system

Abstract

We provide the system. [Solution] A data acquisition method for collecting individual athlete data, Analysis means for analyzing the aforementioned exerciser data and generating an optimized exercise plan for the exerciser, A feedback provision means that provides real-time feedback to the exerciser based on the aforementioned exercise plan, A means of dialogue with the aforementioned exerciser, providing advice and answers to questions during exercise, A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 There is a problem that athletes cannot obtain an appropriate exercise plan according to their individual needs, and it is difficult to receive real-time feedback during exercise and guidance on form improvement. As a result, efficient training cannot be achieved, and sometimes there is a risk of injury. Also, it is difficult to maintain motivation for exercise with general training methods. 【Means for Solving the Problems】 【0005】 To address this challenge, the present invention provides a system that includes artificial intelligence for collecting and analyzing exercise data using wearable devices and communication terminals. This system has the function of generating an optimized exercise plan for the exerciser and providing real-time feedback. Furthermore, it provides advice and answers to questions during exercise through dialogue with the exerciser, and supports motivation maintenance tailored to individual needs. In this way, users can train in a way that is most suitable for them and achieve their goals safely and effectively. 【0006】 "Data acquisition means" refers to devices and methods for acquiring relevant biometric and motion data from an exerciser. 【0007】 "Analysis means" refers to devices or methods for processing and analyzing acquired data to generate an exercise plan optimized for the individual. 【0008】 A "feedback provision method" refers to a device or method for providing information to the exerciser in real time based on the exercise plan and pointing out areas for improvement during the exercise. 【0009】 "Dialogue tools" refer to devices and methods for communicating with athletes and providing answers to questions and advice during exercise in natural language. 【0010】 An "artificial intelligence algorithm" is a computer program or method used to analyze data from athletes and provide useful feedback or predictions. [Brief explanation of the drawing] 【0011】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3]This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention] 【0012】 Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings. 【0013】 First, let's explain the terminology used in the following explanation. 【0014】 In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0015】 In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0016】 In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like. 【0017】 In the following embodiments, the numbered communication I / F (Interface) is an interface that includes a communication processor, an antenna, and the like. 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), or Bluetooth (registered trademark), and the like. 【0018】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0019】 [First Embodiment] 【0020】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0021】 As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. 【0022】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0023】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0024】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0025】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0026】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0027】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0028】 As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30. 【0029】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0030】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0031】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0032】 This invention provides an exercise support system tailored to the individual needs of exercisers, integrating data acquisition, analysis, feedback, and dialogue mechanisms. The system is designed to maximize the effectiveness of exercisers' training and enable safe and efficient exercise. 【0033】 Data acquisition 【0034】 Devices: Wearable devices worn by athletes and communication terminals used by athletes have the capability to acquire important biometric information in real time, such as heart rate, acceleration, and GPS location data. This information provides detailed data about the athlete's current performance status. 【0035】 Data Analysis 【0036】 Server: The collected data is analyzed by the server's AI algorithm. This analysis is performed to capture an overall picture of the exerciser's physical condition and performance, and to generate an optimal exercise plan tailored to individual goals and fitness levels. 【0037】 Provide feedback 【0038】 Device: Based on the generated exercise plan, the device provides real-time feedback to the exerciser. For example, the device gives specific instructions via voice or text messages such as "Slow down your running pace" or "Emphatize your arm swing." 【0039】 Dialogue 【0040】 Server: Responses to exercisers' questions are prepared using natural language processing technology. When a user has a question about exercise, the server provides appropriate advice and information. 【0041】 Specific example 【0042】 User: For example, suppose a user is training for a marathon. One day, this user feels more tired than usual when running a long distance, especially in hot weather. 【0043】 Terminal: A wearable device detects an abnormal increase in heart rate and immediately sends that data to a server. 【0044】 Server: The AI ​​dynamically adjusts the exercise plan and instructs the user in real time to slow down. 【0045】 User: By receiving this feedback and slowing down, the user can safely continue training. At this time, the server may also suggest, "It would be a good idea to take a 15-minute break from training in this weather." 【0046】 In this way, the present invention provides individualized support tailored to the exerciser's situation, resulting in a more effective and safer training experience. 【0047】 The following describes the processing flow. 【0048】 Step 1: 【0049】 The device confirms that the user is wearing a wearable device and a communication terminal, and then begins acquiring data. Specifically, it collects heart rate, location information, and acceleration data in real time. 【0050】 Step 2: 【0051】 The device sends the collected data to the server. The data is packaged at regular time intervals and sent via secure communication. 【0052】 Step 3: 【0053】 The server inputs the received data into an AI algorithm for real-time analysis. The AI ​​evaluates the exerciser's activity and identifies indicators for improving form and safety. 【0054】 Step 4: 【0055】 The server generates a customized exercise plan for the user based on the analysis results. This plan includes elements such as the type of exercise, pace, and duration. 【0056】 Step 5: 【0057】 The device provides real-time feedback to the user based on the generated exercise plan. This includes specific exercise instructions via voice guidance and on-screen displays. 【0058】 Step 6: 【0059】 The server uses natural language processing technology to quickly answer questions submitted by users. It determines what additional information the user needs and provides an appropriate response. 【0060】 Step 7: 【0061】 After the user completes the training, the device provides comprehensive feedback, including a performance summary, achievement level, and advice for the next session. 【0062】 In this way, a series of processes are performed to support the user's fitness experience. 【0063】 (Example 1) 【0064】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0065】 In modern times, it is crucial for athletes to engage in effective and safe exercise tailored to their individual needs, but selecting appropriate exercise plans and providing real-time feedback remains challenging. There is a need to address this issue and provide a support system that enables athletes to maximize their performance. 【0066】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0067】 In this invention, the server includes information acquisition means for collecting individual exercise information, analysis means for analyzing the exercise information to generate an optimized exercise plan for the exerciser, and generation means for providing feedback and advice to the user in natural language using a generated AI model. This enables the formulation of an optimal exercise plan tailored to the exerciser and the provision of rapid feedback. 【0068】 "Individual exerciser information" refers to biometric data such as heart rate, acceleration, and location information, as well as activity data, acquired for each exerciser. 【0069】 "Information acquisition means" refers to devices that have the function of collecting biometric data and activity data from athletes, and include wearable devices and communication devices. 【0070】 "Analysis means" refers to a system that includes an algorithm that uses acquired data to analyze the physical condition and performance of the exerciser and generates an optimized exercise plan. 【0071】 "Notification means" refers to a device or system that has the function of sending real-time feedback to the exerciser based on the generated exercise plan. 【0072】 A "response mechanism" refers to a system that has an interactive function to provide information in response to the user's questions or requests, and uses natural language processing technology. 【0073】 A "generative AI model" refers to a statistical or machine learning-based model that uses artificial intelligence to perform data analysis and natural language generation. 【0074】 This invention is a system for providing individualized support to athletes. It primarily utilizes wearable devices and communication equipment to acquire individual athlete information and transmit it to a server. These devices are constantly connected to the server via Bluetooth or Wi-Fi. 【0075】 The server uses generative AI models and machine learning algorithms to analyze data received from the exerciser. This data analysis includes biometric data such as heart rate, acceleration, and location information, which allows for a deeper understanding of the exerciser's fitness level and daily exercise habits. 【0076】 Based on the analysis results, the server generates an optimized exercise plan. This exercise plan is sent to the device as feedback using natural language generation technology. The device provides instructions to the exerciser using voice output and screen displays. Specifically, this includes friendly advice such as "Let's slow down your running pace" or "It's time to hydrate." 【0077】 Furthermore, users can send questions to the server through a dialogue mechanism. The server can utilize natural language processing technology to provide appropriate answers and advice to the user's questions. This system will be a crucial support for exercisers in achieving their fitness goals. 【0078】 For example, if a user detects an abnormally high heart rate during marathon training, the device will react in real time by immediately displaying a message such as "Please slow down." 【0079】 Examples of prompt statements include the following: 【0080】 "Please provide appropriate advice on what to do when an abnormal heart rate is detected." 【0081】 "Please generate exercise advice based on the current weather conditions." 【0082】 This invention utilizes a variety of technological means to provide users with a more effective and safer exercise experience. 【0083】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0084】 Step 1: 【0085】 The terminal acquires biometric data such as the exerciser's heart rate, acceleration, and location information in real time through a wearable device. The terminal formats this data into a predetermined format and prepares it for transmission to the server. The input is the exerciser's biometric information, and the output is data packets that can be transferred to the server. 【0086】 Step 2: 【0087】 The server receives data packets formatted by the terminal. The server stores this data in a database and performs the necessary preprocessing for subsequent data analysis. The input is the data packets received from the terminal, and the output is the data stored in a format suitable for analysis. 【0088】 Step 3: 【0089】 The server uses a generative AI model to analyze incoming data in detail. It compares it with the exerciser's past exercise data to detect trends and anomalies in their condition. The input is exercise data stored in a database, and the output is insights or alerts about the exerciser's current condition. 【0090】 Step 4: 【0091】 Based on the analysis results, the server uses natural language generation technology to create appropriate feedback messages for the exerciser. For example, it may include specific instructions such as, "Your heart rate is high, please slow down." The input is the insights obtained from the analysis, and the output is the exercise guidance message. 【0092】 Step 5: 【0093】 The terminal receives feedback messages sent from the server and notifies the exerciser of these messages. The terminal displays the messages on its screen or reads out voice instructions using speech synthesis technology. The input is feedback messages from the server, and the output is notifications or voice instructions to the exerciser. 【0094】 Step 6: 【0095】 The user enters questions or requests on a terminal during exercise. Questions are entered via voice or text and sent from the terminal to the server. The input is the user's question, and the output is the server's preparation for processing. 【0096】 Step 7: 【0097】 The server analyzes questions received from users and generates appropriate answers and advice using natural language processing techniques. The input is user question data, and the output is an answer formed in natural language. 【0098】 Step 8: 【0099】 The terminal receives responses from the server and notifies the participant. This is done using audio output or a display. The input is the response data from the server, and the output is the notification to the participant. 【0100】 (Application Example 1) 【0101】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0102】 In modern times, providing effective and safe training methods tailored to the individual needs of athletes is crucial, but it has been difficult to provide a system that dynamically adjusts feedback based on the athlete's condition and environmental factors. The present invention aims to provide a system that can provide athletes with real-time, environmentally responsive and effective feedback, thereby optimizing their exercise. 【0103】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0104】 In this invention, the server includes data acquisition means for collecting individual exercise data, analysis means for analyzing the exercise data and generating an optimized exercise plan for the exerciser, and feedback provision means for providing real-time feedback to the exerciser based on the exercise plan. This makes it possible to provide exercisers with dynamic exercise guidance that takes environmental conditions into account in real time, thereby supporting safe and effective training. 【0105】 "Data acquisition means" refers to a device or method for collecting individual biometric and environmental information of an exerciser. 【0106】 "Analysis means" refers to an algorithm or process for generating an optimized exercise plan based on acquired exercise data. 【0107】 A "feedback provision means" is a device or function that provides instructions and advice to the exerciser in real time based on the generated exercise plan. 【0108】 A "means of communication" refers to an interface or function for exchanging information with exercisers and providing advice and answers to questions during exercise. 【0109】 "Environmental analysis means" refers to a device or method for evaluating the environmental conditions surrounding an exerciser and generating appropriate advice. 【0110】 The system implementing this invention consists of a server and a terminal. The server collects data from wearable devices and communication terminals to acquire individual biometric and environmental information of the exerciser. As a result, data such as heart rate, acceleration, and GPS location are transmitted to the server in real time. 【0111】 The server analyzes this collected data using artificial intelligence algorithms. The analyzed data is used to generate an optimal exercise plan based on the exerciser's fitness level, goals, and environmental conditions. The server also uses environmental analysis tools to evaluate external conditions such as weather and time of day, and incorporates these into the exercise plan. 【0112】 The generated exercise plan is transferred to a device via a feedback system, and instructions are delivered to the exerciser in real time as voice or text messages. The device is a smartphone or smartwatch worn by the exerciser, allowing them to receive advice immediately and continue exercising safely and effectively. 【0113】 As a concrete example, consider a case where a user is training for a marathon on a hot day. In this case, the server detects an increase in heart rate data and adjusts the exercise plan, instructing the user to slow down. Furthermore, environmental analysis can be used to assess if the weather is unusually hot and suggest additional breaks to the user. 【0114】 An example of a prompt for a generative AI model is: "The robot assistant analyzes the exerciser's data in real time and provides exercise advice tailored to the weather. What kind of feedback should be provided when the user is running in the scorching sun?" 