system

Abstract

Provide a system. 【Solution means】 Means for acquiring biological data using a wearable biosensor, Means for analyzing the acquired biological data in real time and detecting abnormalities, Means for providing appropriate instructions to the user in multiple languages based on the analysis results, Means for generating an activity plan according to the user's health condition and proposing a comfortable environment, Means for using virtual reality technology to visually provide the generated activity plan to the user, Means for anonymizing the accumulated information and sharing it with international academic research institutions, Means for transmitting information to the nearest medical institution in response to the detection of an abnormality in the user's health condition, A system including the above.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] The problem to be solved by the present invention is to improve medical access for international travelers and foreign residents and provide individualized tourism experiences. Specifically, it lies in achieving a balance between medical care and tourism by overcoming language and cultural barriers, providing accurate real-time health monitoring and multilingual support, and further proposing a tourism plan according to the user's health condition.

Means for Solving the Problems

[0005] This invention provides a means for acquiring biometric information using a wearable biosensor and analyzing this information in real time. Based on the analysis results, it provides appropriate instructions to the user in multiple languages ​​and generates a tourism plan optimized for the user's health condition using reinforcement learning. It also includes a means for providing the user with the tourism plan generated using visual technology. Furthermore, by anonymizing the accumulated data and sharing it with international research institutions, it contributes to global medical research.

[0006] A "wearable biosensor" is a small measuring device that can be attached to the human body to continuously acquire biometric information such as heart rate and body temperature.

[0007] "Real-time analysis" is the process of processing collected data immediately and making the results available quickly.

[0008] "Anomaly detection" is an algorithmic process that identifies data that deviates from the normal range and detects problems early.

[0009] "Multilingual provision" refers to assistive technology that transmits information and instructions in multiple languages, allowing users to obtain information in their native language.

[0010] "Tourism plan generation" is the process of creating suggestions for destinations and activities based on the user's preferences and health status.

[0011] "Reinforcement learning" is a part of artificial intelligence, a technique for learning optimal actions and decisions through trial and error.

[0012] "Visual presentation" refers to a method of presenting information or plans to users in an easily understandable format by using graphics and videos to visualize them.

[0013] "Anonymization" is a technique that protects privacy by processing data in a way that makes it impossible to identify individuals.

[0014] An "international research institution" is an organization established across national borders, conducting scientific and medical research with the participation of researchers from various countries. [Brief explanation of the drawing]

[0015] [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]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a 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.

[0019] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] 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."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] This invention combines wearable devices and AI technology to create a system that allows people to self-manage their health even in new environments they encounter. The following describes specific embodiments of the invention.

[0037] First, the user wears a wearable biosensor to collect biometric data such as body temperature and heart rate in real time. This sensor transmits the data to the device via Bluetooth or Wi-Fi.

[0038] The device utilizes an AI model to analyze the received data. This allows it to learn normal health patterns from the data and detect abnormalities when they occur. When an abnormality is detected, the device notifies the user in multiple languages ​​and provides specific instructions regarding their health status.

[0039] Next, the device generates a sightseeing plan based on the user's health status. This uses reinforcement learning technology to consider the user's preferences and environmental conditions, suggesting optimal activities and tourist destinations. These suggestions are presented visually using AR and VR technologies. For example, if the user has a high body temperature, a cool art museum might be recommended, and visual technology allows the user to preview the museum's interior beforehand.

[0040] Furthermore, this system is linked to a server, and data is securely stored in the cloud. The stored data is anonymized to protect personal information and then shared with international research institutions. This sharing supports the expansion of global knowledge and technological advancement in the medical field.

[0041] By integrating the above functions, this invention provides an environment where users can safely enjoy both medical care and tourism simultaneously without feeling any language or cultural barriers.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The user wears a wearable biosensor to continuously measure data such as body temperature and heart rate. The wearable device transmits the measured data to the terminal.

[0045] Step 2:

[0046] The device activates an AI algorithm to analyze the received biometric data. This algorithm has the ability to compare historical data with real-time data and detect anomalies.

[0047] Step 3:

[0048] When an anomaly is detected, the device sends an alert to the user. This alert includes health recommendations and countermeasures in multiple languages.

[0049] Step 4:

[0050] The device creates a sightseeing plan based on the user's health status. It utilizes a reinforcement learning model to generate a customized plan that takes into account the user's budget, time, and health condition.

[0051] Step 5:

[0052] The device displays the generated sightseeing plan to the user using AR / VR technology. This allows the user to visually confirm a preview of the places they will visit and the activities they will engage in.

[0053] Step 6:

[0054] Data is sent from the device to the server. The server anonymizes the biometric data and stores it securely.

[0055] Step 7:

[0056] The server shares accumulated data with international research institutions via federated learning technology. This process supports the advancement of medical research.

[0057] (Example 1)

[0058] 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."

[0059] In modern society, users find it difficult to effectively manage their health in different environments, and there is a need for ways to reduce health risks and stay safe and healthy, especially when traveling or visiting new places. Furthermore, providing individually optimized travel plans based on health conditions is challenging, necessitating a system that is intuitive and reassuring for users. Additionally, building a system that utilizes collected data more broadly and effectively to contribute to the advancement of international medical research is another challenge.

[0060] 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.

[0061] In this invention, the server includes means for acquiring biometric data using a wearable information collection device, means for processing the acquired biometric data immediately and identifying abnormalities, and means for providing appropriate instructions to the user in multiple languages ​​based on the processing results. This allows the user to understand their health status in real time and take appropriate countermeasures quickly in the event of an abnormality. Furthermore, by optimizing the movement plan using a generative AI model, it is possible to provide a personalized movement plan tailored to the user's preferences and health status, and intuitive information can be provided through visual means. This realizes a safe, healthy, and highly satisfying experience.

[0062] A "wearable information collection device" is an electronic device that is worn on the body to continuously monitor and acquire the user's biometric data.

[0063] "Biometric data" refers to numerical information that indicates the user's physical condition, such as body temperature, heart rate, and blood pressure.

[0064] "Immediate processing" refers to a process where biometric data is analyzed immediately after being received, and results are obtained quickly.

[0065] "Identifying anomalies" means detecting values ​​that deviate from normal data patterns or sudden changes.

[0066] "Providing appropriate instructions in multiple languages" means presenting necessary actions in multiple languages ​​so that they can be understood regardless of the user's language.

[0067] A "travel plan" is a schedule of destinations and activities suggested to the user based on their health condition and preferences.

[0068] A "generative AI model" is an artificial intelligence algorithm that learns from large amounts of data and enables data analysis and prediction.

[0069] "Visual presentation" refers to a method that allows users to directly understand information through videos and images.

[0070] "Anonymization" is the process of removing personal information from data so that individuals cannot be identified.

[0071] An "international research institution" is an organization that conducts medical and technological research across multiple countries.

[0072] "Learning technology" refers to techniques that use data to improve models and automatically enhance their performance.

[0073] This invention is a system that combines a wearable information collection device with artificial intelligence technology to support the user's health management while providing an optimal travel plan.

