the user's facial expressions, tone of voice, and physical movements to understand their emotional state at that time. For example, while the user is operating the smartphone, the camera captures their face and analyzes their voice to determine emotions such as stress or joy. The emotion engine includes facial expression analysis using OpenCV and TensorFlow.

[1163] The emotion data recognized by the emotion engine is also sent to the server, and the artificial intelligence combines it with vital data to generate further lifestyle improvement suggestions. For example, if stress levels are high, it will generate suggestions for relaxation exercises or advice on reconsidering the timing of work breaks.

[1164] The generated lifestyle improvement suggestions and emotional feedback are sent from the server to the user's device, where they are presented to the user. The device displays the feedback in a visually easy-to-understand format, suggesting specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as, "Your stress level seems high. Try doing some relaxation exercises."

[1165] After the user takes the recommended action based on the feedback, the wearable device again collects new vital data, which is again sent to the server via the device. The emotion engine also periodically collects emotional data and similarly sends it to the server. The generative AI reevaluates this data to determine the effectiveness of improvements and provides further feedback as needed. This provides ongoing support for the user's health management.

[1166] The system of the present invention effectively utilizes individual vital data and emotional data to provide lifestyle improvement suggestions tailored to the user, thereby contributing to the prevention of lifestyle-related diseases such as diabetes and their progression to more serious conditions. Furthermore, because the entire system functions in real time, it is possible to maintain the user's motivation in their daily lives and have their behavior reflected immediately.

[1167] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1168] Step 1:

[1169] Users wear a wearable device in their daily lives, which collects vital data such as heart rate, exercise volume, dietary habits, sleep data, and stress levels in real time.

[1170] Input: User's daily activities and physiological status

[1171] Specific operation: Specifically, when the user eats breakfast, the time and contents of the meal are recorded. Data is also collected continuously during exercise and while sleeping.

[1172] Output: Collected vital data

[1173] Step 2:

[1174] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. Once the device is connected, data is automatically synchronized.

[1175] Input: Vital data collected by a wearable device

[1176] Specific operation: Heart rate and exercise data are sent to your smartphone in real time.

[1177] Output: Vital data stored on the user's device

[1178] Step 3:

[1179] The device periodically transmits vital data to the server at set intervals, such as at the end of each day or after a specific event, and the success status of the data transmission is confirmed.

[1180] Input: Vital data stored on the device

[1181] Specific operation: Heart rate and exercise data are uploaded to the server at midnight.

[1182] Output: Vital data stored on the server

[1183] Step 4:

[1184] The server integrates and centrally manages the received vital data. The server is equipped with a generative artificial intelligence that analyzes the integrated data.

[1185] Input: Vital data stored on the server

[1186] How it works: The AI ​​model analyzes heart rate data from the past week to detect outliers and health trends, and analyzes diet and exercise trends to assess fluctuations in health.

[1187] Output: Analysis results (detection of outliers, health trends, etc.)

[1188] Step 5:

[1189] Based on the analysis, the generative AI model generates personalized lifestyle recommendations for each user, including specific instructions for diet, exercise, sleep, and stress management.

[1190] Input: Analysis results

[1191] Specific actions: Guidance such as "Increase the amount of high-protein foods at breakfast" or "Do 30 minutes of aerobic exercise every night" is generated.

[1192] Output: Personalized lifestyle changes

[1193] Step 6:

[1194] To recognize the user's emotions, the emotion engine analyzes the user's facial expressions, tone of voice, body movements, etc. This data is collected to understand the user's emotional state.

[1195] Input: User's facial expressions, tone of voice, and physical movements

[1196] Specific actions: Captures faces, analyzes tone of voice, and determines emotions such as stress or joy.

[1197] Output: Emotion data

[1198] Step 7:

[1199] Emotional data recognized by the emotion engine is also sent to the server, and the generative AI model combines this with vital data to generate further lifestyle improvement suggestions.

[1200] Input: Emotion data, vital data

[1201] Specific actions: If stress levels are high, suggestions for relaxation exercises and advice on reconsidering work break timing will be generated.

[1202] Output: Additional lifestyle changes

[1203] Step 8:

[1204] The server sends the generated lifestyle improvement suggestions and emotion-based feedback to the user's device, which then presents them to the user. Real-time feedback is provided using a notification function.

[1205] Input: Additional lifestyle changes

[1206] Specific behavior: The device uses the notification function to notify you, "Your stress level seems high. Try some relaxation exercises."

[1207] Output: Presented feedback to the user

[1208] Step 9:

[1209] After the user takes action based on the feedback, the wearable device again collects new vital data, which is then sent to the server via the device. The emotion engine also periodically collects emotional data and sends it to the server in the same way.

[1210] Input: Vital data and emotional data after user actions

[1211] What happens: Heart rate data is collected after a relaxation exercise.