【0115】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0116】 Step 1: 【0117】 The server collects individual data from the exerciser. This process involves real-time acquisition of biometric information such as heart rate, acceleration, and GPS location from wearable devices and communication terminals. This data is transferred to the server and treated as initial data. 【0118】 Step 2: 【0119】 The server performs analysis based on the acquired data. It monitors the exerciser's heart rate and pace in real time and generates an optimized exercise plan using an artificial intelligence algorithm. This data processing takes into account the exerciser's current fitness level and goals to determine the next action. 【0120】 Step 3: 【0121】 The server acquires environmental information and incorporates it into the exercise plan. In this step, environmental conditions such as local temperature and humidity are collected based on geographical location information using weather APIs, etc. This makes the exercise plan more personalized. 【0122】 Step 4: 【0123】 The device receives an optimized exercise plan from the server and feedback based on environmental information. It provides real-time advice to the exerciser as voice instructions and text messages. Specifically, it suggests concrete actions such as "slow down" or "take a break for a certain period of time." 【0124】 Step 5: 【0125】 The user acts on the feedback received from the device. Following the instructions provided by the device during exercise improves safety and performance. At this stage, the interaction between the server and the device is complete, and real-time support continues until the exercise session ends. 【0126】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0127】 This invention is an exercise support system that combines an emotion engine that recognizes the user's emotions, thereby providing comprehensive support tailored to each individual exerciser. The following describes a typical embodiment for carrying out this invention. 【0128】 Data acquisition 【0129】 Terminal: To understand the user's condition during exercise, wearable devices and communication terminals collect biometric and environmental data. This includes heart rate, exercise data, and audio / video data from the terminal's camera and microphone. 【0130】 emotion recognition 【0131】 Server: Using audio and video data transmitted from the terminal, the emotion engine recognizes emotions from the user's facial expressions and tone of voice. This analysis identifies the user's emotional state. 【0132】 Data analysis and adjustment of exercise plan 【0133】 Server: The server analyzes collected exercise and emotional data using AI algorithms to generate or adjust an exercise plan optimized for the user. If emotional data detects, for example, fatigue or stress, the exercise intensity is adjusted accordingly. 【0134】 Real-time feedback 【0135】 Device: The device provides feedback to the user according to the exercise plan, including messages tailored to the user's emotional state. For example, if the user is feeling stressed, it might advise, "Relax and take slow, deep breaths." 【0136】 Dialogue 【0137】 Server: Provides appropriate answers to questions from participants using natural language processing techniques. This includes responses that take into account the user's current emotional state. 【0138】 Specific example 【0139】 User: A user is training using a fitness app. This user is trying a new exercise plan and feels a little anxious shortly after starting. 【0140】 The device's camera and microphone detect the anxiety and send it to the server. 【0141】 Server: The emotion engine detects anxiety and adjusts the difficulty level of the exercise plan. Based on this, the device provides voice advice such as, "Start slowly, and increase the pace as you get used to it." 【0142】 User: This feedback gives me the confidence to continue exercising. 【0143】 This invention aims to provide an optimal exercise experience by taking into account not only the user's physical characteristics but also their emotional characteristics. 【0144】 The following describes the processing flow. 【0145】 Step 1: 【0146】 The device activates the wearable device and communication terminal when the user prepares to start exercising, and simultaneously collects biometric data (heart rate, movement data, etc.) and audio / video data. 【0147】 Step 2: 【0148】 The device transmits collected biometric data and audio / video data to the server. This data is transferred in real time via a secure connection. 【0149】 Step 3: 【0150】 The server inputs audio and video data into the emotion engine to analyze the user's emotional state. The engine detects the user's emotions from their facial expressions and tone of voice, identifying states such as anxiety, stress, and concentration. 【0151】 Step 4: 【0152】 The server uses biometric data and emotional state to evaluate the user's exercise performance with an AI algorithm. Based on this evaluation, it makes appropriate adjustments to the exercise plan. For example, if emotional data indicates the user is fatigued, the plan is adjusted to reduce the exercise load. 【0153】 Step 5: 【0154】 The device provides feedback to the user based on the adjusted exercise plan. This feedback is delivered verbally, for example, "You don't seem to be feeling well. How about slowing down a bit?" 【0155】 Step 6: 【0156】 The server generates natural responses to user questions and requests, taking into account their emotional state, and delivers them through the terminal. For example, the response might suggest, "Taking a short break might help you relax." 【0157】 Step 7: 【0158】 When a user finishes their workout, the device sends all the process data to a server, and the server displays comprehensive feedback to the user. This feedback includes a summary of the workout and areas for improvement. 【0159】 (Example 2) 【0160】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0161】 Conventional exercise support systems provide exercise plans based solely on the exerciser's physical data, failing to consider emotional states and thus unable to provide optimal support for individual users. Furthermore, the low accuracy of feedback and dialogue leaves challenges in maintaining user motivation and improving the effectiveness of exercise. 【0162】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0163】 In this invention, the server includes data acquisition means for understanding the user's state by collecting individual exerciser's heart rate, activity level, and environmental information; emotion recognition means for identifying emotions from acquired audio and video; and analysis means for generating or adjusting an optimized exercise plan by analyzing exerciser data and emotion data. This enables optimal exercise support that takes into account the user's emotional state. 【0164】 "Data acquisition means" refers to a device or process for collecting information on the exerciser's heart rate, activity level, and environmental information in order to understand the user's condition. 【0165】 "Emotion recognition means" refers to a system or method for identifying a user's emotions based on acquired audio and video data. 【0166】 "Analysis means" refers to a device or process that has the function of analyzing exercise data and emotional data to generate or adjust an optimized exercise plan. 【0167】 A "feedback provision method" is a system for providing real-time feedback to users based on their exercise plan. 【0168】 A "dialogue method" is a system that engages in dialogue with the participant and provides advice and answers to questions using natural language processing technology. 【0169】 A "wearable device" is a device that a user can wear to collect physical and environmental information. 【0170】 A "communication device" is a device or group of devices used to collect data and transmit it to a server. 【0171】 An "artificial intelligence algorithm" is a computational method used to analyze and process data and make decisions based on a specific purpose. 【0172】 A "generated AI model" is a model that uses patterns learned from data to perform analysis and predictions based on new data. 【0173】 This system aims to continuously and dynamically collect individual information about athletes and, based on that information, provide them with optimal feedback in real time. A specific embodiment of the invention is configured as follows: 【0174】 Hardware and data acquisition 【0175】 The devices utilize wearable devices such as smartwatches and fitness trackers to acquire biometric information such as the exerciser's heart rate and activity level in real time. They also collect audio and video data via communication devices such as smartphones and tablets to understand the environment. These devices transmit data to the server using Bluetooth or Wi-Fi. 【0176】 Emotion recognition and data analysis 【0177】 The server performs emotion recognition based on the received audio and video data. The emotion engine used here incorporates machine learning algorithms that can identify emotions from the user's facial expressions and tone of voice. The server further analyzes all of the exerciser's data and uses the generated AI model to optimize and adjust the system according to the exerciser. 【0178】 Feedback and dialogue 【0179】 The device provides real-time feedback to the user. It notifies the user of exercise guidance and advice via voice or text, taking into account the user's emotional state. The server also utilizes natural language processing technology to provide appropriate answers to questions from the exerciser. 【0180】 Specific example 【0181】 If a user is experiencing anxiety while trying a new exercise program, the smartphone's camera and microphone detect this anxiety. The data is sent to a server where an emotion recognition engine analyzes the anxiety and adjusts the exercise plan. As a result, the device provides a message such as, "Start slowly, and increase the pace as you get used to it." 【0182】 Example of a prompt 【0183】 "Analyze the user's biometric and emotional data collected in real time and suggest how to adjust the exercise intensity." 【0184】 In this way, the present invention provides an optimal exercise experience that comprehensively considers the physical and emotional elements of the exerciser. 【0185】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0186】 Step 1: 【0187】 The terminal acquires biometric information such as the exerciser's heart rate and activity level in real time from a wearable device. It also collects the user's voice and video data using a communication device. This data, obtained as input, is immediately transmitted to the server. The output provides information on the exerciser's physical condition and environment. This data collection process forms the basis for understanding the user's daily fluctuations. 【0188】 Step 2: 【0189】 The server inputs audio and video data sent from the terminal into an emotion recognition engine. This allows the engine to identify the user's emotions from their facial expressions and tone of voice, and output a specific emotional state. This data processing enables analysis of the user's current psychological state. 【0190】 Step 3: 【0191】 The server inputs exercise and emotional data into an AI algorithm for analysis. It then generates or adjusts an exercise plan optimized for the user. As a result of this process, a new exercise plan is obtained as output. Specifically, the data calculation involves pattern recognition of past data to dynamically determine the most effective exercise intensity and content. 【0192】 Step 4: 【0193】 The device provides real-time feedback tailored to the user based on the generated exercise plan. This feedback includes advice that aligns with the user's emotional state. For example, a message such as "Let's slow down a bit today" might be presented via voice or text. Based on the exercise plan received as input, specific exercise instructions are output. 【0194】 Step 5: 【0195】 The server inputs questions from users into natural language processing technology and generates appropriate responses. These responses are output considering information retrieved from the database and the user's emotional state. Specifically, it analyzes the intent of the user's question and extracts and provides the best possible answer. In this way, a system that can respond to user inquiries immediately is realized. 【0196】 (Application Example 2) 【0197】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal". 【0198】 This invention aims to improve the exercise experience by considering not only the physical health but also the emotional health of the exerciser and providing an optimized exercise plan tailored to each individual exerciser. Furthermore, it aims to automate exercise adjustment based on emotion recognition, which was lacking in conventional exercise support systems, and to improve the accuracy of the feedback provided as a result. 【0199】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0200】 In this invention, the server includes data acquisition means for collecting individual exercise data, emotion recognition means for recognizing the emotional state of the exerciser, and analysis means for generating an optimized exercise plan for the exerciser. This enables real-time exercise adjustment and feedback provision based on the emotional state of the exerciser. 【0201】 "Individual exerciser data" refers to information that includes unique physical and physiological parameters for each exerciser, and is used to optimize exercise. 【0202】 "Emotion recognition means" refers to a component of a system that has the function of identifying an emotion based on the facial expression, tone of voice, and other cues of the person performing the action. 【0203】 An "analysis device" is a device that processes collected data and executes an algorithm to generate an optimized exercise plan for the exerciser. 【0204】 "Exercise plan adjustment means" refers to a device or program for appropriately modifying an existing exercise plan according to the emotional state of the person exercising. 【0205】 A "feedback provisioning device" is a device that has the function of transmitting advice and information to the exerciser in real time based on the generated exercise plan. 【0206】 A "means of dialogue" is an interface that provides advice and answers questions through communication with activists. 【0207】 A "portable device" is a device that can be worn on the body or carried around and collects exercise data or biometric data. 【0208】 A "machine learning algorithm" is a form of artificial intelligence technology used to analyze collected data and identify areas for improvement in a person's movements. 【0209】 The system for carrying out the present invention includes a series of components for monitoring and analyzing the user's physical and emotional state in real time and providing optimal exercise support. 【0210】 At the heart of the system is a server, which is responsible for receiving and analyzing vast amounts of data. Wearable devices and communication terminals collect heart rate and movement data while the user is wearing them. This data is supplemented by emotion recognition mechanisms, which identify the user's emotions from their facial expressions and voice. 【0211】 The server uses analysis tools based on this data to generate a user's exercise plan. A machine learning algorithm takes into account the user's movements and emotional state to construct the optimal exercise pattern in real time. Furthermore, an exercise plan adjustment tool dynamically modifies the plan based on the emotional state. 【0212】 While the user is exercising, feedback and interaction tools provide immediate advice based on a tailored exercise plan. For example, if the user feels stressed, the device sends a message encouraging relaxation. 【0213】 For example, when a user tries a new exercise program, if the emotion recognition function detects anxiety, the server adjusts the exercise intensity and provides feedback such as, "Start slowly, and increase the pace once you get used to it." 【0214】 Using a generative AI model, you can use prompts like the following: 【0215】 "What are some ideas for the support and feedback the system should provide when a user starts a new exercise routine for the first time? Please consider situations where the user might be feeling anxious." 【0216】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0217】 Step 1: 【0218】 The device collects heart rate and motion data from wearable devices, and audio and video data from communication devices. This data includes the user's exercise and emotional state. The device transmits the collected biometric data to a server. 【0219】 Step 2: 【0220】 The server receives data sent from the terminal and analyzes the user's emotional state using emotion recognition technology. The input audio and video data is processed by an analysis engine, identifying emotions from the user's facial expressions and tone of voice. The output is information about the user's emotional state. 【0221】 Step 3: 【0222】 The server uses analysis tools to generate an optimized exercise plan based on exercise and emotional data. The collected exercise data is processed using machine learning algorithms to generate exercise patterns suitable for the user. The output is the optimized exercise plan. 【0223】 Step 4: 【0224】 The server modifies the exercise plan based on the user's emotional state using an exercise plan adjustment mechanism. It detects the user's stress and fatigue levels from emotional data and adjusts the exercise intensity and content accordingly. The output is the adjusted exercise plan. 【0225】 Step 5: 【0226】 The device utilizes feedback mechanisms to provide the user with real-time feedback based on a customized exercise plan. For example, the device might send a voice message such as, "Relax and take slow, deep breaths." The output is a feedback message to the user. 