[0074] First, the user wears a wearable data collection device. This device acquires biometric data such as body temperature and heart rate in real time and continuously monitors the data. The collected data is transmitted to a device such as a smartphone or tablet via Bluetooth or Wi-Fi. This data acquisition allows the user to easily monitor their own health status.

[0075] The device utilizes a generative AI model to analyze the received biometric data. This AI model is based on frameworks such as TENSORFLOW® and PyTorch, built using Python, and processes the acquired data in real time. This allows it to learn normal health patterns and identify abnormalities when they are detected. For example, it can detect an anomaly when the heart rate deviates from the normal range and take appropriate action.

[0076] If an abnormality is detected, the device employs a method to provide instructions to the user in multiple languages. Specifically, action instructions such as "Stop exercising and take a break" are given in a language the user understands. This allows users to receive health guidance even without language barriers.

[0077] Furthermore, the device uses reinforcement learning technology to generate an optimal travel plan based on the user's health status and preferences. This plan includes potential destinations and activities, which are presented visually using AR and VR technologies. For example, if the user is not feeling well, health-conscious destinations such as indoor art museums or museums will be suggested. Visual technologies such as GOOGLE CARDBOARD® allow users to preview the interior of the museum beforehand.

[0078] Furthermore, the collected biometric data and analysis results are securely stored in the cloud via servers. The cloud service accumulates anonymized data, which is then shared with international research institutions, contributing to the advancement of global medical research.

[0079] This system, utilizing a generative AI model, allows users to confidently manage their health and create plans in their new environment. An example of a prompt would be, "Tell me some recommended nearby tourist spots." This enables the system to efficiently provide information tailored to the user's needs.

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] The user wears a wearable data collection device. This device acquires biometric data such as body temperature and heart rate in real time as part of the user's physical information. The input is the user's biosignals, and the output is formalized biometric data transmitted to a terminal via Bluetooth or Wi-Fi. This device continuously monitors the data using sensors and collects necessary physiological data.

[0083] Step 2:

[0084] The device sends the received biometric data to an AI model for immediate processing. The input is biometric data acquired from a wearable device, which the AI ​​model analyzes and compares to normal health patterns. The output is the identification result of whether or not an anomaly exists. The AI ​​model is built using TensorFlow and PyTorch and identifies anomalies in the data in real time.

[0085] Step 3:

[0086] When an anomaly is detected, the device sends instructions to the user in multiple languages. The input is the analysis result indicating the anomaly, and the output is an instruction message to the user. Specifically, the user is given instructions in a language they understand, such as "Stop exercising." This allows the user to take appropriate action immediately.

[0087] Step 4:

[0088] The device further utilizes a generative AI model to create travel plans tailored to the user's health status and preferences. Inputs are user preference data and current health status, while output is an optimized travel schedule and destination list. Reinforcement learning techniques are used to optimize the plan, which is then presented to the user visually through AR or VR technology. This plan makes it easier for the user to choose health-conscious activities.

[0089] Step 5:

[0090] The generated data and analysis results are stored in the cloud by the server. The input is the original biometric data and its analysis results, and the output is an anonymized dataset on the cloud. This allows for the sharing of information with international research institutions while protecting personal information, contributing to the advancement of medical research. Cloud services such as AWS® may be used in this process.

[0091] (Application Example 1)

[0092] 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."

[0093] The objective of this invention is to enable citizens residing in smart cities to efficiently monitor their daily health status, detect abnormalities early, and take appropriate action. Furthermore, it aims to allow users to continue their daily lives and sports activities with peace of mind, even when experiencing health problems, without causing them stress. In addition, we hope to contribute to improving the quality of life for users by proposing activities and environments tailored to their health status.

[0094] 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.

[0095] In this invention, the server includes means for acquiring biometric data using a wearable biosensor, means for analyzing the biometric data in real time and detecting abnormalities, and means for transmitting information to the nearest medical institution based on the analysis results. This enables timely management of the user's health status and allows for prompt and appropriate medical response when an abnormality is detected.

[0096] A "wearable biosensor" is a small electronic device worn by an individual to collect biometric data in real time.

[0097] "Biometric data" refers to physiological information that indicates an individual's health status, such as body temperature and heart rate.

[0098] "Real-time analysis" is a technology that processes acquired data immediately and generates results quickly.

[0099] Anomaly detection is the process of identifying data that deviates from normal health patterns.

[0100] "Multilingual instructions" is a function that provides instructions derived from analysis results in different languages ​​that the user can understand.

[0101] An "activity plan" is a plan that includes daily activities and places to visit, tailored to the user's health condition and preferences.

[0102] "Virtual reality technology" is a technology that uses digital imaging technology to simulate experiences that are the same as those in the real world.

[0103] "Anonymization" is a technique that protects privacy by processing data in a way that makes it impossible to identify individuals.

[0104] An "academic research institution" is an organization whose purpose is to conduct scientific investigations and research and to create new knowledge.

[0105] "Nearest medical institution" refers to the facility that provides medical services geographically closest to the target user.

[0106] The system for implementing the present invention consists of a wearable biosensor, a terminal device such as a smartphone or tablet, and a server connected to the cloud. The user wears the wearable biosensor and acquires biometric data such as body temperature and heart rate. This wearable device transmits the acquired data to the terminal device via Bluetooth or Wi-Fi.

[0107] The terminal device is equipped with software that implements a generative AI model, allowing for real-time analysis of biometric data. This analysis learns normal health patterns, and the device has a function to notify the user if an abnormality is detected. Furthermore, it periodically sends health data to the nearest medical institution, enabling prompt medical intervention as needed.

[0108] Furthermore, the server uses reinforcement learning techniques to generate activity plans based on the user's preferences and health status. This plan is then presented to the user visually using virtual reality technology. Specifically, a user with a fever can be suggested a cool museum or park, and detailed information about it can be virtually guided through the site.

[0109] To ensure data security, the server anonymizes the accumulated biometric data and shares it with international academic research institutions. This allows for contributions to medical research while protecting the privacy of individual users.

[0110] As a concrete example, when a traveler visiting a smart city wears a wearable device and experiences health problems, the application detects the abnormality and provides a notification prompting them to visit a medical facility immediately. It also provides activity suggestions based on the user's health status using a generative AI model. An example of a prompt message is, "Detect health abnormalities based on data from the wearable device and generate appropriate action suggestions within the smart city."

[0111] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0112] Step 1:

[0113] The user wears a wearable biosensor to acquire biometric data such as body temperature and heart rate. This sensor transmits this data to a device via Bluetooth or Wi-Fi. The input data is biometric information, and the output is the transmitted biometric data. Data transmission is performed by the communication module on the sensor side.

[0114] Step 2:

[0115] The device inputs received biometric data into a generating AI model for real-time analysis. Through this analysis, it learns normal health patterns and has the ability to detect abnormalities. The input is the received biometric data, and the output indicates whether or not an abnormality is present. Data processing is performed using neural network analysis.