[1212] Output: New vital and emotional data collected

[1213] Step 10:

[1214] A generative AI model re-evaluates this data, determines the effectiveness of improvements, and provides further feedback as needed, supporting the user in managing their health on an ongoing basis.

[1215] Input: New vital and emotional data

[1216] Specific actions: Evaluate whether relaxation exercises have improved stress levels and provide new suggestions.

[1217] Output: Reevaluated results and further feedback

[1218] (Application example 2)

[1219] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1220] Health management is becoming increasingly important in modern society, but it is difficult to receive personalized advice in real time that takes into account individual lifestyle habits and health conditions. Furthermore, physical stores often lack the information necessary to provide optimal services to each individual customer. Therefore, there is a need for a system that provides personalized services to customers and supports health management based on vital signs and emotional data.

[1221] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting daily vital data from the wearable device, means for transmitting the vital data to the device, means for the device to transmit the vital data to the server, means for the server to integrate and analyze the vital data, means for a generative artificial intelligence to generate personalized lifestyle improvement suggestions based on the integrated and analyzed vital data, means for transmitting the generated lifestyle improvement suggestions to the device and presenting them to the user, and a brick-and-mortar store application that provides customized services based on the vital data and emotion data when a customer visits a brick-and-mortar store while wearing a wearable device. This makes it possible to provide lifestyle improvement suggestions tailored to individual users in real time, and to provide personalized services even in brick-and-mortar stores.

[1222] A "wearable device" is a device that can be worn by a user and collects and transmits vital data such as heart rate, amount of exercise, dietary content, sleep data, and stress level in real time.

[1223] "Vital data" refers to biological information such as heart rate, blood sugar level, amount of exercise, sleep data, and stress level that indicates the user's health condition.

[1224] A "terminal" is a device (such as a smartphone or tablet) that has the function of receiving collected vital data and sending it to a server.

[1225] The "server" is a computer that integrates and analyzes vital data sent from the device and generates personalized lifestyle improvement suggestions using generative artificial intelligence.

[1226] "Generative AI" is an algorithm that automatically generates optimal lifestyle improvement suggestions for users based on integrated and analyzed vital data.

[1227] "Lifestyle changes" are advice that includes specific instructions and recommendations regarding diet, exercise, sleep, and stress management.

[1228] "Emotion data" is information indicating the user's emotional state obtained from facial expressions, tone of voice, body movements, and the like.

[1229] The "physical store application" is software that provides customized services based on vital and emotional data when customers visit a physical store while wearing a wearable device.

[1230] The present invention provides a specific means for providing personalized services to customers using a system including a wearable terminal, a terminal, a server, a generative artificial intelligence, and an emotion engine. The following describes specific embodiments of the present invention.

[1231] Users wear a wearable device in their daily lives. The device collects various vital data in real time, such as heart rate, exercise volume, dietary intake, sleep data, and stress levels. For example, when a user eats breakfast, the device records the time and content of the meal. It also continuously collects data while exercising or sleeping.

[1232] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. When the device is connected, data is automatically synchronized. For example, heart rate and exercise volume data are sent to the device in real time.

[1233] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed.

[1234] The server integrates and centrally manages the received vital data. The server is equipped with generative artificial intelligence, which analyzes the integrated data. For example, it analyzes the user's data from the past week to detect abnormal values ​​and health trends. It analyzes patterns such as trends in heart rate and blood sugar levels, and fluctuations in exercise volume.

[1235] Based on the analysis results, the AI ​​generates personalized lifestyle improvement recommendations for each user, including specific instructions for diet, exercise, sleep, and stress management. For example, dietary advice such as "Increase the amount of high-protein foods you eat at breakfast from now on" and exercise advice such as "Do 30 minutes of aerobic exercise every night" are generated.

[1236] Furthermore, the emotion engine recognizes the user's emotions. The emotion engine analyzes data such as the user's facial expressions, tone of voice, and physical movements to grasp the user's emotional state at that time. For example, while the user is operating the smartphone, the camera captures the face and analyzes the voice to determine emotions such as stress or joy.

[1237] The emotion data recognized by the emotion engine is also sent to the server, and the artificial intelligence combines it with vital data to generate further lifestyle improvement suggestions. For example, if stress levels are high, it will generate suggestions for relaxation exercises or advice on reconsidering the timing of work breaks.

[1238] In addition, an important component of the present invention is a store application that provides customized services based on vital data and emotional data when a customer wearing a wearable device visits a store. For example, if a user is determined to be in a high-stress state, the application can guide the user to a relaxing area in the store or provide products that will reduce stress.