【0227】 Step 6: 【0228】 The user inputs questions or concerns during exercise into a terminal using a dialogue mechanism. The terminal sends this information to a server. The server utilizes a generative AI model to provide appropriate responses that take into account the user's emotional state. The output is the response information for the user. 【0229】 The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data. 【0230】 Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0231】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14. 【0232】 [Second Embodiment] 【0233】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0234】 As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server. 【0235】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0236】 The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52. 【0237】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0238】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0239】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0240】 Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0241】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0242】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0243】 In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0244】 Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0245】 This invention provides an exercise support system tailored to the individual needs of exercisers, integrating data acquisition, analysis, feedback, and dialogue mechanisms. The system is designed to maximize the effectiveness of exercisers' training and enable safe and efficient exercise. 【0246】 Data acquisition 【0247】 Devices: Wearable devices worn by athletes and communication terminals used by athletes have the capability to acquire important biometric information in real time, such as heart rate, acceleration, and GPS location data. This information provides detailed data about the athlete's current performance status. 【0248】 Data Analysis 【0249】 Server: The collected data is analyzed by the server's AI algorithm. This analysis is performed to capture an overall picture of the exerciser's physical condition and performance, and to generate an optimal exercise plan tailored to individual goals and fitness levels. 【0250】 Provide feedback 【0251】 Device: Based on the generated exercise plan, the device provides real-time feedback to the exerciser. For example, the device gives specific instructions via voice or text messages such as "Slow down your running pace" or "Emphatize your arm swing." 【0252】 Dialogue 【0253】 Server: Responses to exercisers' questions are prepared using natural language processing technology. When a user has a question about exercise, the server provides appropriate advice and information. 【0254】 Specific example 【0255】 User: For example, suppose a user is training for a marathon. One day, this user feels more tired than usual when running a long distance, especially in hot weather. 【0256】 Terminal: A wearable device detects an abnormal increase in heart rate and immediately sends that data to a server. 【0257】 Server: The AI ​​dynamically adjusts the exercise plan and instructs the user in real time to slow down. 【0258】 User: By receiving this feedback and slowing down, the user can safely continue training. At this time, the server may also suggest, "It would be a good idea to take a 15-minute break from training in this weather." 【0259】 In this way, the present invention provides individualized support tailored to the exerciser's situation, resulting in a more effective and safer training experience. 【0260】 The following describes the processing flow. 【0261】 Step 1: 【0262】 The device confirms that the user is wearing a wearable device and a communication terminal, and then begins acquiring data. Specifically, it collects heart rate, location information, and acceleration data in real time. 【0263】 Step 2: 【0264】 The device sends the collected data to the server. The data is packaged at regular time intervals and sent via secure communication. 【0265】 Step 3: 【0266】 The server inputs the received data into an AI algorithm for real-time analysis. The AI ​​evaluates the exerciser's activity and identifies indicators for improving form and safety. 【0267】 Step 4: 【0268】 The server generates a customized exercise plan for the user based on the analysis results. This plan includes elements such as the type of exercise, pace, and duration. 【0269】 Step 5: 【0270】 The device provides real-time feedback to the user based on the generated exercise plan. This includes specific exercise instructions via voice guidance and on-screen displays. 【0271】 Step 6: 【0272】 The server uses natural language processing technology to quickly answer questions submitted by users. It determines what additional information the user needs and provides an appropriate response. 【0273】 Step 7: 【0274】 After the user completes the training, the device provides comprehensive feedback, including a performance summary, achievement level, and advice for the next session. 【0275】 In this way, a series of processes are performed to support the user's fitness experience. 【0276】 (Example 1) 【0277】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0278】 In modern times, it is crucial for athletes to engage in effective and safe exercise tailored to their individual needs, but selecting appropriate exercise plans and providing real-time feedback remains challenging. There is a need to address this issue and provide a support system that enables athletes to maximize their performance. 【0279】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0280】 In this invention, the server includes an information acquisition means for collecting individual athlete information, an analysis means for analyzing the athlete information to generate an optimized exercise plan for the athlete, and a generation means for providing feedback and advice to the user in natural language using a generation AI model. This enables the formulation of an optimal exercise plan according to the athlete and the provision of prompt feedback. 【0281】 "Individual athlete information" refers to biometric data and activity data such as heart rate, acceleration, and position information acquired for each athlete. 【0282】 "Information acquisition means" refers to a device having a function of collecting biometric data and activity data from an athlete, including a wearable device and a communication device. 【0283】 "Analysis means" refers to a mechanism including an algorithm that analyzes the physical condition and performance of an athlete using the acquired data and generates an optimized exercise plan. 【0284】 "Notification means" refers to a device or system having a function of transmitting real-time feedback to an athlete based on the generated exercise plan. 【0285】 "Response means" refers to a system having an interactive function of providing information in response to an athlete's questions and requests and using natural language processing technology. 【0286】 "Generation AI model" refers to a statistical or machine learning-based model for performing data analysis and natural language generation using artificial intelligence. 【0287】 This invention is a system for providing individual support to athletes. It mainly utilizes wearable devices and communication devices to acquire individual athlete information and transmit it to the server. These devices are constantly connected to the server via Bluetooth or Wi-Fi. 【0288】 The server uses generative AI models and machine learning algorithms to analyze data received from the exerciser. This data analysis includes biometric data such as heart rate, acceleration, and location information, which allows for a deeper understanding of the exerciser's fitness level and daily exercise habits. 【0289】 Based on the analysis results, the server generates an optimized exercise plan. This exercise plan is sent to the device as feedback using natural language generation technology. The device provides instructions to the exerciser using voice output and screen displays. Specifically, this includes friendly advice such as "Let's slow down your running pace" or "It's time to hydrate." 【0290】 Furthermore, users can send questions to the server through a dialogue mechanism. The server can utilize natural language processing technology to provide appropriate answers and advice to the user's questions. This system will be a crucial support for exercisers in achieving their fitness goals. 【0291】 For example, if a user detects an abnormally high heart rate during marathon training, the device will react in real time by immediately displaying a message such as "Please slow down." 【0292】 Examples of prompt statements include the following: 【0293】 "Please provide appropriate advice on what to do when an abnormal heart rate is detected." 【0294】 "Please generate exercise advice based on the current weather conditions." 【0295】 This invention utilizes a variety of technological means to provide users with a more effective and safer exercise experience. 【0296】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0297】 Step 1: 【0298】 The terminal acquires biometric data such as the exerciser's heart rate, acceleration, and location information in real time through a wearable device. The terminal formats this data into a predetermined format and prepares it for transmission to the server. The input is the exerciser's biometric information, and the output is data packets that can be transferred to the server. 【0299】 Step 2: 【0300】 The server receives data packets formatted by the terminal. The server stores this data in a database and performs the necessary preprocessing for subsequent data analysis. The input is the data packets received from the terminal, and the output is the data stored in a format suitable for analysis. 【0301】 Step 3: 【0302】 The server uses a generative AI model to analyze incoming data in detail. It compares it with the exerciser's past exercise data to detect trends and anomalies in their condition. The input is exercise data stored in a database, and the output is insights or alerts about the exerciser's current condition. 【0303】 Step 4: 【0304】 Based on the analysis results, the server uses natural language generation technology to create appropriate feedback messages for the exerciser. For example, it may include specific instructions such as, "Your heart rate is high, please slow down." The input is the insights obtained from the analysis, and the output is the exercise guidance message. 【0305】 Step 5: 【0306】 The terminal receives the feedback message sent from the server and notifies the athlete of it. The terminal displays the message on the display or reads out the voice instruction using voice synthesis technology. The input is the feedback message from the server, and the output is the notification to the athlete or the voice instruction. 【0307】 Step 6: 【0308】 During exercise, the user inputs questions or requests using the terminal. The questions are input in voice or text and are sent from the terminal to the server. The input is the question from the user, and the output is the preparation for processing by the server. 【0309】 Step 7: 【0310】 The server analyzes the questions received from the user and generates appropriate answers or advice using natural language processing technology. The input is the question data from the user, and the output is the answer formed in natural language. 【0311】 Step 8: 【0312】 The terminal receives the answer from the server and notifies the athlete of it. This uses voice output or display on the display. The input is the answer data from the server, and the output is the notification to the athlete. 【0313】 (Application Example 1) 【0314】 Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal". 【0315】 In modern times, it is important to provide an effective and safe training method according to the needs of individual athletes, but it has been difficult to provide a system that dynamically adjusts feedback based on the athlete's condition and environmental conditions. An object of the present invention is to provide a system that can provide effective feedback according to the environment in real time to the athlete and optimize the exercise. 【0316】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0317】 In this invention, the server includes data acquisition means for collecting individual exercise data, analysis means for analyzing the exercise data and generating an optimized exercise plan for the exerciser, and feedback provision means for providing real-time feedback to the exerciser based on the exercise plan. This makes it possible to provide exercisers with dynamic exercise guidance that takes environmental conditions into account in real time, thereby supporting safe and effective training. 【0318】 "Data acquisition means" refers to a device or method for collecting individual biometric and environmental information of an exerciser. 【0319】 "Analysis means" refers to an algorithm or process for generating an optimized exercise plan based on acquired exercise data. 【0320】 A "feedback provision means" is a device or function that provides instructions and advice to the exerciser in real time based on the generated exercise plan. 【0321】 A "means of communication" refers to an interface or function for exchanging information with exercisers and providing advice and answers to questions during exercise. 【0322】 "Environmental analysis means" refers to a device or method for evaluating the environmental conditions surrounding an exerciser and generating appropriate advice. 【0323】 The system implementing this invention consists of a server and a terminal. The server collects data from wearable devices and communication terminals to acquire individual biometric and environmental information of the exerciser. As a result, data such as heart rate, acceleration, and GPS location are transmitted to the server in real time. 【0324】 The server analyzes this collected data using artificial intelligence algorithms. The analyzed data is used to generate an optimal exercise plan based on the exerciser's fitness level, goals, and environmental conditions. The server also uses environmental analysis tools to evaluate external conditions such as weather and time of day, and incorporates these into the exercise plan. 【0325】 The generated exercise plan is transferred to a device via a feedback system, and instructions are delivered to the exerciser in real time as voice or text messages. The device is a smartphone or smartwatch worn by the exerciser, allowing them to receive advice immediately and continue exercising safely and effectively. 【0326】 As a concrete example, consider a case where a user is training for a marathon on a hot day. In this case, the server detects an increase in heart rate data and adjusts the exercise plan, instructing the user to slow down. Furthermore, environmental analysis can be used to assess if the weather is unusually hot and suggest additional breaks to the user. 【0327】 An example of a prompt for a generative AI model is: "The robot assistant analyzes the exerciser's data in real time and provides exercise advice tailored to the weather. What kind of feedback should be provided when the user is running in the scorching sun?" 【0328】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0329】 Step 1: 【0330】 The server collects individual data from the exerciser. This process involves real-time acquisition of biometric information such as heart rate, acceleration, and GPS location from wearable devices and communication terminals. This data is transferred to the server and treated as initial data. 【0331】 Step 2: 【0332】 The server performs analysis based on the acquired data. It monitors the exerciser's heart rate and pace in real time and generates an optimized exercise plan using an artificial intelligence algorithm. This data processing takes into account the exerciser's current fitness level and goals to determine the next action. 【0333】 Step 3: 【0334】 The server acquires environmental information and incorporates it into the exercise plan. In this step, environmental conditions such as local temperature and humidity are collected based on geographical location information using weather APIs, etc. This makes the exercise plan more personalized. 【0335】 Step 4: 【0336】 The device receives an optimized exercise plan from the server and feedback based on environmental information. It provides real-time advice to the exerciser as voice instructions and text messages. Specifically, it suggests concrete actions such as "slow down" or "take a break for a certain period of time." 【0337】 Step 5: 【0338】 The user acts on the feedback received from the device. Following the instructions provided by the device during exercise improves safety and performance. At this stage, the interaction between the server and the device is complete, and real-time support continues until the exercise session ends. 【0339】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0340】 This invention is an exercise support system that combines an emotion engine that recognizes the user's emotions, thereby providing comprehensive support tailored to each individual exerciser. The following describes a typical embodiment for carrying out this invention. 【0341】 Data acquisition 【0342】 Terminal: To understand the user's condition during exercise, wearable devices and communication terminals collect biometric and environmental data. This includes heart rate, exercise data, and audio / video data from the terminal's camera and microphone. 【0343】 emotion recognition 【0344】 Server: Using audio and video data transmitted from the terminal, the emotion engine recognizes emotions from the user's facial expressions and tone of voice. This analysis identifies the user's emotional state. 