[0116] Step 3:

[0117] Based on the analysis results, the terminal immediately notifies the user if an anomaly is detected. During this process, multilingual notification messages are generated and displayed to the user. The input is the result of the anomaly detection, and the output is the notification to the user. Natural language processing is used to generate the messages.

[0118] Step 4:

[0119] The server generates an activity plan using reinforcement learning techniques based on the user's health status and preferences. The generated plan includes actions and destinations tailored to the user's health condition. The input is the user's health status and preference data, and the output is the generated activity plan. A reinforcement learning algorithm is used for plan generation.

[0120] Step 5:

[0121] The server provides the user with the generated activity plan using virtual reality technology. Specifically, it offers virtual tours of places the user will visit and route guidance. The input is the activity plan, and the output is the experience information from the virtual reality. A VR application is used to present the virtual reality.

[0122] Step 6:

[0123] The server anonymizes the accumulated biometric data and securely shares it with international academic research institutions. This step involves data anonymization and secure transmission. The input is biometric data, and the output is anonymized research data. Data de-identification techniques and encryption protocols are used for implementation.

[0124] 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.

[0125] This invention is a system that analyzes a user's biometric information and emotional state in combination, and provides personalized medical and tourism experiences based on that analysis. The specific configuration and operation are as follows.

[0126] First, the user wears a wearable biosensor to collect biometric data such as body temperature and heart rate. Simultaneously, an emotion engine analyzes the user's emotional state from their facial expressions and voice. This makes it possible to monitor both physical health and emotional state.

[0127] The device analyzes collected biometric and emotional data. An AI algorithm is used to learn the user's normal health and emotional patterns from the data, enabling real-time anomaly detection and response to emotional changes.

[0128] Subsequently, the device provides multilingual instructions that take into account the user's health and emotional state. For example, if the user is feeling stressed, it will generate instructions recommending relaxing tourist destinations. This process includes a function to dynamically update the instructions in response to changes in the user's emotions.

[0129] In addition, the device uses a reinforcement learning model to create a travel plan tailored to the user's health and emotional state. This plan reflects the results of the user's emotional analysis to provide the optimal travel experience. For example, if the user is feeling happy, a plan including activities that further enhance that feeling will be presented.

[0130] Furthermore, the device uses AR / VR technology to visually provide users with details of the plan, allowing them to check planned tourist destinations and activities in advance. In cases of emotional instability, additional information may be provided to grab their attention.

[0131] Finally, the server securely stores the acquired data in the cloud, anonymizes it, and shares it with research institutions. This sharing facilitates international research on the relationship between emotions and health. It also contributes to improving the system's accuracy through continuous feedback.

[0132] In this way, the present invention realizes advanced and personalized medical and travel experiences that meet the needs of users.

[0133] The following describes the processing flow.

[0134] Step 1:

[0135] The user wears a wearable biosensor to measure biometric information such as body temperature and heart rate. Simultaneously, a device with a built-in emotion engine collects emotional data from facial expressions and voice. The terminal receives this data.

[0136] Step 2:

[0137] The device analyzes received biometric and emotional data using an AI algorithm. This allows it to learn normal health conditions and emotional patterns, and detect abnormalities and emotional changes.

[0138] Step 3:

[0139] The device provides the user with appropriate instructions in multiple languages ​​based on detected anomalies and emotional states. Specifically, if the user is stressed, instructions suggesting a relaxing environment will be generated.

[0140] Step 4:

[0141] The device generates a sightseeing plan based on the user's health and emotional state. The reinforcement learning model considers the user's budget and preferences to select the most suitable activities.

[0142] Step 5:

[0143] The device visually displays the generated sightseeing plan to the user using AR / VR technology. This allows the user to check the details of the suggested sightseeing destinations and activities in advance.

[0144] Step 6:

[0145] The device monitors the user's emotional state in real time and dynamically adjusts the sightseeing plan as needed. For example, if the user becomes excited, it might consider adding an active activity to the plan.

[0146] Step 7:

[0147] The server securely stores all data in the cloud, anonymizes it, and shares it with international research institutions. This data sharing will advance research on the relationship between emotions and health.

[0148] (Example 2)

[0149] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0150] In recent years, there has been a growing need for personalized health management and lifestyle improvements, but existing systems struggle to provide individualized medical guidance and travel experiences for each user. Furthermore, there is a demand for more accurate health management and personalized recommendations through integrated analysis of biometric information and emotional states. Additionally, securely sharing collected personal data and utilizing it for international research remains a challenge.

[0151] 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.

[0152] In this invention, the server includes means for acquiring physiological information and emotional state using an information gathering device, means for analyzing the acquired information and detecting abnormalities, and means for providing the user with customized instructions in multiple languages ​​based on the analysis. This enables personalized health and behavioral suggestions.

[0153] An "information gathering device" is a device used to acquire a user's physiological information and emotional state, and includes wearable sensors, cameras, and microphones.

[0154] "Physiological information" refers to numerical data that indicates the user's physical condition, such as body temperature and heart rate.

[0155] "Emotional state" refers to the psychological state analyzed based on the user's facial expressions and voice analysis.

[0156] "Detecting anomalies" means identifying data that deviates from normal health conditions or emotional patterns.

[0157] "Customized instructions in multiple languages" means providing advice and instructions that are individually tailored in multiple languages ​​based on the user's health condition and emotions.

[0158] An "activity plan" is a suggestion of places to visit and activities to do, generated while taking into account the user's health and emotional state.

[0159] "Providing information using visual technology" means using technologies such as AR and VR to visually present information and experiences to users.

[0160] "Providing collected data anonymized" means processing the data in a way that prevents individuals from being identified and then securely sharing it with research institutions and other organizations.

[0161] "Reinforcement learning technology" is a machine learning method that finds the optimal strategy through trial and error and provides individually tailored plans based on the user's requirements and preferences.

[0162] This invention is a system that acquires and analyzes a user's physiological information and emotional state to provide personalized medical and lifestyle suggestions. The specific operation is as follows:

[0163] The user wears a wearable biosensor, which acts as an information gathering device, to acquire physiological information such as body temperature and heart rate. This biosensor continuously collects everyday data and transmits it to a terminal using wireless communication. At the same time, the user's facial expressions and voice are captured by a camera and microphone, and this data is used to analyze their emotional state.

[0164] The device analyzes collected physiological and emotional data in real time. Machine learning algorithms are used for the analysis, particularly to learn normal health and emotional patterns for anomaly detection. Based on the analysis results, a generative AI model is used to provide the user with customized instructions in multiple languages. These instructions appear as notifications on the user's smartphone, prompting specific actions for health improvement or behavioral suggestions. For example, if the analysis indicates the user is feeling fatigued, instructions such as "We recommend taking a walk in a park to refresh yourself" might be provided.

[0165] Furthermore, the device applies reinforcement learning technology to create an activity plan optimized for the user's state. This plan takes into account the user's preferences and emotional state and is presented to the user using visual technology. AR and VR technologies allow users to virtually experience visited locations and activities, and they can review the plan details before departure.