[1239] The generated lifestyle improvement suggestions and emotional feedback are sent from the server to the user's device, where they are presented to the user. The device displays the feedback in a visually easy-to-understand format, suggesting specific actions the user should take next. For example, a notification function can be used to provide real-time feedback such as, "Your stress level seems high. Try doing some relaxation exercises."

[1240] Below is an example prompt that includes guidelines for providing customized services based on wearable device data when customers visit a store.

[1241] Example prompt sentence:

[1242] "Please suggest personalized in-store services based on the vital and emotional data of user ID: user12345."

[1243] The above is a specific description based on an embodiment of the present invention. This system configuration allows for real-time provision of lifestyle improvement suggestions tailored to individual users, and also makes it possible to provide personalized services in brick-and-mortar stores.

[1244] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1245] Step 1:

[1246] Users wear a wearable device and collect vital data during their daily lives. Specifically, the wearable device records heart rate, exercise, diet, sleep, stress level, etc. in real time. The input is the user's daily data, and the output is the collected vital data.

[1247] Step 2:

[1248] The vital data collected by the wearable device is sent to the user's device (smartphone or tablet) via Bluetooth or Wi-Fi. When the device is connected, data synchronization is performed automatically. The input is the collected vital data, and the output is the synchronized data sent to the device.

[1249] Step 3:

[1250] The device periodically sends vital data to the server at set intervals. For example, data is automatically uploaded at the end of each day or after a specific event. At this time, the success status of the data transmission is confirmed. The input is the vital data on the device, and the output is the data sent to the server.

[1251] Step 4:

[1252] The server integrates the received vital data and manages it centrally. The server is equipped with generative artificial intelligence that analyzes the integrated data. The input is the vital data sent to the server, and the output is the integrated and analyzed data.

[1253] Step 5:

[1254] The server's artificial intelligence generates personalized lifestyle improvement recommendations for each user based on the analyzed data. For example, it analyzes the user's data from the past week, detects abnormal values ​​and health trends, and generates specific advice. The input is the integrated and analyzed data, and the output is the generated improvement recommendations.

[1255] Step 6:

[1256] The emotion engine analyzes data such as facial expressions, tone of voice, and body movements to recognize the user's emotions. For example, while the user is operating a smartphone, a camera captures the face and analyzes the voice to determine the emotion. The input is the user's emotion-related data, and the output is the analyzed emotion data.

[1257] Step 7:

[1258] The server receives the emotional data from the emotion engine and combines it with vital data to generate further lifestyle improvement recommendations. For example, if stress levels are high, it will suggest relaxation exercises. The input is emotional data and vital data, and the output is further personalized improvement recommendations.

[1259] Step 8:

[1260] When a user visits a physical store while wearing a wearable device, the system provides customized services based on their vital and emotional data. Specifically, this includes guiding them to relaxation areas and recommending appropriate products based on the user's stress level. The input is the user's latest vital and emotional data, and the output is the provision of personalized services.

[1261] Step 9:

[1262] The generated lifestyle improvement suggestions and emotional feedback are sent from the server to the user's device and presented in a visually easy-to-understand format. Specifically, real-time feedback is provided using a notification function. The input is the generated improvement suggestions, and the output is the feedback displayed on the user's device.

[1263] The above is the processing flow of the system that provides personalized services using vital data and emotional data.

[1264] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1265] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1266] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1267] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1268] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1269] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1270] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1271] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1272] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1273] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1274] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1275] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1276] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1277] 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.

[1278] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1279] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1280] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1281] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1282] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1283] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1284] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1285] The following is further disclosed regarding the above embodiment.

[1286] (Claim 1)

[1287] A means of collecting daily vital data from a wearable device;

[1288] means for transmitting the vital data to a terminal;

[1289] means for transmitting the vital data to a server by the terminal;

[1290] A means for the server to integrate and analyze the vital data;

[1291] A means for generating personalized lifestyle improvement proposals based on the integrated and analyzed vital data by a generating artificial intelligence;

[1292] means for transmitting the generated lifestyle improvement plan to the terminal and presenting it to the user;

[1293] A system including:

[1294] (Claim 2)

[1295] 10. The system of claim 1, wherein the lifestyle modification suggestions include specific instructions regarding diet, exercise, sleep, and stress management.

[1296] (Claim 3)

[1297] 10. The system of claim 1, wherein the wearable device collects blood glucose levels, heart rate, activity, sleep data, and stress levels.

[1298] "Example 1"

[1299] (Claim 1)

[1300] A means of collecting daily vital data from a wearable device;

[1301] means for transmitting the vital data to a terminal;

[1302] means for transmitting the vital data to a server by the terminal;

[1303] means for the server to integrate and analyze the vital data and detect patterns and abnormal values;

[1304] A means for generating personalized lifestyle improvement proposals based on the integrated and analyzed vital data by a generating artificial intelligence;

[1305] means for transmitting the generated lifestyle improvement plan to the terminal and presenting it to the user;

[1306] A system including:

[1307] (Claim 2)

[1308] 10. The system of claim 1, wherein the lifestyle modification suggestions include specific instructions regarding diet, exercise, sleep, and stress management.