【0345】 Data analysis and adjustment of exercise plan 【0346】 Server: The server analyzes collected exercise and emotional data using AI algorithms to generate or adjust an exercise plan optimized for the user. If emotional data detects, for example, fatigue or stress, the exercise intensity is adjusted accordingly. 【0347】 Real-time feedback 【0348】 Device: The device provides feedback to the user according to the exercise plan, including messages tailored to the user's emotional state. For example, if the user is feeling stressed, it might advise, "Relax and take slow, deep breaths." 【0349】 Dialogue 【0350】 Server: Provides appropriate answers to questions from participants using natural language processing techniques. This includes responses that take into account the user's current emotional state. 【0351】 Specific example 【0352】 User: A user is training using a fitness app. This user is trying a new exercise plan and feels a little anxious shortly after starting. 【0353】 The device's camera and microphone detect the anxiety and send it to the server. 【0354】 Server: The emotion engine detects anxiety and adjusts the difficulty level of the exercise plan. Based on this, the device provides voice advice such as, "Start slowly, and increase the pace as you get used to it." 【0355】 User: This feedback gives me the confidence to continue exercising. 【0356】 This invention aims to provide an optimal exercise experience by taking into account not only the user's physical characteristics but also their emotional characteristics. 【0357】 The following describes the processing flow. 【0358】 Step 1: 【0359】 The device activates the wearable device and communication terminal when the user prepares to start exercising, and simultaneously collects biometric data (heart rate, movement data, etc.) and audio / video data. 【0360】 Step 2: 【0361】 The device transmits collected biometric data and audio / video data to the server. This data is transferred in real time via a secure connection. 【0362】 Step 3: 【0363】 The server inputs audio and video data into the emotion engine to analyze the user's emotional state. The engine detects the user's emotions from their facial expressions and tone of voice, identifying states such as anxiety, stress, and concentration. 【0364】 Step 4: 【0365】 The server uses biometric data and emotional state to evaluate the user's exercise performance with an AI algorithm. Based on this evaluation, it makes appropriate adjustments to the exercise plan. For example, if emotional data indicates the user is fatigued, the plan is adjusted to reduce the exercise load. 【0366】 Step 5: 【0367】 The device provides feedback to the user based on the adjusted exercise plan. This feedback is delivered verbally, for example, "You don't seem to be feeling well. How about slowing down a bit?" 【0368】 Step 6: 【0369】 The server generates natural responses to user questions and requests, taking into account their emotional state, and delivers them through the terminal. For example, the response might suggest, "Taking a short break might help you relax." 【0370】 Step 7: 【0371】 When a user finishes their workout, the device sends all the process data to a server, and the server displays comprehensive feedback to the user. This feedback includes a summary of the workout and areas for improvement. 【0372】 (Example 2) 【0373】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0374】 Conventional exercise support systems provide exercise plans based solely on the exerciser's physical data, failing to consider emotional states and thus unable to provide optimal support for individual users. Furthermore, the low accuracy of feedback and dialogue leaves challenges in maintaining user motivation and improving the effectiveness of exercise. 【0375】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0376】 In this invention, the server includes data acquisition means for understanding the user's state by collecting individual exerciser's heart rate, activity level, and environmental information; emotion recognition means for identifying emotions from acquired audio and video; and analysis means for generating or adjusting an optimized exercise plan by analyzing exerciser data and emotion data. This enables optimal exercise support that takes into account the user's emotional state. 【0377】 "Data acquisition means" refers to a device or process for collecting information on the exerciser's heart rate, activity level, and environmental information in order to understand the user's condition. 【0378】 "Emotion recognition means" refers to a system or method for identifying a user's emotions based on acquired audio and video data. 【0379】 "Analysis means" refers to a device or process that has the function of analyzing exercise data and emotional data to generate or adjust an optimized exercise plan. 【0380】 A "feedback provision method" is a system for providing real-time feedback to users based on their exercise plan. 【0381】 A "dialogue method" is a system that engages in dialogue with the participant and provides advice and answers to questions using natural language processing technology. 【0382】 A "wearable device" is a device that a user can wear to collect physical and environmental information. 【0383】 A "communication device" is a device or group of devices used to collect data and transmit it to a server. 【0384】 An "artificial intelligence algorithm" is a computational method used to analyze and process data and make decisions based on a specific purpose. 【0385】 A "generated AI model" is a model that uses patterns learned from data to perform analysis and predictions based on new data. 【0386】 This system aims to continuously and dynamically collect individual information about athletes and, based on that information, provide them with optimal feedback in real time. A specific embodiment of the invention is configured as follows: 【0387】 Hardware and data acquisition 【0388】 The devices utilize wearable devices such as smartwatches and fitness trackers to acquire biometric information such as the exerciser's heart rate and activity level in real time. They also collect audio and video data via communication devices such as smartphones and tablets to understand the environment. These devices transmit data to the server using Bluetooth or Wi-Fi. 【0389】 Emotion recognition and data analysis 【0390】 The server performs emotion recognition based on the received audio and video data. The emotion engine used here incorporates machine learning algorithms that can identify emotions from the user's facial expressions and tone of voice. The server further analyzes all of the exerciser's data and uses the generated AI model to optimize and adjust the system according to the exerciser. 【0391】 Feedback and dialogue 【0392】 The device provides real-time feedback to the user. It notifies the user of exercise guidance and advice via voice or text, taking into account the user's emotional state. The server also utilizes natural language processing technology to provide appropriate answers to questions from the exerciser. 【0393】 Specific example 【0394】 If a user is experiencing anxiety while trying a new exercise program, the smartphone's camera and microphone detect this anxiety. The data is sent to a server where an emotion recognition engine analyzes the anxiety and adjusts the exercise plan. As a result, the device provides a message such as, "Start slowly, and increase the pace as you get used to it." 【0395】 Example of a prompt 【0396】 "Analyze the user's biometric and emotional data collected in real time and suggest how to adjust the exercise intensity." 【0397】 In this way, the present invention provides an optimal exercise experience that comprehensively considers the physical and emotional elements of the exerciser. 【0398】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0399】 Step 1: 【0400】 The terminal acquires biometric information such as the exerciser's heart rate and activity level in real time from a wearable device. It also collects the user's voice and video data using a communication device. This data, obtained as input, is immediately transmitted to the server. The output provides information on the exerciser's physical condition and environment. This data collection process forms the basis for understanding the user's daily fluctuations. 【0401】 Step 2: 【0402】 The server inputs audio and video data sent from the terminal into an emotion recognition engine. This allows the engine to identify the user's emotions from their facial expressions and tone of voice, and output a specific emotional state. This data processing enables analysis of the user's current psychological state. 【0403】 Step 3: 【0404】 The server inputs exercise and emotional data into an AI algorithm for analysis. It then generates or adjusts an exercise plan optimized for the user. As a result of this process, a new exercise plan is obtained as output. Specifically, the data calculation involves pattern recognition of past data to dynamically determine the most effective exercise intensity and content. 【0405】 Step 4: 【0406】 The device provides real-time feedback tailored to the user based on the generated exercise plan. This feedback includes advice that aligns with the user's emotional state. For example, a message such as "Let's slow down a bit today" might be presented via voice or text. Based on the exercise plan received as input, specific exercise instructions are output. 【0407】 Step 5: 【0408】 The server inputs questions from users into natural language processing technology and generates appropriate responses. These responses are output considering information retrieved from the database and the user's emotional state. Specifically, it analyzes the intent of the user's question and extracts and provides the best possible answer. In this way, a system that can respond to user inquiries immediately is realized. 【0409】 (Application Example 2) 【0410】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0411】 This invention aims to improve the exercise experience by considering not only the physical health but also the emotional health of the exerciser and providing an optimized exercise plan tailored to each individual exerciser. Furthermore, it aims to automate exercise adjustment based on emotion recognition, which was lacking in conventional exercise support systems, and to improve the accuracy of the feedback provided as a result. 【0412】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0413】 In this invention, the server includes data acquisition means for collecting individual exercise data, emotion recognition means for recognizing the emotional state of the exerciser, and analysis means for generating an optimized exercise plan for the exerciser. This enables real-time exercise adjustment and feedback provision based on the emotional state of the exerciser. 【0414】 "Individual exerciser data" refers to information that includes unique physical and physiological parameters for each exerciser, and is used to optimize exercise. 【0415】 "Emotion recognition means" refers to a component of a system that has the function of identifying an emotion based on the facial expression, tone of voice, and other cues of the person performing the action. 【0416】 An "analysis device" is a device that processes collected data and executes an algorithm to generate an optimized exercise plan for the exerciser. 【0417】 "Exercise plan adjustment means" refers to a device or program for appropriately modifying an existing exercise plan according to the emotional state of the person exercising. 【0418】 A "feedback provisioning device" is a device that has the function of transmitting advice and information to the exerciser in real time based on the generated exercise plan. 【0419】 A "means of dialogue" is an interface that provides advice and answers questions through communication with activists. 【0420】 A "portable device" is a device that can be worn on the body or carried around and collects exercise data or biometric data. 【0421】 A "machine learning algorithm" is a form of artificial intelligence technology used to analyze collected data and identify areas for improvement in a person's movements. 【0422】 The system for carrying out the present invention includes a series of components for monitoring and analyzing the user's physical and emotional state in real time and providing optimal exercise support. 【0423】 At the heart of the system is a server, which is responsible for receiving and analyzing vast amounts of data. Wearable devices and communication terminals collect heart rate and movement data while the user is wearing them. This data is supplemented by emotion recognition mechanisms, which identify the user's emotions from their facial expressions and voice. 【0424】 The server uses analysis tools based on this data to generate a user's exercise plan. A machine learning algorithm takes into account the user's movements and emotional state to construct the optimal exercise pattern in real time. Furthermore, an exercise plan adjustment tool dynamically modifies the plan based on the emotional state. 【0425】 While the user is exercising, feedback and interaction tools provide immediate advice based on a tailored exercise plan. For example, if the user feels stressed, the device sends a message encouraging relaxation. 【0426】 For example, when a user tries a new exercise program, if the emotion recognition function detects anxiety, the server adjusts the exercise intensity and provides feedback such as, "Start slowly, and increase the pace once you get used to it." 【0427】 Using a generative AI model, you can use prompts like the following: 【0428】 "What are some ideas for the support and feedback the system should provide when a user starts a new exercise routine for the first time? Please consider situations where the user might be feeling anxious." 【0429】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0430】 Step 1: 【0431】 The device collects heart rate and motion data from wearable devices, and audio and video data from communication devices. This data includes the user's exercise and emotional state. The device transmits the collected biometric data to a server. 【0432】 Step 2: 【0433】 The server receives data sent from the terminal and analyzes the user's emotional state using emotion recognition technology. The input audio and video data is processed by an analysis engine, identifying emotions from the user's facial expressions and tone of voice. The output is information about the user's emotional state. 【0434】 Step 3: 【0435】 The server uses analysis tools to generate an optimized exercise plan based on exercise and emotional data. The collected exercise data is processed using machine learning algorithms to generate exercise patterns suitable for the user. The output is the optimized exercise plan. 【0436】 Step 4: 【0437】 The server modifies the exercise plan based on the user's emotional state using an exercise plan adjustment mechanism. It detects the user's stress and fatigue levels from emotional data and adjusts the exercise intensity and content accordingly. The output is the adjusted exercise plan. 【0438】 Step 5: 【0439】 The device utilizes feedback mechanisms to provide the user with real-time feedback based on a customized exercise plan. For example, the device might send a voice message such as, "Relax and take slow, deep breaths." The output is a feedback message to the user. 【0440】 Step 6: 【0441】 The user inputs questions or concerns during exercise into a terminal using a dialogue mechanism. The terminal sends this information to a server. The server utilizes a generative AI model to provide appropriate responses that take into account the user's emotional state. The output is the response information for the user. 【0442】 The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0443】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0444】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214. 【0445】 [Third Embodiment] 【0446】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0447】 As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server. 【0448】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0449】 The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52. 【0450】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0451】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0452】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0453】 Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0454】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0455】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0456】 In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0457】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal". 【0458】 This invention provides an exercise support system tailored to the individual needs of exercisers, integrating data acquisition, analysis, feedback, and dialogue mechanisms. The system is designed to maximize the effectiveness of exercisers' training and enable safe and efficient exercise. 【0459】 Data acquisition 【0460】 Devices: Wearable devices worn by athletes and communication terminals used by athletes have the capability to acquire important biometric information in real time, such as heart rate, acceleration, and GPS location data. This information provides detailed data about the athlete's current performance status. 【0461】 Data Analysis 【0462】 Server: The collected data is analyzed by the server's AI algorithm. This analysis is performed to capture an overall picture of the exerciser's physical condition and performance, and to generate an optimal exercise plan tailored to individual goals and fitness levels. 【0463】 Provide feedback 【0464】 Device: Based on the generated exercise plan, the device provides real-time feedback to the exerciser. For example, the device gives specific instructions via voice or text messages such as "Slow down your running pace" or "Emphatize your arm swing." 【0465】 Dialogue 【0466】 Server: Responses to exercisers' questions are prepared using natural language processing technology. When a user has a question about exercise, the server provides appropriate advice and information. 