[0166] The server securely stores the collected and analyzed data in the cloud. During this process, the data is anonymized to protect individual privacy and shared with research institutions, contributing to the advancement of international research. Furthermore, feedback from the data can be used to improve the system's accuracy.

[0167] An example of a prompt sentence to input into a generative AI model would be, "Please suggest relaxing tourist destinations that are recommended when the user is feeling stressed."

[0168] This system analyzes the user's health and emotional state and provides multilingual instructions and personalized activity plans based on that analysis, thereby delivering a highly personalized experience to the user.

[0169] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0170] Step 1:

[0171] The user wears a wearable device to collect physiological data such as body temperature and heart rate. This data is transmitted wirelessly to a terminal. Physiological data is the input, and data transmission to the terminal is the output. The device records the data with a timestamp and periodically transfers it to the terminal.

[0172] Step 2:

[0173] The user acquires facial and audio data through their smartphone's camera and microphone. This activates an emotion engine that analyzes the user's emotional state. The input consists of facial and audio data, and the output is the analyzed emotional state. The emotion recognition algorithm extracts facial features and generates an emotion score.

[0174] Step 3:

[0175] The device integrates collected physiological and emotional information and analyzes the data using an AI algorithm. This process involves data preprocessing, including noise reduction, before the normalized data is input to the AI ​​module. The output provides anomaly detection results compared to the user's normal state. The AI ​​performs pattern recognition and provides evaluations that form the basis for real-time notifications.

[0176] Step 4:

[0177] Based on the analysis results, the device uses a generative AI model to create customized instructions for the user in multiple languages. The input is the analysis results, and the output is instructions displayed on the user's smartphone. This provides the user with an appropriate action plan tailored to their specific health and emotional state.

[0178] Step 5:

[0179] The device applies reinforcement learning techniques to create an optimized activity plan based on the user's preferences and emotional state. The input is user profile data and analysis results, and the output is a personalized activity plan. This allows the user to receive detailed recommendations for tourist destinations and activities.

[0180] Step 6:

[0181] The device utilizes AR / VR technology to provide a visualization of the generated activity plan. The activity plan is the input, and the visualized information is presented to the AR / VR device as output. Based on this information, the user can virtually experience the visited locations and make decisions.

[0182] Step 7:

[0183] The server stores all physiological information, emotional states, and analysis results in the cloud, anonymizing the data. All collected data is the input, and securely stored anonymized data is the output. The server shares this data with international research institutions to help with continuous system improvement.

[0184] (Application Example 2)

[0185] 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".

[0186] Conventional systems struggled to efficiently provide individualized support that considered users' health and emotional states, as well as offer concrete suggestions for daily life actions. Furthermore, the lack of real-time analysis of user data for anomaly detection and the ability to respond quickly to such anomalies posed challenges in maintaining users' health and improving their quality of life. Additionally, the security of data sharing for international research using such systems was insufficient.

[0187] 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.

[0188] In this invention, the server includes means for acquiring biometric information using a wearable sensor device, means for analyzing the acquired biometric information and emotional state in real time and detecting anomalies, means for providing the user with appropriate action suggestions in multiple languages ​​based on the analysis results, means for generating application plans according to the user's health and emotional state, means for providing the generated application plans to the user visually and allowing them to confirm them via a monitoring device, means for anonymizing the accumulated data and securely sharing it with international research facilities, and means for controlling a physical agent capable of performing optimal actions based on the user's biometric information and emotional state. This enables highly personalized support for daily life tailored to the user's health and emotional state.

[0189] A "wearable sensor device" is a device that is attached to a user's body to continuously measure and acquire their biometric information.

[0190] "Biometric information" refers to data that indicates the user's physical condition, such as body temperature, heart rate, and blood oxygen saturation.

[0191] "Emotional state" refers to the user's psychological condition and is information obtained by analyzing facial expressions, voice, and other factors.

[0192] "Real-time analysis" is a process that collects data, performs analysis immediately on the spot, and produces results.

[0193] "Anomaly detection" refers to identifying changes in health or emotions as phenomena that deviate from the standard state based on analyzed data.

[0194] "Action suggestions" refer to recommending activities and behaviors that are appropriate for the user's current health and emotional state.

[0195] "Providing information in multiple languages" refers to a method of translating and distributing information and instructions in multiple languages ​​for users with different native languages.

[0196] An "application plan" refers to specific plans and action proposals that are feasible in daily life, based on the user's situation.

[0197] "Providing information through visual means" refers to a method of presenting information to users visually using images and videos to aid their understanding.

[0198] A "monitor device" is a device that displays information to the user, enabling them to check and operate it.

[0199] "Anonymization" is a process that removes elements that can identify an individual from collected data, thereby protecting privacy.

[0200] An "international research facility" is an organization or institution that conducts research activities and utilizes data across multiple countries.

[0201] A "physical agent" is an artificial entity that controls specific devices or equipment to assist users in performing their actions.

[0202] The system for realizing this invention consists of three parties: a user, a terminal, and a server. The user wears a wearable sensor device to acquire biometric information such as body temperature and heart rate. This allows for continuous monitoring of the user's health status. Furthermore, an emotion recognition algorithm can be used to analyze the user's emotional state in real time from their facial expressions and voice.

[0203] The device analyzes collected biometric information and emotional states in real time using an AI algorithm, detecting deviations from normal states as abnormalities. This enables the generation of appropriate action suggestions based on the user's health and emotional state, and provides information in multiple languages. Suggestions could include, for example, playing music for relaxation or recommending exercises.

[0204] The server securely stores data transmitted from the terminal in the cloud and anonymizes the data. The anonymized data is shared with international research institutions and contributes to research exploring the relationship between emotional states and health. Furthermore, when generating user application plans, reinforcement learning algorithms can be used to provide suggestions optimized for individual preferences. The generated application plans are visually presented to the user through AR / VR technology to aid visual understanding.

[0205] For example, if a user feels stressed after work, the system might suggest playing relaxation music and plan a walking route for the next day. An example of a prompt might be, "Based on the user's biometric information and emotions, let's suggest the most suitable relaxation method. For example, what methods would you suggest if the user is tired?"

[0206] This will enable users to receive appropriate support based on their health and emotional state, thereby improving their quality of life.

[0207] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0208] Step 1:

[0209] The user wears a wearable sensor device. The sensor acquires biometric information such as body temperature and heart rate. The input is the user's physical data, and the output is the acquired biometric information. Based on this information, the sensor continuously collects the user's biometric data and transmits it to the terminal.

[0210] Step 2:

[0211] The device receives collected biometric information and voice input, and uses an emotion recognition algorithm to analyze the user's emotional state. The input is biometric information and voice data, and the output is the user's emotional state. In this process, voice and facial expression data are analyzed, and emotions are identified by AI.

[0212] Step 3:

[0213] The device uses an AI algorithm to analyze acquired biometric information and emotional state in real time, detecting deviations from a normal state as abnormalities. The output is a diagnostic result regarding the user's condition. In this step, data is compared to detect health abnormalities in the user.