[1309] (Claim 3)

[1310] 10. The system of claim 1, wherein the wearable device collects blood glucose levels, heart rate, activity, sleep data, and stress levels.

[1311] (Claim 4)

[1312] The system of claim 1, wherein the generated lifestyle improvement suggestions are presented to the user in real time using a notification function.

[1313] (Claim 5)

[1314] 10. The system of claim 1, wherein the server includes means for re-evaluating the user's behavioral data and providing further feedback as needed.

[1315] "Application Example 1"

[1316] (Claim 1)

[1317] A means of collecting daily vital data from a wearable device;

[1318] means for transmitting the vital data to a terminal;

[1319] means for transmitting the vital data to a server by the terminal;

[1320] A means for the server to integrate and analyze the vital data;

[1321] A means for generating personalized lifestyle improvement proposals based on the integrated and analyzed vital data by a generating artificial intelligence;

[1322] means for transmitting the generated lifestyle improvement plan to the terminal and presenting it to the user;

[1323] a means for collecting operation data of the equipment from sensors attached to the equipment in the factory and analyzing the operation data;

[1324] A means for generating specific improvement plans to improve the operating efficiency of factory equipment based on the analyzed operation data by the generating artificial intelligence;

[1325] a means for transmitting the generated improvement plan to a terminal of a factory manager and presenting the plan;

[1326] A system including:

[1327] (Claim 2)

[1328] The system of claim 1 , wherein the lifestyle improvement suggestions and the improvement suggestions for improving the operational efficiency of factory equipment include specific instructions.

[1329] (Claim 3)

[1330] 10. The system of claim 1, wherein the wearable device or sensor collects blood glucose levels, heart rate, activity, sleep data, stress levels, temperature, vibration, movement frequency, and power consumption.

[1331] "Example 2: Combining Emotion Engines"

[1332] (Claim 1)

[1333] A means of collecting daily vital data from a wearable device;

[1334] means for transmitting the vital data to a terminal;

[1335] means for transmitting the vital data to a server by the terminal;

[1336] A means for the server to integrate and analyze the vital data;

[1337] A means for generating personalized lifestyle improvement proposals based on the integrated and analyzed vital data by a generating artificial intelligence;

[1338] means for transmitting the generated lifestyle improvement plan to the terminal and presenting it to the user;

[1339] a means for an emotion engine to collect emotion data of a user and transmit the emotion data to a server;

[1340] a means for analyzing the emotion data in combination with vital data to generate additional lifestyle improvement suggestions;

[1341] A system including:

[1342] (Claim 2)

[1343] 10. The system of claim 1, wherein the lifestyle modification suggestions include specific instructions regarding diet, exercise, sleep, and stress management.

[1344] (Claim 3)

[1345] 10. The system of claim 1, wherein the wearable device collects heart rate, activity, diet, sleep data, and stress levels.

[1346] "Application example 2 when combining emotion engines"

[1347] (Claim 1)

[1348] A means of collecting daily vital data from a wearable device;

[1349] means for transmitting the vital data to a terminal;

[1350] means for transmitting the vital data to a server by the terminal;

[1351] A means for the server to integrate and analyze the vital data;

[1352] A means for generating personalized lifestyle improvement proposals based on the integrated and analyzed vital data by a generating artificial intelligence;

[1353] means for transmitting the generated lifestyle improvement plan to the terminal and presenting it to the user;

[1354] A physical store application that provides customized services based on vital data and emotional data when customers visit a physical store while wearing a wearable device.

[1355] A system including:

[1356] (Claim 2)

[1357] 10. The system of claim 1, wherein the lifestyle modification suggestions include specific instructions regarding diet, exercise, sleep, and stress management.

[1358] (Claim 3)

[1359] 10. The system of claim 1, wherein the wearable device collects blood glucose levels, heart rate, activity, sleep data, and stress levels. [Explanation of symbols]

[1360] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of collecting daily vital data from a wearable device; means for transmitting the vital data to a terminal; means for transmitting the vital data to a server by the terminal; A means for the server to integrate and analyze the vital data; A means for generating personalized lifestyle improvement proposals based on the integrated and analyzed vital data by a generating artificial intelligence; means for transmitting the generated lifestyle improvement plan to the terminal and presenting it to the user; A system including:

2. The system of claim 1 , wherein the lifestyle modification suggestions include specific instructions regarding diet, exercise, sleep, and stress management.

3. The system of claim 1 , wherein the wearable device collects blood glucose levels, heart rate, activity, sleep data, and stress levels.

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