【0467】 Specific example 【0468】 User: For example, suppose a user is training for a marathon. One day, this user feels more tired than usual when running a long distance, especially in hot weather. 【0469】 Terminal: A wearable device detects an abnormal increase in heart rate and immediately sends that data to a server. 【0470】 Server: The AI ​​dynamically adjusts the exercise plan and instructs the user in real time to slow down. 【0471】 User: By receiving this feedback and slowing down, the user can safely continue training. At this time, the server may also suggest, "It would be a good idea to take a 15-minute break from training in this weather." 【0472】 In this way, the present invention provides individualized support tailored to the exerciser's situation, resulting in a more effective and safer training experience. 【0473】 The following describes the processing flow. 【0474】 Step 1: 【0475】 The device confirms that the user is wearing a wearable device and a communication terminal, and then begins acquiring data. Specifically, it collects heart rate, location information, and acceleration data in real time. 【0476】 Step 2: 【0477】 The device sends the collected data to the server. The data is packaged at regular time intervals and sent via secure communication. 【0478】 Step 3: 【0479】 The server inputs the received data into an AI algorithm for real-time analysis. The AI ​​evaluates the exerciser's activity and identifies indicators for improving form and safety. 【0480】 Step 4: 【0481】 The server generates a customized exercise plan for the user based on the analysis results. This plan includes elements such as the type of exercise, pace, and duration. 【0482】 Step 5: 【0483】 The device provides real-time feedback to the user based on the generated exercise plan. This includes specific exercise instructions via voice guidance and on-screen displays. 【0484】 Step 6: 【0485】 The server uses natural language processing technology to quickly answer questions submitted by users. It determines what additional information the user needs and provides an appropriate response. 【0486】 Step 7: 【0487】 After the user completes the training, the device provides comprehensive feedback, including a performance summary, achievement level, and advice for the next session. 【0488】 In this way, a series of processes are performed to support the user's fitness experience. 【0489】 (Example 1) 【0490】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0491】 In modern times, it is crucial for athletes to engage in effective and safe exercise tailored to their individual needs, but selecting appropriate exercise plans and providing real-time feedback remains challenging. There is a need to address this issue and provide a support system that enables athletes to maximize their performance. 【0492】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0493】 In this invention, the server includes information acquisition means for collecting individual exercise information, analysis means for analyzing the exercise information to generate an optimized exercise plan for the exerciser, and generation means for providing feedback and advice to the user in natural language using a generated AI model. This enables the formulation of an optimal exercise plan tailored to the exerciser and the provision of rapid feedback. 【0494】 "Individual exerciser information" refers to biometric data such as heart rate, acceleration, and location information, as well as activity data, acquired for each exerciser. 【0495】 "Information acquisition means" refers to devices that have the function of collecting biometric data and activity data from athletes, and include wearable devices and communication devices. 【0496】 "Analysis means" refers to a system that includes an algorithm that uses acquired data to analyze the physical condition and performance of the exerciser and generates an optimized exercise plan. 【0497】 "Notification means" refers to a device or system that has the function of sending real-time feedback to the exerciser based on the generated exercise plan. 【0498】 A "response mechanism" refers to a system that has an interactive function to provide information in response to the user's questions or requests, and uses natural language processing technology. 【0499】 A "generative AI model" refers to a statistical or machine learning-based model that uses artificial intelligence to perform data analysis and natural language generation. 【0500】 This invention is a system for providing individualized support to athletes. It primarily utilizes wearable devices and communication equipment to acquire individual athlete information and transmit it to a server. These devices are constantly connected to the server via Bluetooth or Wi-Fi. 【0501】 The server uses generative AI models and machine learning algorithms to analyze data received from the exerciser. This data analysis includes biometric data such as heart rate, acceleration, and location information, which allows for a deeper understanding of the exerciser's fitness level and daily exercise habits. 【0502】 Based on the analysis results, the server generates an optimized exercise plan. This exercise plan is sent to the device as feedback using natural language generation technology. The device provides instructions to the exerciser using voice output and screen displays. Specifically, this includes friendly advice such as "Let's slow down your running pace" or "It's time to hydrate." 【0503】 Furthermore, users can send questions to the server through a dialogue mechanism. The server can utilize natural language processing technology to provide appropriate answers and advice to the user's questions. This system will be a crucial support for exercisers in achieving their fitness goals. 【0504】 For example, if a user detects an abnormally high heart rate during marathon training, the device will react in real time by immediately displaying a message such as "Please slow down." 【0505】 Examples of prompt statements include the following: 【0506】 "Please provide appropriate advice on what to do when an abnormal heart rate is detected." 【0507】 "Please generate exercise advice based on the current weather conditions." 【0508】 This invention utilizes a variety of technological means to provide users with a more effective and safer exercise experience. 【0509】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0510】 Step 1: 【0511】 The terminal acquires biometric data such as the exerciser's heart rate, acceleration, and location information in real time through a wearable device. The terminal formats this data into a predetermined format and prepares it for transmission to the server. The input is the exerciser's biometric information, and the output is data packets that can be transferred to the server. 【0512】 Step 2: 【0513】 The server receives data packets formatted by the terminal. The server stores this data in a database and performs the necessary preprocessing for subsequent data analysis. The input is the data packets received from the terminal, and the output is the data stored in a format suitable for analysis. 【0514】 Step 3: 【0515】 The server uses a generative AI model to analyze incoming data in detail. It compares it with the exerciser's past exercise data to detect trends and anomalies in their condition. The input is exercise data stored in a database, and the output is insights or alerts about the exerciser's current condition. 【0516】 Step 4: 【0517】 Based on the analysis results, the server uses natural language generation technology to create appropriate feedback messages for the exerciser. For example, it may include specific instructions such as, "Your heart rate is high, please slow down." The input is the insights obtained from the analysis, and the output is the exercise guidance message. 【0518】 Step 5: 【0519】 The terminal receives feedback messages sent from the server and notifies the exerciser of these messages. The terminal displays the messages on its screen or reads out voice instructions using speech synthesis technology. The input is feedback messages from the server, and the output is notifications or voice instructions to the exerciser. 【0520】 Step 6: 【0521】 The user enters questions or requests on a terminal during exercise. Questions are entered via voice or text and sent from the terminal to the server. The input is the user's question, and the output is the server's preparation for processing. 【0522】 Step 7: 【0523】 The server analyzes questions received from users and generates appropriate answers and advice using natural language processing techniques. The input is user question data, and the output is an answer formed in natural language. 【0524】 Step 8: 【0525】 The terminal receives responses from the server and notifies the participant. This is done using audio output or a display. The input is the response data from the server, and the output is the notification to the participant. 【0526】 (Application Example 1) 【0527】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0528】 In modern times, providing effective and safe training methods tailored to the individual needs of athletes is crucial, but it has been difficult to provide a system that dynamically adjusts feedback based on the athlete's condition and environmental factors. The present invention aims to provide a system that can provide athletes with real-time, environmentally responsive and effective feedback, thereby optimizing their exercise. 【0529】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0530】 In this invention, the server includes data acquisition means for collecting individual exercise data, analysis means for analyzing the exercise data and generating an optimized exercise plan for the exerciser, and feedback provision means for providing real-time feedback to the exerciser based on the exercise plan. This makes it possible to provide exercisers with dynamic exercise guidance that takes environmental conditions into account in real time, thereby supporting safe and effective training. 【0531】 "Data acquisition means" refers to a device or method for collecting individual biometric and environmental information of an exerciser. 【0532】 "Analysis means" refers to an algorithm or process for generating an optimized exercise plan based on acquired exercise data. 【0533】 A "feedback provision means" is a device or function that provides instructions and advice to the exerciser in real time based on the generated exercise plan. 【0534】 A "means of communication" refers to an interface or function for exchanging information with exercisers and providing advice and answers to questions during exercise. 【0535】 "Environmental analysis means" refers to a device or method for evaluating the environmental conditions surrounding an exerciser and generating appropriate advice. 【0536】 The system implementing this invention consists of a server and a terminal. The server collects data from wearable devices and communication terminals to acquire individual biometric and environmental information of the exerciser. As a result, data such as heart rate, acceleration, and GPS location are transmitted to the server in real time. 【0537】 The server analyzes this collected data using artificial intelligence algorithms. The analyzed data is used to generate an optimal exercise plan based on the exerciser's fitness level, goals, and environmental conditions. The server also uses environmental analysis tools to evaluate external conditions such as weather and time of day, and incorporates these into the exercise plan. 【0538】 The generated exercise plan is transferred to a device via a feedback system, and instructions are delivered to the exerciser in real time as voice or text messages. The device is a smartphone or smartwatch worn by the exerciser, allowing them to receive advice immediately and continue exercising safely and effectively. 【0539】 As a concrete example, consider a case where a user is training for a marathon on a hot day. In this case, the server detects an increase in heart rate data and adjusts the exercise plan, instructing the user to slow down. Furthermore, environmental analysis can be used to assess if the weather is unusually hot and suggest additional breaks to the user. 【0540】 An example of a prompt for a generative AI model is: "The robot assistant analyzes the exerciser's data in real time and provides exercise advice tailored to the weather. What kind of feedback should be provided when the user is running in the scorching sun?" 【0541】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0542】 Step 1: 【0543】 The server collects individual data from the exerciser. This process involves real-time acquisition of biometric information such as heart rate, acceleration, and GPS location from wearable devices and communication terminals. This data is transferred to the server and treated as initial data. 【0544】 Step 2: 【0545】 The server performs analysis based on the acquired data. It monitors the exerciser's heart rate and pace in real time and generates an optimized exercise plan using an artificial intelligence algorithm. This data processing takes into account the exerciser's current fitness level and goals to determine the next action. 【0546】 Step 3: 【0547】 The server acquires environmental information and incorporates it into the exercise plan. In this step, environmental conditions such as local temperature and humidity are collected based on geographical location information using weather APIs, etc. This makes the exercise plan more personalized. 【0548】 Step 4: 【0549】 The device receives an optimized exercise plan from the server and feedback based on environmental information. It provides real-time advice to the exerciser as voice instructions and text messages. Specifically, it suggests concrete actions such as "slow down" or "take a break for a certain period of time." 【0550】 Step 5: 【0551】 The user acts on the feedback received from the device. Following the instructions provided by the device during exercise improves safety and performance. At this stage, the interaction between the server and the device is complete, and real-time support continues until the exercise session ends. 【0552】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0553】 This invention is an exercise support system that combines an emotion engine that recognizes the user's emotions, thereby providing comprehensive support tailored to each individual exerciser. The following describes a typical embodiment for carrying out this invention. 【0554】 Data acquisition 【0555】 Terminal: To understand the user's condition during exercise, wearable devices and communication terminals collect biometric and environmental data. This includes heart rate, exercise data, and audio / video data from the terminal's camera and microphone. 【0556】 emotion recognition 【0557】 Server: Using audio and video data transmitted from the terminal, the emotion engine recognizes emotions from the user's facial expressions and tone of voice. This analysis identifies the user's emotional state. 【0558】 Data analysis and adjustment of exercise plan 【0559】 Server: The server analyzes collected exercise and emotional data using AI algorithms to generate or adjust an exercise plan optimized for the user. If emotional data detects, for example, fatigue or stress, the exercise intensity is adjusted accordingly. 【0560】 Real-time feedback 【0561】 Device: The device provides feedback to the user according to the exercise plan, including messages tailored to the user's emotional state. For example, if the user is feeling stressed, it might advise, "Relax and take slow, deep breaths." 【0562】 Dialogue 【0563】 Server: Provides appropriate answers to questions from participants using natural language processing techniques. This includes responses that take into account the user's current emotional state. 【0564】 Specific example 【0565】 User: A user is training using a fitness app. This user is trying a new exercise plan and feels a little anxious shortly after starting. 【0566】 The device's camera and microphone detect the anxiety and send it to the server. 【0567】 Server: The emotion engine detects anxiety and adjusts the difficulty level of the exercise plan. Based on this, the device provides voice advice such as, "Start slowly, and increase the pace as you get used to it." 【0568】 User: This feedback gives me the confidence to continue exercising. 【0569】 This invention aims to provide an optimal exercise experience by taking into account not only the user's physical characteristics but also their emotional characteristics. 【0570】 The following describes the processing flow. 【0571】 Step 1: 【0572】 The device activates the wearable device and communication terminal when the user prepares to start exercising, and simultaneously collects biometric data (heart rate, movement data, etc.) and audio / video data. 【0573】 Step 2: 【0574】 The device transmits collected biometric data and audio / video data to the server. This data is transferred in real time via a secure connection. 【0575】 Step 3: 【0576】 The server inputs audio and video data into the emotion engine to analyze the user's emotional state. The engine detects the user's emotions from their facial expressions and tone of voice, identifying states such as anxiety, stress, and concentration. 【0577】 Step 4: 【0578】 The server uses biometric data and emotional state to evaluate the user's exercise performance with an AI algorithm. Based on this evaluation, it makes appropriate adjustments to the exercise plan. For example, if emotional data indicates the user is fatigued, the plan is adjusted to reduce the exercise load. 【0579】 Step 5: 【0580】 The device provides feedback to the user based on the adjusted exercise plan. This feedback is delivered verbally, for example, "You don't seem to be feeling well. How about slowing down a bit?" 