[0214] Step 4:

[0215] The device generates appropriate action suggestions based on the analysis results and provides them to the user in multiple languages. The input is the diagnostic result, and the output is a guideline for action suggestions. Specifically, this includes playing relaxation music and providing action recommendations tailored to the user's physical condition.

[0216] Step 5:

[0217] The server receives data transmitted from the terminal in Kitami and stores it in secure cloud storage. The input is anonymized user data, and the output is securely stored data. In this step, the data is anonymized and made shareable with international research institutions.

[0218] Step 6:

[0219] The server uses a reinforcement learning algorithm to generate application plans optimized for the user's interests and preferences. The input consists of collected data and user history, and the output is a individually optimized plan. This process learns from past data and generates suggestions tailored to the user.

[0220] Step 7:

[0221] The generated application plan is visually presented to the user from the device using AR / VR technology. The input is an individually optimized plan, and the output is visual content. In this step, an environment is created in which the user can check the specific details in advance through the visualization of the plan.

[0222] 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.

[0223] Data generation model 58 is a type of 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.

[0224] 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.

[0225] [Second Embodiment]

[0226] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0227] 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.

[0228] 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).

[0229] 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.

[0230] 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.

[0231] 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).

[0232] 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.

[0233] 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.

[0234] 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.

[0235] 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.

[0236] 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.

[0237] 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".

[0238] This invention combines wearable devices and AI technology to create a system that allows people to self-manage their health even in new environments they encounter. The following describes specific embodiments of the invention.

[0239] First, the user wears a wearable biosensor to collect biometric data such as body temperature and heart rate in real time. This sensor transmits the data to the device via Bluetooth or Wi-Fi.

[0240] The device utilizes an AI model to analyze the received data. This allows it to learn normal health patterns from the data and detect abnormalities when they occur. When an abnormality is detected, the device notifies the user in multiple languages ​​and provides specific instructions regarding their health status.

[0241] Next, the device generates a sightseeing plan based on the user's health status. This uses reinforcement learning technology to consider the user's preferences and environmental conditions, suggesting optimal activities and tourist destinations. These suggestions are presented visually using AR and VR technologies. For example, if the user has a high body temperature, a cool art museum might be recommended, and visual technology allows the user to preview the museum's interior beforehand.

[0242] Furthermore, this system is linked to a server, and data is securely stored in the cloud. The stored data is anonymized to protect personal information and then shared with international research institutions. This sharing supports the expansion of global knowledge and technological advancement in the medical field.

[0243] By integrating the above functions, this invention provides an environment where users can safely enjoy both medical care and tourism simultaneously without feeling any language or cultural barriers.

[0244] The following describes the processing flow.

[0245] Step 1:

[0246] The user wears a wearable biosensor to continuously measure data such as body temperature and heart rate. The wearable device transmits the measured data to the terminal.

[0247] Step 2:

[0248] The device activates an AI algorithm to analyze the received biometric data. This algorithm has the ability to compare historical data with real-time data and detect anomalies.

[0249] Step 3:

[0250] When an anomaly is detected, the device sends an alert to the user. This alert includes health recommendations and countermeasures in multiple languages.

[0251] Step 4:

[0252] The device creates a sightseeing plan based on the user's health status. It utilizes a reinforcement learning model to generate a customized plan that takes into account the user's budget, time, and health condition.

[0253] Step 5:

[0254] The device displays the generated sightseeing plan to the user using AR / VR technology. This allows the user to visually confirm a preview of the places they will visit and the activities they will engage in.

[0255] Step 6:

[0256] Data is sent from the device to the server. The server anonymizes the biometric data and stores it securely.

[0257] Step 7:

[0258] The server shares accumulated data with international research institutions via federated learning technology. This process supports the advancement of medical research.

[0259] (Example 1)

[0260] 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."

[0261] In modern society, users find it difficult to effectively manage their health in different environments, and there is a need for ways to reduce health risks and stay safe and healthy, especially when traveling or visiting new places. Furthermore, providing individually optimized travel plans based on health conditions is challenging, necessitating a system that is intuitive and reassuring for users. Additionally, building a system that utilizes collected data more broadly and effectively to contribute to the advancement of international medical research is another challenge.

[0262] 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.

[0263] In this invention, the server includes means for acquiring biometric data using a wearable information collection device, means for processing the acquired biometric data immediately and identifying abnormalities, and means for providing appropriate instructions to the user in multiple languages ​​based on the processing results. This allows the user to understand their health status in real time and take appropriate countermeasures quickly in the event of an abnormality. Furthermore, by optimizing the movement plan using a generative AI model, it is possible to provide a personalized movement plan tailored to the user's preferences and health status, and intuitive information can be provided through visual means. This realizes a safe, healthy, and highly satisfying experience.

[0264] A "wearable information collection device" is an electronic device that is worn on the body to continuously monitor and acquire the user's biometric data.

[0265] "Biometric data" refers to numerical information that indicates the user's physical condition, such as body temperature, heart rate, and blood pressure.

[0266] "Immediate processing" refers to a process where biometric data is analyzed immediately after being received, and results are obtained quickly.

[0267] "Identifying anomalies" means detecting values ​​that deviate from normal data patterns or sudden changes.

[0268] "Providing appropriate instructions in multiple languages" means presenting necessary actions in multiple languages ​​so that they can be understood regardless of the user's language.

[0269] A "travel plan" is a schedule of destinations and activities suggested to the user based on their health condition and preferences.

[0270] A "generative AI model" is an artificial intelligence algorithm that learns from large amounts of data and enables data analysis and prediction.

[0271] "Visual presentation" refers to a method that allows users to directly understand information through videos and images.

[0272] "Anonymization" is the process of removing personal information from data so that individuals cannot be identified.

[0273] An "international research institution" is an organization that conducts medical and technological research across multiple countries.

[0274] "Learning technology" refers to techniques that use data to improve models and automatically enhance their performance.

[0275] This invention is a system that combines a wearable information collection device with artificial intelligence technology to support the user's health management while providing an optimal travel plan.

[0276] First, the user wears a wearable data collection device. This device acquires biometric data such as body temperature and heart rate in real time and continuously monitors the data. The collected data is transmitted to a device such as a smartphone or tablet via Bluetooth or Wi-Fi. This data acquisition allows the user to easily monitor their own health status.

[0277] The device utilizes a generative AI model to analyze the received biometric data. This AI model is based on frameworks such as TensorFlow and PyTorch, built using Python, and processes the acquired data in real time. This allows it to learn normal health patterns and identify abnormalities when they are detected. For example, it can detect an anomaly when the heart rate deviates from the normal range and take appropriate action.

[0278] If an abnormality is detected, the device employs a method to provide instructions to the user in multiple languages. Specifically, action instructions such as "Stop exercising and take a break" are given in a language the user understands. This allows users to receive health guidance even without language barriers.

[0279] Furthermore, the device uses reinforcement learning technology to generate an optimal travel plan based on the user's health status and preferences. This plan includes potential destinations and activities, which are presented visually using AR and VR technologies. For example, if the user is not feeling well, health-conscious destinations such as indoor art museums or museums will be suggested. Visual technologies such as Google® Cardboard allow users to preview the interior of the museum beforehand.

[0280] Furthermore, the collected biometric data and analysis results are securely stored in the cloud via servers. The cloud service accumulates anonymized data, which is then shared with international research institutions, contributing to the advancement of global medical research.

[0281] This system, utilizing a generative AI model, allows users to confidently manage their health and create plans in their new environment. An example of a prompt would be, "Tell me some recommended nearby tourist spots." This enables the system to efficiently provide information tailored to the user's needs.

[0282] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0283] Step 1:

[0284] The user wears a wearable information collection device. As the user's physical information, biometric data such as body temperature and heart rate are acquired in real time. The input is the user's biometric signal, and the output is the formatted biometric data transmitted to the terminal via Bluetooth or Wi-Fi. This device continuously monitors data using sensors and collects necessary physiological data.

[0285] Step 2:

[0286] The terminal transmits the received biometric data to the AI model for immediate processing. The input is the biometric data obtained from the wearable device, and the AI model analyzes this and compares it with the normal health pattern. The output is the identification result of whether there are abnormalities. The AI model is constructed using TensorFlow or PyTorch and identifies the abnormal locations of the data in real time.

[0287] Step 3:

[0288] When an abnormality is detected, the terminal sends instructions to the user in multiple languages. The input is the analysis result indicating the abnormality, and the output is the instruction message to the user. Specifically, an instruction such as "Let's stop exercising" is provided in a language that the user can understand. This enables the user to immediately take appropriate measures.

[0289] Step 4:

[0290] The terminal further utilizes the generative AI model to formulate a movement plan according to the user's health status and preferences. The input is the user's preference data and the current health status, and the output is an optimized movement schedule and a list of destinations. The plan is optimized using reinforcement learning techniques and visually provided to the user through AR or VR technologies. This plan makes it easier for the user to select activities considering their health.

[0291] Step 5:

[0292] The generated data and analysis results are stored in the cloud by the server. The input is the original biometric data and its analysis results, and the output is an anonymized dataset on the cloud. This allows for the sharing of information with international research institutions while protecting personal information, contributing to the advancement of medical research. Cloud services such as AWS may be used in this process.

[0293] (Application Example 1)

[0294] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0295] The objective of this invention is to enable citizens residing in smart cities to efficiently monitor their daily health status, detect abnormalities early, and take appropriate action. Furthermore, it aims to allow users to continue their daily lives and sports activities with peace of mind, even when experiencing health problems, without causing them stress. In addition, we hope to contribute to improving the quality of life for users by proposing activities and environments tailored to their health status.

[0296] 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.

[0297] In this invention, the server includes means for acquiring biometric data using a wearable biosensor, means for analyzing the biometric data in real time and detecting abnormalities, and means for transmitting information to the nearest medical institution based on the analysis results. This enables timely management of the user's health status and allows for prompt and appropriate medical response when an abnormality is detected.

[0298] A "wearable biosensor" is a small electronic device worn by an individual to collect biometric data in real time.

[0299] "Biological data" refers to physiological information indicating an individual's health status, such as body temperature and heart rate.

[0300] "Real-time analysis" is a technology that immediately processes the acquired data and quickly generates results.

[0301] "Anomaly detection" is a process of identifying data that deviates from the normal health pattern.

[0302] "Multilingual instruction" is a function that provides instructions obtained from the analysis results in different languages that can be understood by the user.

[0303] "Activity plan" is a plan that includes daily activities and visit destinations proposed according to the user's health status and preferences.

[0304] "Virtual reality technology" is a technology that uses digital video technology to simulate the same experience as the real world.

[0305] "Anonymization" is a method of protecting privacy by processing data so that individual identification is impossible.

[0306] "Academic research institution" is an organization that conducts scientific investigations and research for the purpose of creating new knowledge.

[0307] "The nearest medical institution" is a facility that provides medical services that are geographically closest to the target user.

[0308] The system for implementing the present invention is composed of a wearable biosensor, terminal devices such as smartphones and tablets, and a server connected to the cloud. The user wears the wearable biosensor and acquires biological data such as body temperature and heart rate. This wearable device transmits the acquired data to the terminal device via Bluetooth or Wi-Fi.

[0309] The terminal device is equipped with software that implements a generative AI model, allowing for real-time analysis of biometric data. This analysis learns normal health patterns, and the device has a function to notify the user if an abnormality is detected. Furthermore, it periodically sends health data to the nearest medical institution, enabling prompt medical intervention as needed.

[0310] Furthermore, the server uses reinforcement learning techniques to generate activity plans based on the user's preferences and health status. This plan is then presented to the user visually using virtual reality technology. Specifically, a user with a fever can be suggested a cool museum or park, and detailed information about it can be virtually guided through the site.

[0311] To ensure data security, the server anonymizes the accumulated biometric data and shares it with international academic research institutions. This allows for contributions to medical research while protecting the privacy of individual users.

[0312] As a concrete example, when a traveler visiting a smart city wears a wearable device and experiences health problems, the application detects the abnormality and provides a notification prompting them to visit a medical facility immediately. It also provides activity suggestions based on the user's health status using a generative AI model. An example of a prompt message is, "Detect health abnormalities based on data from the wearable device and generate appropriate action suggestions within the smart city."

[0313] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0314] Step 1:

[0315] The user wears a wearable biosensor to acquire biometric data such as body temperature and heart rate. This sensor transmits this data to a device via Bluetooth or Wi-Fi. The input data is biometric information, and the output is the transmitted biometric data. Data transmission is performed by the communication module on the sensor side.

[0316] Step 2:

[0317] The device inputs received biometric data into a generating AI model for real-time analysis. Through this analysis, it learns normal health patterns and has the ability to detect abnormalities. The input is the received biometric data, and the output indicates whether or not an abnormality is present. Data processing is performed using neural network analysis.

[0318] Step 3:

[0319] Based on the analysis results, the terminal immediately notifies the user if an anomaly is detected. During this process, multilingual notification messages are generated and displayed to the user. The input is the result of the anomaly detection, and the output is the notification to the user. Natural language processing is used to generate the messages.

[0320] Step 4:

[0321] The server generates an activity plan using reinforcement learning techniques based on the user's health status and preferences. The generated plan includes actions and destinations tailored to the user's health condition. The input is the user's health status and preference data, and the output is the generated activity plan. A reinforcement learning algorithm is used for plan generation.

[0322] Step 5:

[0323] The server provides the user with the generated activity plan using virtual reality technology. Specifically, it offers virtual tours of places the user will visit and route guidance. The input is the activity plan, and the output is the experience information from the virtual reality. A VR application is used to present the virtual reality.