【0581】 Step 6: 【0582】 The server generates natural responses to user questions and requests, taking into account their emotional state, and delivers them through the terminal. For example, the response might suggest, "Taking a short break might help you relax." 【0583】 Step 7: 【0584】 When a user finishes their workout, the device sends all the process data to a server, and the server displays comprehensive feedback to the user. This feedback includes a summary of the workout and areas for improvement. 【0585】 (Example 2) 【0586】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0587】 Conventional exercise support systems provide exercise plans based solely on the exerciser's physical data, failing to consider emotional states and thus unable to provide optimal support for individual users. Furthermore, the low accuracy of feedback and dialogue leaves challenges in maintaining user motivation and improving the effectiveness of exercise. 【0588】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0589】 In this invention, the server includes data acquisition means for understanding the user's state by collecting individual exerciser's heart rate, activity level, and environmental information; emotion recognition means for identifying emotions from acquired audio and video; and analysis means for generating or adjusting an optimized exercise plan by analyzing exerciser data and emotion data. This enables optimal exercise support that takes into account the user's emotional state. 【0590】 "Data acquisition means" refers to a device or process for collecting information on the exerciser's heart rate, activity level, and environmental information in order to understand the user's condition. 【0591】 "Emotion recognition means" refers to a system or method for identifying a user's emotions based on acquired audio and video data. 【0592】 "Analysis means" refers to a device or process that has the function of analyzing exercise data and emotional data to generate or adjust an optimized exercise plan. 【0593】 A "feedback provision method" is a system for providing real-time feedback to users based on their exercise plan. 【0594】 A "dialogue method" is a system that engages in dialogue with the participant and provides advice and answers to questions using natural language processing technology. 【0595】 A "wearable device" is a device that a user can wear to collect physical and environmental information. 【0596】 A "communication device" is a device or group of devices used to collect data and transmit it to a server. 【0597】 An "artificial intelligence algorithm" is a computational method used to analyze and process data and make decisions based on a specific purpose. 【0598】 A "generated AI model" is a model that uses patterns learned from data to perform analysis and predictions based on new data. 【0599】 This system aims to continuously and dynamically collect individual information about athletes and, based on that information, provide them with optimal feedback in real time. A specific embodiment of the invention is configured as follows: 【0600】 Hardware and data acquisition 【0601】 The devices utilize wearable devices such as smartwatches and fitness trackers to acquire biometric information such as the exerciser's heart rate and activity level in real time. They also collect audio and video data via communication devices such as smartphones and tablets to understand the environment. These devices transmit data to the server using Bluetooth or Wi-Fi. 【0602】 Emotion recognition and data analysis 【0603】 The server performs emotion recognition based on the received audio and video data. The emotion engine used here incorporates machine learning algorithms that can identify emotions from the user's facial expressions and tone of voice. The server further analyzes all of the exerciser's data and uses the generated AI model to optimize and adjust the system according to the exerciser. 【0604】 Feedback and dialogue 【0605】 The device provides real-time feedback to the user. It notifies the user of exercise guidance and advice via voice or text, taking into account the user's emotional state. The server also utilizes natural language processing technology to provide appropriate answers to questions from the exerciser. 【0606】 Specific example 【0607】 If a user is experiencing anxiety while trying a new exercise program, the smartphone's camera and microphone detect this anxiety. The data is sent to a server where an emotion recognition engine analyzes the anxiety and adjusts the exercise plan. As a result, the device provides a message such as, "Start slowly, and increase the pace as you get used to it." 【0608】 Example of a prompt 【0609】 "Analyze the user's biometric and emotional data collected in real time and suggest how to adjust the exercise intensity." 【0610】 In this way, the present invention provides an optimal exercise experience that comprehensively considers the physical and emotional elements of the exerciser. 【0611】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0612】 Step 1: 【0613】 The terminal acquires biometric information such as the exerciser's heart rate and activity level in real time from a wearable device. It also collects the user's voice and video data using a communication device. This data, obtained as input, is immediately transmitted to the server. The output provides information on the exerciser's physical condition and environment. This data collection process forms the basis for understanding the user's daily fluctuations. 【0614】 Step 2: 【0615】 The server inputs audio and video data sent from the terminal into an emotion recognition engine. This allows the engine to identify the user's emotions from their facial expressions and tone of voice, and output a specific emotional state. This data processing enables analysis of the user's current psychological state. 【0616】 Step 3: 【0617】 The server inputs exercise and emotional data into an AI algorithm for analysis. It then generates or adjusts an exercise plan optimized for the user. As a result of this process, a new exercise plan is obtained as output. Specifically, the data calculation involves pattern recognition of past data to dynamically determine the most effective exercise intensity and content. 【0618】 Step 4: 【0619】 The device provides real-time feedback tailored to the user based on the generated exercise plan. This feedback includes advice that aligns with the user's emotional state. For example, a message such as "Let's slow down a bit today" might be presented via voice or text. Based on the exercise plan received as input, specific exercise instructions are output. 【0620】 Step 5: 【0621】 The server inputs questions from users into natural language processing technology and generates appropriate responses. These responses are output considering information retrieved from the database and the user's emotional state. Specifically, it analyzes the intent of the user's question and extracts and provides the best possible answer. In this way, a system that can respond to user inquiries immediately is realized. 【0622】 (Application Example 2) 【0623】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0624】 This invention aims to improve the exercise experience by considering not only the physical health but also the emotional health of the exerciser and providing an optimized exercise plan tailored to each individual exerciser. Furthermore, it aims to automate exercise adjustment based on emotion recognition, which was lacking in conventional exercise support systems, and to improve the accuracy of the feedback provided as a result. 【0625】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0626】 In this invention, the server includes data acquisition means for collecting individual exercise data, emotion recognition means for recognizing the emotional state of the exerciser, and analysis means for generating an optimized exercise plan for the exerciser. This enables real-time exercise adjustment and feedback provision based on the emotional state of the exerciser. 【0627】 "Individual exerciser data" refers to information that includes unique physical and physiological parameters for each exerciser, and is used to optimize exercise. 【0628】 "Emotion recognition means" refers to a component of a system that has the function of identifying an emotion based on the facial expression, tone of voice, and other cues of the person performing the action. 【0629】 An "analysis device" is a device that processes collected data and executes an algorithm to generate an optimized exercise plan for the exerciser. 【0630】 "Exercise plan adjustment means" refers to a device or program for appropriately modifying an existing exercise plan according to the emotional state of the person exercising. 【0631】 A "feedback provisioning device" is a device that has the function of transmitting advice and information to the exerciser in real time based on the generated exercise plan. 【0632】 A "means of dialogue" is an interface that provides advice and answers questions through communication with activists. 【0633】 A "portable device" is a device that can be worn on the body or carried around and collects exercise data or biometric data. 【0634】 A "machine learning algorithm" is a form of artificial intelligence technology used to analyze collected data and identify areas for improvement in a person's movements. 【0635】 The system for carrying out the present invention includes a series of components for monitoring and analyzing the user's physical and emotional state in real time and providing optimal exercise support. 【0636】 At the heart of the system is a server, which is responsible for receiving and analyzing vast amounts of data. Wearable devices and communication terminals collect heart rate and movement data while the user is wearing them. This data is supplemented by emotion recognition mechanisms, which identify the user's emotions from their facial expressions and voice. 【0637】 The server uses analysis tools based on this data to generate a user's exercise plan. A machine learning algorithm takes into account the user's movements and emotional state to construct the optimal exercise pattern in real time. Furthermore, an exercise plan adjustment tool dynamically modifies the plan based on the emotional state. 【0638】 While the user is exercising, feedback and interaction tools provide immediate advice based on a tailored exercise plan. For example, if the user feels stressed, the device sends a message encouraging relaxation. 【0639】 For example, when a user tries a new exercise program, if the emotion recognition function detects anxiety, the server adjusts the exercise intensity and provides feedback such as, "Start slowly, and increase the pace once you get used to it." 【0640】 Using a generative AI model, you can use prompts like the following: 【0641】 "What are some ideas for the support and feedback the system should provide when a user starts a new exercise routine for the first time? Please consider situations where the user might be feeling anxious." 【0642】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0643】 Step 1: 【0644】 The device collects heart rate and motion data from wearable devices, and audio and video data from communication devices. This data includes the user's exercise and emotional state. The device transmits the collected biometric data to a server. 【0645】 Step 2: 【0646】 The server receives data sent from the terminal and analyzes the user's emotional state using emotion recognition technology. The input audio and video data is processed by an analysis engine, identifying emotions from the user's facial expressions and tone of voice. The output is information about the user's emotional state. 【0647】 Step 3: 【0648】 The server uses analysis tools to generate an optimized exercise plan based on exercise and emotional data. The collected exercise data is processed using machine learning algorithms to generate exercise patterns suitable for the user. The output is the optimized exercise plan. 【0649】 Step 4: 【0650】 The server modifies the exercise plan based on the user's emotional state using an exercise plan adjustment mechanism. It detects the user's stress and fatigue levels from emotional data and adjusts the exercise intensity and content accordingly. The output is the adjusted exercise plan. 【0651】 Step 5: 【0652】 The device utilizes feedback mechanisms to provide the user with real-time feedback based on a customized exercise plan. For example, the device might send a voice message such as, "Relax and take slow, deep breaths." The output is a feedback message to the user. 【0653】 Step 6: 【0654】 The user inputs questions or concerns during exercise into a terminal using a dialogue mechanism. The terminal sends this information to a server. The server utilizes a generative AI model to provide appropriate responses that take into account the user's emotional state. The output is the response information for the user. 【0655】 The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0656】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0657】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314. 【0658】 [Fourth Embodiment] 【0659】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0660】 As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server. 【0661】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0662】 The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52. 【0663】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0664】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0665】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0666】 The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes. 【0667】 Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0668】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0669】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0670】 In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0671】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0672】 This invention provides an exercise support system tailored to the individual needs of exercisers, integrating data acquisition, analysis, feedback, and dialogue mechanisms. The system is designed to maximize the effectiveness of exercisers' training and enable safe and efficient exercise. 【0673】 Data acquisition 【0674】 Devices: Wearable devices worn by athletes and communication terminals used by athletes have the capability to acquire important biometric information in real time, such as heart rate, acceleration, and GPS location data. This information provides detailed data about the athlete's current performance status. 【0675】 Data Analysis 【0676】 Server: The collected data is analyzed by the server's AI algorithm. This analysis is performed to capture an overall picture of the exerciser's physical condition and performance, and to generate an optimal exercise plan tailored to individual goals and fitness levels. 【0677】 Provide feedback 【0678】 Device: Based on the generated exercise plan, the device provides real-time feedback to the exerciser. For example, the device gives specific instructions via voice or text messages such as "Slow down your running pace" or "Emphatize your arm swing." 【0679】 Dialogue 【0680】 Server: Responses to exercisers' questions are prepared using natural language processing technology. When a user has a question about exercise, the server provides appropriate advice and information. 【0681】 Specific example 【0682】 User: For example, suppose a user is training for a marathon. One day, this user feels more tired than usual when running a long distance, especially in hot weather. 【0683】 Terminal: A wearable device detects an abnormal increase in heart rate and immediately sends that data to a server. 【0684】 Server: The AI ​​dynamically adjusts the exercise plan and instructs the user in real time to slow down. 【0685】 User: By receiving this feedback and slowing down, the user can safely continue training. At this time, the server may also suggest, "It would be a good idea to take a 15-minute break from training in this weather." 【0686】 In this way, the present invention provides individualized support tailored to the exerciser's situation, resulting in a more effective and safer training experience. 【0687】 The following describes the processing flow. 【0688】 Step 1: 【0689】 The device confirms that the user is wearing a wearable device and a communication terminal, and then begins acquiring data. Specifically, it collects heart rate, location information, and acceleration data in real time. 【0690】 Step 2: 【0691】 The device sends the collected data to the server. The data is packaged at regular time intervals and sent via secure communication. 【0692】 Step 3: 【0693】 The server inputs the received data into an AI algorithm for real-time analysis. The AI ​​evaluates the exerciser's activity and identifies indicators for improving form and safety. 【0694】 Step 4: 【0695】 The server generates a customized exercise plan for the user based on the analysis results. This plan includes elements such as the type of exercise, pace, and duration. 【0696】 Step 5: 【0697】 The device provides real-time feedback to the user based on the generated exercise plan. This includes specific exercise instructions via voice guidance and on-screen displays. 【0698】 Step 6: 【0699】 The server uses natural language processing technology to quickly answer questions submitted by users. It determines what additional information the user needs and provides an appropriate response. 【0700】 Step 7: 【0701】 After the user completes the training, the device provides comprehensive feedback, including a performance summary, achievement level, and advice for the next session. 【0702】 In this way, a series of processes are performed to support the user's fitness experience. 