[0324] Step 6:

[0325] The server anonymizes the accumulated biometric data and securely shares it with international academic research institutions. This step involves data anonymization and secure transmission. The input is biometric data, and the output is anonymized research data. Data de-identification techniques and encryption protocols are used for implementation.

[0326] 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.

[0327] This invention is a system that analyzes a user's biometric information and emotional state in combination, and provides personalized medical and tourism experiences based on that analysis. The specific configuration and operation are as follows.

[0328] First, the user wears a wearable biosensor to collect biometric data such as body temperature and heart rate. Simultaneously, an emotion engine analyzes the user's emotional state from their facial expressions and voice. This makes it possible to monitor both physical health and emotional state.

[0329] The device analyzes collected biometric and emotional data. An AI algorithm is used to learn the user's normal health and emotional patterns from the data, enabling real-time anomaly detection and response to emotional changes.

[0330] Subsequently, the device provides multilingual instructions that take into account the user's health and emotional state. For example, if the user is feeling stressed, it will generate instructions recommending relaxing tourist destinations. This process includes a function to dynamically update the instructions in response to changes in the user's emotions.

[0331] In addition, the device uses a reinforcement learning model to create a travel plan tailored to the user's health and emotional state. This plan reflects the results of the user's emotional analysis to provide the optimal travel experience. For example, if the user is feeling happy, a plan including activities that further enhance that feeling will be presented.

[0332] Furthermore, the device uses AR / VR technology to visually provide users with details of the plan, allowing them to check planned tourist destinations and activities in advance. In cases of emotional instability, additional information may be provided to grab their attention.

[0333] Finally, the server securely stores the acquired data in the cloud, anonymizes it, and shares it with research institutions. This sharing facilitates international research on the relationship between emotions and health. It also contributes to improving the system's accuracy through continuous feedback.

[0334] In this way, the present invention realizes advanced and personalized medical and travel experiences that meet the needs of users.

[0335] The following describes the processing flow.

[0336] Step 1:

[0337] The user wears a wearable biosensor to measure biometric information such as body temperature and heart rate. Simultaneously, a device with a built-in emotion engine collects emotional data from facial expressions and voice. The terminal receives this data.

[0338] Step 2:

[0339] The device analyzes received biometric and emotional data using an AI algorithm. This allows it to learn normal health conditions and emotional patterns, and detect abnormalities and emotional changes.

[0340] Step 3:

[0341] The device provides the user with appropriate instructions in multiple languages ​​based on detected anomalies and emotional states. Specifically, if the user is stressed, instructions suggesting a relaxing environment will be generated.

[0342] Step 4:

[0343] The device generates a sightseeing plan based on the user's health and emotional state. The reinforcement learning model considers the user's budget and preferences to select the most suitable activities.

[0344] Step 5:

[0345] The device visually displays the generated sightseeing plan to the user using AR / VR technology. This allows the user to check the details of the suggested sightseeing destinations and activities in advance.

[0346] Step 6:

[0347] The device monitors the user's emotional state in real time and dynamically adjusts the sightseeing plan as needed. For example, if the user becomes excited, it might consider adding an active activity to the plan.

[0348] Step 7:

[0349] The server securely stores all data in the cloud, anonymizes it, and shares it with international research institutions. This data sharing will advance research on the relationship between emotions and health.

[0350] (Example 2)

[0351] 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".

[0352] In recent years, there has been a growing need for personalized health management and lifestyle improvements, but existing systems struggle to provide individualized medical guidance and travel experiences for each user. Furthermore, there is a demand for more accurate health management and personalized recommendations through integrated analysis of biometric information and emotional states. Additionally, securely sharing collected personal data and utilizing it for international research remains a challenge.

[0353] 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.

[0354] In this invention, the server includes means for acquiring physiological information and emotional state using an information gathering device, means for analyzing the acquired information and detecting abnormalities, and means for providing the user with customized instructions in multiple languages ​​based on the analysis. This enables personalized health and behavioral suggestions.

[0355] An "information gathering device" is a device used to acquire a user's physiological information and emotional state, and includes wearable sensors, cameras, and microphones.

[0356] "Physiological information" refers to numerical data that indicates the user's physical condition, such as body temperature and heart rate.

[0357] "Emotional state" refers to the psychological state analyzed based on the user's facial expressions and voice analysis.

[0358] "Detecting anomalies" means identifying data that deviates from normal health conditions or emotional patterns.

[0359] "Customized instructions in multiple languages" means providing advice and instructions that are individually tailored in multiple languages ​​based on the user's health condition and emotions.

[0360] An "activity plan" is a suggestion of places to visit and activities to do, generated while taking into account the user's health and emotional state.

[0361] "Providing information using visual technology" means using technologies such as AR and VR to visually present information and experiences to users.

[0362] "Providing collected data anonymized" means processing the data in a way that prevents individuals from being identified and then securely sharing it with research institutions and other organizations.

[0363] "Reinforcement learning technology" is a machine learning method that finds the optimal strategy through trial and error and provides individually tailored plans based on the user's requirements and preferences.

[0364] This invention is a system that acquires and analyzes a user's physiological information and emotional state to provide personalized medical and lifestyle suggestions. The specific operation is as follows:

[0365] The user wears a wearable biosensor, which acts as an information gathering device, to acquire physiological information such as body temperature and heart rate. This biosensor continuously collects everyday data and transmits it to a terminal using wireless communication. At the same time, the user's facial expressions and voice are captured by a camera and microphone, and this data is used to analyze their emotional state.

[0366] The device analyzes collected physiological and emotional data in real time. Machine learning algorithms are used for the analysis, particularly to learn normal health and emotional patterns for anomaly detection. Based on the analysis results, a generative AI model is used to provide the user with customized instructions in multiple languages. These instructions appear as notifications on the user's smartphone, prompting specific actions for health improvement or behavioral suggestions. For example, if the analysis indicates the user is feeling fatigued, instructions such as "We recommend taking a walk in a park to refresh yourself" might be provided.

[0367] Furthermore, the device applies reinforcement learning technology to create an activity plan optimized for the user's state. This plan takes into account the user's preferences and emotional state and is presented to the user using visual technology. AR and VR technologies allow users to virtually experience visited locations and activities, and they can review the plan details before departure.

[0368] The server securely stores the collected and analyzed data in the cloud. During this process, the data is anonymized to protect individual privacy and shared with research institutions, contributing to the advancement of international research. Furthermore, feedback from the data can be used to improve the system's accuracy.

[0369] An example of a prompt sentence to input into a generative AI model would be, "Please suggest relaxing tourist destinations that are recommended when the user is feeling stressed."

[0370] This system analyzes the user's health and emotional state and provides multilingual instructions and personalized activity plans based on that analysis, thereby delivering a highly personalized experience to the user.

[0371] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0372] Step 1:

[0373] The user wears a wearable device to collect physiological data such as body temperature and heart rate. This data is transmitted wirelessly to a terminal. Physiological data is the input, and data transmission to the terminal is the output. The device records the data with a timestamp and periodically transfers it to the terminal.