【0703】 (Example 1) 【0704】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0705】 In modern times, it is crucial for athletes to engage in effective and safe exercise tailored to their individual needs, but selecting appropriate exercise plans and providing real-time feedback remains challenging. There is a need to address this issue and provide a support system that enables athletes to maximize their performance. 【0706】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0707】 In this invention, the server includes information acquisition means for collecting individual exercise information, analysis means for analyzing the exercise information to generate an optimized exercise plan for the exerciser, and generation means for providing feedback and advice to the user in natural language using a generated AI model. This enables the formulation of an optimal exercise plan tailored to the exerciser and the provision of rapid feedback. 【0708】 "Individual exerciser information" refers to biometric data such as heart rate, acceleration, and location information, as well as activity data, acquired for each exerciser. 【0709】 "Information acquisition means" refers to devices that have the function of collecting biometric data and activity data from athletes, and include wearable devices and communication devices. 【0710】 "Analysis means" refers to a system that includes an algorithm that uses acquired data to analyze the physical condition and performance of the exerciser and generates an optimized exercise plan. 【0711】 "Notification means" refers to a device or system that has the function of sending real-time feedback to the exerciser based on the generated exercise plan. 【0712】 A "response mechanism" refers to a system that has an interactive function to provide information in response to the user's questions or requests, and uses natural language processing technology. 【0713】 A "generative AI model" refers to a statistical or machine learning-based model that uses artificial intelligence to perform data analysis and natural language generation. 【0714】 This invention is a system for providing individualized support to athletes. It primarily utilizes wearable devices and communication equipment to acquire individual athlete information and transmit it to a server. These devices are constantly connected to the server via Bluetooth or Wi-Fi. 【0715】 The server uses generative AI models and machine learning algorithms to analyze data received from the exerciser. This data analysis includes biometric data such as heart rate, acceleration, and location information, which allows for a deeper understanding of the exerciser's fitness level and daily exercise habits. 【0716】 Based on the analysis results, the server generates an optimized exercise plan. This exercise plan is sent to the device as feedback using natural language generation technology. The device provides instructions to the exerciser using voice output and screen displays. Specifically, this includes friendly advice such as "Let's slow down your running pace" or "It's time to hydrate." 【0717】 Furthermore, users can send questions to the server through a dialogue mechanism. The server can utilize natural language processing technology to provide appropriate answers and advice to the user's questions. This system will be a crucial support for exercisers in achieving their fitness goals. 【0718】 For example, if a user detects an abnormally high heart rate during marathon training, the device will react in real time by immediately displaying a message such as "Please slow down." 【0719】 Examples of prompt statements include the following: 【0720】 "Please provide appropriate advice on what to do when an abnormal heart rate is detected." 【0721】 "Please generate exercise advice based on the current weather conditions." 【0722】 This invention utilizes a variety of technological means to provide users with a more effective and safer exercise experience. 【0723】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0724】 Step 1: 【0725】 The terminal acquires biometric data such as the exerciser's heart rate, acceleration, and location information in real time through a wearable device. The terminal formats this data into a predetermined format and prepares it for transmission to the server. The input is the exerciser's biometric information, and the output is data packets that can be transferred to the server. 【0726】 Step 2: 【0727】 The server receives data packets formatted by the terminal. The server stores this data in a database and performs the necessary preprocessing for subsequent data analysis. The input is the data packets received from the terminal, and the output is the data stored in a format suitable for analysis. 【0728】 Step 3: 【0729】 The server uses a generative AI model to analyze incoming data in detail. It compares it with the exerciser's past exercise data to detect trends and anomalies in their condition. The input is exercise data stored in a database, and the output is insights or alerts about the exerciser's current condition. 【0730】 Step 4: 【0731】 Based on the analysis results, the server uses natural language generation technology to create appropriate feedback messages for the exerciser. For example, it may include specific instructions such as, "Your heart rate is high, please slow down." The input is the insights obtained from the analysis, and the output is the exercise guidance message. 【0732】 Step 5: 【0733】 The terminal receives feedback messages sent from the server and notifies the exerciser of these messages. The terminal displays the messages on its screen or reads out voice instructions using speech synthesis technology. The input is feedback messages from the server, and the output is notifications or voice instructions to the exerciser. 【0734】 Step 6: 【0735】 The user enters questions or requests on a terminal during exercise. Questions are entered via voice or text and sent from the terminal to the server. The input is the user's question, and the output is the server's preparation for processing. 【0736】 Step 7: 【0737】 The server analyzes questions received from users and generates appropriate answers and advice using natural language processing techniques. The input is user question data, and the output is an answer formed in natural language. 【0738】 Step 8: 【0739】 The terminal receives responses from the server and notifies the participant. This is done using audio output or a display. The input is the response data from the server, and the output is the notification to the participant. 【0740】 (Application Example 1) 【0741】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0742】 In modern times, providing effective and safe training methods tailored to the individual needs of athletes is crucial, but it has been difficult to provide a system that dynamically adjusts feedback based on the athlete's condition and environmental factors. The present invention aims to provide a system that can provide athletes with real-time, environmentally responsive and effective feedback, thereby optimizing their exercise. 【0743】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0744】 In this invention, the server includes data acquisition means for collecting individual exercise data, analysis means for analyzing the exercise data and generating an optimized exercise plan for the exerciser, and feedback provision means for providing real-time feedback to the exerciser based on the exercise plan. This makes it possible to provide exercisers with dynamic exercise guidance that takes environmental conditions into account in real time, thereby supporting safe and effective training. 【0745】 "Data acquisition means" refers to a device or method for collecting individual biometric and environmental information of an exerciser. 【0746】 "Analysis means" refers to an algorithm or process for generating an optimized exercise plan based on acquired exercise data. 【0747】 A "feedback provision means" is a device or function that provides instructions and advice to the exerciser in real time based on the generated exercise plan. 【0748】 A "means of communication" refers to an interface or function for exchanging information with exercisers and providing advice and answers to questions during exercise. 【0749】 "Environmental analysis means" refers to a device or method for evaluating the environmental conditions surrounding an exerciser and generating appropriate advice. 【0750】 The system implementing this invention consists of a server and a terminal. The server collects data from wearable devices and communication terminals to acquire individual biometric and environmental information of the exerciser. As a result, data such as heart rate, acceleration, and GPS location are transmitted to the server in real time. 【0751】 The server analyzes this collected data using artificial intelligence algorithms. The analyzed data is used to generate an optimal exercise plan based on the exerciser's fitness level, goals, and environmental conditions. The server also uses environmental analysis tools to evaluate external conditions such as weather and time of day, and incorporates these into the exercise plan. 【0752】 The generated exercise plan is transferred to a device via a feedback system, and instructions are delivered to the exerciser in real time as voice or text messages. The device is a smartphone or smartwatch worn by the exerciser, allowing them to receive advice immediately and continue exercising safely and effectively. 【0753】 As a concrete example, consider a case where a user is training for a marathon on a hot day. In this case, the server detects an increase in heart rate data and adjusts the exercise plan, instructing the user to slow down. Furthermore, environmental analysis can be used to assess if the weather is unusually hot and suggest additional breaks to the user. 【0754】 An example of a prompt for a generative AI model is: "The robot assistant analyzes the exerciser's data in real time and provides exercise advice tailored to the weather. What kind of feedback should be provided when the user is running in the scorching sun?" 【0755】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0756】 Step 1: 【0757】 The server collects individual data from the exerciser. This process involves real-time acquisition of biometric information such as heart rate, acceleration, and GPS location from wearable devices and communication terminals. This data is transferred to the server and treated as initial data. 【0758】 Step 2: 【0759】 The server performs analysis based on the acquired data. It monitors the exerciser's heart rate and pace in real time and generates an optimized exercise plan using an artificial intelligence algorithm. This data processing takes into account the exerciser's current fitness level and goals to determine the next action. 【0760】 Step 3: 【0761】 The server acquires environmental information and incorporates it into the exercise plan. In this step, environmental conditions such as local temperature and humidity are collected based on geographical location information using weather APIs, etc. This makes the exercise plan more personalized. 【0762】 Step 4: 【0763】 The device receives an optimized exercise plan from the server and feedback based on environmental information. It provides real-time advice to the exerciser as voice instructions and text messages. Specifically, it suggests concrete actions such as "slow down" or "take a break for a certain period of time." 【0764】 Step 5: 【0765】 The user acts on the feedback received from the device. Following the instructions provided by the device during exercise improves safety and performance. At this stage, the interaction between the server and the device is complete, and real-time support continues until the exercise session ends. 【0766】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0767】 This invention is an exercise support system that combines an emotion engine that recognizes the user's emotions, thereby providing comprehensive support tailored to each individual exerciser. The following describes a typical embodiment for carrying out this invention. 【0768】 Data acquisition 【0769】 Terminal: To understand the user's condition during exercise, wearable devices and communication terminals collect biometric and environmental data. This includes heart rate, exercise data, and audio / video data from the terminal's camera and microphone. 【0770】 emotion recognition 【0771】 Server: Using audio and video data transmitted from the terminal, the emotion engine recognizes emotions from the user's facial expressions and tone of voice. This analysis identifies the user's emotional state. 【0772】 Data analysis and adjustment of exercise plan 【0773】 Server: The server analyzes collected exercise and emotional data using AI algorithms to generate or adjust an exercise plan optimized for the user. If emotional data detects, for example, fatigue or stress, the exercise intensity is adjusted accordingly. 【0774】 Real-time feedback 【0775】 Device: The device provides feedback to the user according to the exercise plan, including messages tailored to the user's emotional state. For example, if the user is feeling stressed, it might advise, "Relax and take slow, deep breaths." 【0776】 Dialogue 【0777】 Server: Provides appropriate answers to questions from participants using natural language processing techniques. This includes responses that take into account the user's current emotional state. 【0778】 Specific example 【0779】 User: A user is training using a fitness app. This user is trying a new exercise plan and feels a little anxious shortly after starting. 【0780】 The device's camera and microphone detect the anxiety and send it to the server. 【0781】 Server: The emotion engine detects anxiety and adjusts the difficulty level of the exercise plan. Based on this, the device provides voice advice such as, "Start slowly, and increase the pace as you get used to it." 【0782】 User: This feedback gives me the confidence to continue exercising. 【0783】 This invention aims to provide an optimal exercise experience by taking into account not only the user's physical characteristics but also their emotional characteristics. 【0784】 The following describes the processing flow. 【0785】 Step 1: 【0786】 The device activates the wearable device and communication terminal when the user prepares to start exercising, and simultaneously collects biometric data (heart rate, movement data, etc.) and audio / video data. 【0787】 Step 2: 【0788】 The device transmits collected biometric data and audio / video data to the server. This data is transferred in real time via a secure connection. 【0789】 Step 3: 【0790】 The server inputs audio and video data into the emotion engine to analyze the user's emotional state. The engine detects the user's emotions from their facial expressions and tone of voice, identifying states such as anxiety, stress, and concentration. 【0791】 Step 4: 【0792】 The server uses biometric data and emotional state to evaluate the user's exercise performance with an AI algorithm. Based on this evaluation, it makes appropriate adjustments to the exercise plan. For example, if emotional data indicates the user is fatigued, the plan is adjusted to reduce the exercise load. 【0793】 Step 5: 【0794】 The device provides feedback to the user based on the adjusted exercise plan. This feedback is delivered verbally, for example, "You don't seem to be feeling well. How about slowing down a bit?" 【0795】 Step 6: 【0796】 The server generates natural responses to user questions and requests, taking into account their emotional state, and delivers them through the terminal. For example, the response might suggest, "Taking a short break might help you relax." 【0797】 Step 7: 【0798】 When a user finishes their workout, the device sends all the process data to a server, and the server displays comprehensive feedback to the user. This feedback includes a summary of the workout and areas for improvement. 【0799】 (Example 2) 【0800】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0801】 Conventional exercise support systems provide exercise plans based solely on the exerciser's physical data, failing to consider emotional states and thus unable to provide optimal support for individual users. Furthermore, the low accuracy of feedback and dialogue leaves challenges in maintaining user motivation and improving the effectiveness of exercise. 【0802】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0803】 In this invention, the server includes data acquisition means for understanding the user's state by collecting individual exerciser's heart rate, activity level, and environmental information; emotion recognition means for identifying emotions from acquired audio and video; and analysis means for generating or adjusting an optimized exercise plan by analyzing exerciser data and emotion data. This enables optimal exercise support that takes into account the user's emotional state. 【0804】 "Data acquisition means" refers to a device or process for collecting information on the exerciser's heart rate, activity level, and environmental information in order to understand the user's condition. 【0805】 "Emotion recognition means" refers to a system or method for identifying a user's emotions based on acquired audio and video data. 【0806】 "Analysis means" refers to a device or process that has the function of analyzing exercise data and emotional data to generate or adjust an optimized exercise plan. 【0807】 A "feedback provision method" is a system for providing real-time feedback to users based on their exercise plan. 【0808】 A "dialogue method" is a system that engages in dialogue with the participant and provides advice and answers to questions using natural language processing technology. 【0809】 A "wearable device" is a device that a user can wear to collect physical and environmental information. 【0810】 A "communication device" is a device or group of devices used to collect data and transmit it to a server. 【0811】 An "artificial intelligence algorithm" is a computational method used to analyze and process data and make decisions based on a specific purpose. 【0812】 A "generated AI model" is a model that uses patterns learned from data to perform analysis and predictions based on new data. 【0813】 This system aims to continuously and dynamically collect individual information about athletes and, based on that information, provide them with optimal feedback in real time. A specific embodiment of the invention is configured as follows: 【0814】 Hardware and data acquisition 【0815】 The devices utilize wearable devices such as smartwatches and fitness trackers to acquire biometric information such as the exerciser's heart rate and activity level in real time. They also collect audio and video data via communication devices such as smartphones and tablets to understand the environment. These devices transmit data to the server using Bluetooth or Wi-Fi. 【0816】 Emotion recognition and data analysis 【0817】 The server performs emotion recognition based on the received audio and video data. The emotion engine used here incorporates machine learning algorithms that can identify emotions from the user's facial expressions and tone of voice. The server further analyzes all of the exerciser's data and uses the generated AI model to optimize and adjust the system according to the exerciser. 【0818】 Feedback and dialogue 【0819】 The device provides real-time feedback to the user. It notifies the user of exercise guidance and advice via voice or text, taking into account the user's emotional state. The server also utilizes natural language processing technology to provide appropriate answers to questions from the exerciser. 【0820】 Specific example 【0821】 If a user is experiencing anxiety while trying a new exercise program, the smartphone's camera and microphone detect this anxiety. The data is sent to a server where an emotion recognition engine analyzes the anxiety and adjusts the exercise plan. As a result, the device provides a message such as, "Start slowly, and increase the pace as you get used to it." 【0822】 Example of a prompt 【0823】 "Analyze the user's biometric and emotional data collected in real time and suggest how to adjust the exercise intensity." 【0824】 In this way, the present invention provides an optimal exercise experience that comprehensively considers the physical and emotional elements of the exerciser. 【0825】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0826】 Step 1: 【0827】 The terminal acquires biometric information such as the exerciser's heart rate and activity level in real time from a wearable device. It also collects the user's voice and video data using a communication device. This data, obtained as input, is immediately transmitted to the server. The output provides information on the exerciser's physical condition and environment. This data collection process forms the basis for understanding the user's daily fluctuations. 【0828】 Step 2: 【0829】 The server inputs audio and video data sent from the terminal into an emotion recognition engine. This allows the engine to identify the user's emotions from their facial expressions and tone of voice, and output a specific emotional state. This data processing enables analysis of the user's current psychological state. 【0830】 Step 3: 【0831】 The server inputs exercise and emotional data into an AI algorithm for analysis. It then generates or adjusts an exercise plan optimized for the user. As a result of this process, a new exercise plan is obtained as output. Specifically, the data calculation involves pattern recognition of past data to dynamically determine the most effective exercise intensity and content. 【0832】 Step 4: 【0833】 The device provides real-time feedback tailored to the user based on the generated exercise plan. This feedback includes advice that aligns with the user's emotional state. For example, a message such as "Let's slow down a bit today" might be presented via voice or text. Based on the exercise plan received as input, specific exercise instructions are output. 【0834】 Step 5: 【0835】 The server inputs questions from users into natural language processing technology and generates appropriate responses. These responses are output considering information retrieved from the database and the user's emotional state. Specifically, it analyzes the intent of the user's question and extracts and provides the best possible answer. In this way, a system that can respond to user inquiries immediately is realized. 【0836】 (Application Example 2) 【0837】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0838】 This invention aims to improve the exercise experience by considering not only the physical health but also the emotional health of the exerciser and providing an optimized exercise plan tailored to each individual exerciser. Furthermore, it aims to automate exercise adjustment based on emotion recognition, which was lacking in conventional exercise support systems, and to improve the accuracy of the feedback provided as a result. 【0839】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0840】 In this invention, the server includes data acquisition means for collecting individual exercise data, emotion recognition means for recognizing the emotional state of the exerciser, and analysis means for generating an optimized exercise plan for the exerciser. This enables real-time exercise adjustment and feedback provision based on the emotional state of the exerciser. 【0841】 "Individual exerciser data" refers to information that includes unique physical and physiological parameters for each exerciser, and is used to optimize exercise. 【0842】 "Emotion recognition means" refers to a component of a system that has the function of identifying an emotion based on the facial expression, tone of voice, and other cues of the person performing the action. 【0843】 An "analysis device" is a device that processes collected data and executes an algorithm to generate an optimized exercise plan for the exerciser. 【0844】 "Exercise plan adjustment means" refers to a device or program for appropriately modifying an existing exercise plan according to the emotional state of the person exercising. 【0845】 A "feedback provisioning device" is a device that has the function of transmitting advice and information to the exerciser in real time based on the generated exercise plan. 【0846】 A "means of dialogue" is an interface that provides advice and answers questions through communication with activists. 【0847】 A "portable device" is a device that can be worn on the body or carried around and collects exercise data or biometric data. 【0848】 A "machine learning algorithm" is a form of artificial intelligence technology used to analyze collected data and identify areas for improvement in a person's movements. 【0849】 The system for carrying out the present invention includes a series of components for monitoring and analyzing the user's physical and emotional state in real time and providing optimal exercise support. 【0850】 At the heart of the system is a server, which is responsible for receiving and analyzing vast amounts of data. Wearable devices and communication terminals collect heart rate and movement data while the user is wearing them. This data is supplemented by emotion recognition mechanisms, which identify the user's emotions from their facial expressions and voice. 【0851】 The server uses analysis tools based on this data to generate a user's exercise plan. A machine learning algorithm takes into account the user's movements and emotional state to construct the optimal exercise pattern in real time. Furthermore, an exercise plan adjustment tool dynamically modifies the plan based on the emotional state. 【0852】 While the user is exercising, feedback and interaction tools provide immediate advice based on a tailored exercise plan. For example, if the user feels stressed, the device sends a message encouraging relaxation. 【0853】 For example, when a user tries a new exercise program, if the emotion recognition function detects anxiety, the server adjusts the exercise intensity and provides feedback such as, "Start slowly, and increase the pace once you get used to it." 【0854】 Using a generative AI model, you can use prompts like the following: 【0855】 "What are some ideas for the support and feedback the system should provide when a user starts a new exercise routine for the first time? Please consider situations where the user might be feeling anxious." 【0856】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0857】 Step 1: 【0858】 The device collects heart rate and motion data from wearable devices, and audio and video data from communication devices. This data includes the user's exercise and emotional state. The device transmits the collected biometric data to a server. 【0859】 Step 2: 【0860】 The server receives data sent from the terminal and analyzes the user's emotional state using emotion recognition technology. The input audio and video data is processed by an analysis engine, identifying emotions from the user's facial expressions and tone of voice. The output is information about the user's emotional state. 【0861】 Step 3: 【0862】 The server uses analysis tools to generate an optimized exercise plan based on exercise and emotional data. The collected exercise data is processed using machine learning algorithms to generate exercise patterns suitable for the user. The output is the optimized exercise plan. 【0863】 Step 4: 【0864】 The server modifies the exercise plan based on the user's emotional state using an exercise plan adjustment mechanism. It detects the user's stress and fatigue levels from emotional data and adjusts the exercise intensity and content accordingly. The output is the adjusted exercise plan. 【0865】 Step 5: 【0866】 The device utilizes feedback mechanisms to provide the user with real-time feedback based on a customized exercise plan. For example, the device might send a voice message such as, "Relax and take slow, deep breaths." The output is a feedback message to the user. 【0867】 Step 6: 【0868】 The user inputs questions or concerns during exercise into a terminal using a dialogue mechanism. The terminal sends this information to a server. The server utilizes a generative AI model to provide appropriate responses that take into account the user's emotional state. The output is the response information for the user. 【0869】 The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0870】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0871】 In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0872】 Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion. 【0873】 Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together. 【0874】 These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression. 【0875】 The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become. 【0876】 Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant. 【0877】 The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more." 【0878】 The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values. 【0879】 The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format. 【0880】 In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data. 【0881】 In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56. 【0882】 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. 【0883】 Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56. 【0884】 The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory. 【0885】 The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor. 【0886】 Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources. 【0887】 Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose. 【0888】 The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above. 【0889】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference. 【0890】 The following is further disclosed regarding the embodiments described above. 【0891】 (Claim 1) 【0892】 A data acquisition method for collecting individual athlete data, 【0893】 Analysis means for analyzing the aforementioned exerciser data and generating an optimized exercise plan for the exerciser, 【0894】 A feedback provision means that provides real-time feedback to the exerciser based on the aforementioned exercise plan, 【0895】 A means of dialogue with the aforementioned exerciser, providing advice and answers to questions during exercise, 【0896】 A system that includes this. 【0897】 (Claim 2) 【0898】 The system according to claim 1, wherein the data acquisition means collects data from a wearable device and a communication terminal. 【0899】 (Claim 3) 【0900】 The system according to claim 1, wherein the analysis means uses an artificial intelligence algorithm to identify areas for improvement in the movement of the person performing the exercise. 【0901】 "Example 1" 【0902】 (Claim 1) 【0903】 Information acquisition means for collecting individual participant information, 【0904】 Analysis means for analyzing the aforementioned exerciser information and generating an optimized exercise plan for the exerciser, 【0905】 A notification means that provides real-time feedback to the exerciser based on the aforementioned exercise plan, 【0906】 A means of responding to the aforementioned exerciser, providing advice and answers to questions during exercise, 【0907】 A generation means that uses a generative AI model to provide feedback and advice to the user in natural language, 【0908】 A system that includes this. 【0909】 (Claim 2) 【0910】 The system according to claim 1, wherein the information acquisition means collects information from a wearable device and a communication device. 【0911】 (Claim 3) 【0912】 The system according to claim 1, wherein the analysis means uses a machine learning algorithm to identify areas for improvement in the exerciser's movements. 【0913】 "Application Example 1" 【0914】 (Claim 1) 【0915】 A data acquisition method for collecting individual athlete data, 【0916】 Analysis means for analyzing the aforementioned exerciser data and generating an optimized exercise plan for the exerciser, 【0917】 A feedback provision means that provides real-time feedback to the exerciser based on the aforementioned exercise plan, 【0918】 A means of dialogue with the aforementioned exerciser, providing advice and answers to questions during exercise, 【0919】 An environmental analysis means that generates additional advice for athletes based on weather conditions, 【0920】 A system that includes this. 【0921】 (Claim 2) 【0922】 The system according to claim 1, wherein the data acquisition means uses information collected from a wearable device and a communication terminal. 【0923】 (Claim 3) 【0924】 The system according to claim 1, wherein the analysis means uses an artificial intelligence algorithm capable of dynamically adjusting the exercise plan according to the physical condition and environment of the person exercising. 【0925】 "Example 2 of combining an emotion engine" 【0926】 (Claim 1) 【0927】 A data acquisition means for understanding the user's condition by collecting individual exerciser's heart rate, activity level, and environmental information, 【0928】 An emotion recognition means for identifying emotions from acquired audio and video, 【0929】 An analysis means for generating or adjusting an optimized exercise plan by analyzing exerciser data and emotional data, 【0930】 A feedback provision means that provides real-time feedback according to the user's emotional state based on the aforementioned exercise plan, 【0931】 A dialogue means that engages in conversation with activists and provides advice and answers to questions using natural language processing technology, 【0932】 A system that includes this. 【0933】 (Claim 2) 【0934】 The system according to claim 1, characterized in that the data acquisition means collects data from a wearable device and a communication device. 【0935】 (Claim 3) 【0936】 The system according to claim 1, characterized in that the analysis means identifies areas for improvement in the movement of the athlete using the generated AI model. 【0937】 "Application example 2 when combining with an emotional engine" 【0938】 (Claim 1) 【0939】 A data acquisition method for collecting individual athlete data, 【0940】 Analysis means for analyzing the aforementioned exerciser data and generating an optimized exercise plan for the exerciser, 【0941】 An exercise plan adjustment means for adjusting the optimized exercise plan based on the emotional state of the exerciser, 【0942】 An emotion recognition means for recognizing the emotional state of an athlete, 【0943】 A feedback provision means that provides real-time feedback to the exerciser based on the aforementioned exercise plan, 【0944】 A means of dialogue with the aforementioned exerciser, providing advice and answers to questions during exercise, 【0945】 A system that includes this. 【0946】 (Claim 2) 【0947】 The system according to claim 1, wherein the data acquisition means collects data from a portable device and a communication device. 【0948】 (Claim 3) 【0949】 The system according to claim 1, wherein the analysis means uses a machine learning algorithm to identify areas for improvement in the exerciser's movements. [Explanation of Symbols] 【0950】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] A data acquisition method for collecting individual athlete data, Analysis means for analyzing the aforementioned exerciser data and generating an optimized exercise plan for the exerciser, A feedback provision means that provides real-time feedback to the exerciser based on the aforementioned exercise plan, A means of dialogue with the aforementioned exerciser, providing advice and answers to questions during exercise, A system that includes this. [Claim 2] The system according to claim 1, wherein the data acquisition means collects data from a wearable device and a communication terminal. [Claim 3] The system according to claim 1, wherein the analysis means uses an artificial intelligence algorithm to identify areas for improvement in the movement of the person performing the exercise.

Images