[0374] Step 2:

[0375] The user acquires facial and audio data through their smartphone's camera and microphone. This activates an emotion engine that analyzes the user's emotional state. The input consists of facial and audio data, and the output is the analyzed emotional state. The emotion recognition algorithm extracts facial features and generates an emotion score.

[0376] Step 3:

[0377] The device integrates collected physiological and emotional information and analyzes the data using an AI algorithm. This process involves data preprocessing, including noise reduction, before the normalized data is input to the AI ​​module. The output provides anomaly detection results compared to the user's normal state. The AI ​​performs pattern recognition and provides evaluations that form the basis for real-time notifications.

[0378] Step 4:

[0379] Based on the analysis results, the device uses a generative AI model to create customized instructions for the user in multiple languages. The input is the analysis results, and the output is instructions displayed on the user's smartphone. This provides the user with an appropriate action plan tailored to their specific health and emotional state.

[0380] Step 5:

[0381] The device applies reinforcement learning techniques to create an optimized activity plan based on the user's preferences and emotional state. The input is user profile data and analysis results, and the output is a personalized activity plan. This allows the user to receive detailed recommendations for tourist destinations and activities.

[0382] Step 6:

[0383] The device utilizes AR / VR technology to provide a visualization of the generated activity plan. The activity plan is the input, and the visualized information is presented to the AR / VR device as output. Based on this information, the user can virtually experience the visited locations and make decisions.

[0384] Step 7:

[0385] The server stores all physiological information, emotional states, and analysis results in the cloud, anonymizing the data. All collected data is the input, and securely stored anonymized data is the output. The server shares this data with international research institutions to help with continuous system improvement.

[0386] (Application Example 2)

[0387] 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."

[0388] Conventional systems struggled to efficiently provide individualized support that considered users' health and emotional states, as well as offer concrete suggestions for daily life actions. Furthermore, the lack of real-time analysis of user data for anomaly detection and the ability to respond quickly to such anomalies posed challenges in maintaining users' health and improving their quality of life. Additionally, the security of data sharing for international research using such systems was insufficient.

[0389] 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.

[0390] In this invention, the server includes means for acquiring biometric information using a wearable sensor device, means for analyzing the acquired biometric information and emotional state in real time and detecting anomalies, means for providing the user with appropriate action suggestions in multiple languages ​​based on the analysis results, means for generating application plans according to the user's health and emotional state, means for providing the generated application plans to the user visually and allowing them to confirm them via a monitoring device, means for anonymizing the accumulated data and securely sharing it with international research facilities, and means for controlling a physical agent capable of performing optimal actions based on the user's biometric information and emotional state. This enables highly personalized support for daily life tailored to the user's health and emotional state.

[0391] A "wearable sensor device" is a device that is attached to a user's body to continuously measure and acquire their biometric information.

[0392] "Biometric information" refers to data that indicates the user's physical condition, such as body temperature, heart rate, and blood oxygen saturation.

[0393] "Emotional state" refers to the user's psychological condition and is information obtained by analyzing facial expressions, voice, and other factors.

[0394] "Real-time analysis" is a process that collects data, performs analysis immediately on the spot, and produces results.

[0395] "Anomaly detection" refers to identifying changes in health or emotions as phenomena that deviate from the standard state based on analyzed data.

[0396] "Action suggestions" refer to recommending activities and behaviors that are appropriate for the user's current health and emotional state.

[0397] "Providing information in multiple languages" refers to a method of translating and distributing information and instructions in multiple languages ​​for users with different native languages.

[0398] An "application plan" refers to specific plans and action proposals that are feasible in daily life, based on the user's situation.

[0399] "Providing information through visual means" refers to a method of presenting information to users visually using images and videos to aid their understanding.

[0400] A "monitor device" is a device that displays information to the user, enabling them to check and operate it.

[0401] "Anonymization" is a process that removes elements that can identify an individual from collected data, thereby protecting privacy.

[0402] An "international research facility" is an organization or institution that conducts research activities and utilizes data across multiple countries.

[0403] A "physical agent" is an artificial entity that controls specific devices or equipment to assist users in performing their actions.

[0404] The system for realizing this invention consists of three parties: a user, a terminal, and a server. The user wears a wearable sensor device to acquire biometric information such as body temperature and heart rate. This allows for continuous monitoring of the user's health status. Furthermore, an emotion recognition algorithm can be used to analyze the user's emotional state in real time from their facial expressions and voice.

[0405] The device analyzes collected biometric information and emotional states in real time using an AI algorithm, detecting deviations from normal states as abnormalities. This enables the generation of appropriate action suggestions based on the user's health and emotional state, and provides information in multiple languages. Suggestions could include, for example, playing music for relaxation or recommending exercises.

[0406] The server securely stores data transmitted from the terminal in the cloud and anonymizes the data. The anonymized data is shared with international research institutions and contributes to research exploring the relationship between emotional states and health. Furthermore, when generating user application plans, reinforcement learning algorithms can be used to provide suggestions optimized for individual preferences. The generated application plans are visually presented to the user through AR / VR technology to aid visual understanding.

[0407] For example, if a user feels stressed after work, the system might suggest playing relaxation music and plan a walking route for the next day. An example of a prompt might be, "Based on the user's biometric information and emotions, let's suggest the most suitable relaxation method. For example, what methods would you suggest if the user is tired?"

[0408] This will enable users to receive appropriate support based on their health and emotional state, thereby improving their quality of life.

[0409] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0410] Step 1:

[0411] The user wears a wearable sensor device. The sensor acquires biometric information such as body temperature and heart rate. The input is the user's physical data, and the output is the acquired biometric information. Based on this information, the sensor continuously collects the user's biometric data and transmits it to the terminal.

[0412] Step 2:

[0413] The device receives collected biometric information and voice input, and uses an emotion recognition algorithm to analyze the user's emotional state. The input is biometric information and voice data, and the output is the user's emotional state. In this process, voice and facial expression data are analyzed, and emotions are identified by AI.

[0414] Step 3:

[0415] The device uses an AI algorithm to analyze acquired biometric information and emotional state in real time, detecting deviations from a normal state as abnormalities. The output is a diagnostic result regarding the user's condition. In this step, data is compared to detect health abnormalities in the user.

[0416] Step 4:

[0417] The device generates appropriate action suggestions based on the analysis results and provides them to the user in multiple languages. The input is the diagnostic result, and the output is a guideline for action suggestions. Specifically, this includes playing relaxation music and providing action recommendations tailored to the user's physical condition.

[0418] Step 5:

[0419] The server receives data transmitted from the terminal in Kitami and stores it in secure cloud storage. The input is anonymized user data, and the output is securely stored data. In this step, the data is anonymized and made shareable with international research institutions.

[0420] Step 6:

[0421] The server uses a reinforcement learning algorithm to generate application plans optimized for the user's interests and preferences. The input consists of collected data and user history, and the output is a individually optimized plan. This process learns from past data and generates suggestions tailored to the user.

[0422] Step 7:

[0423] The generated application plan is visually presented to the user from the device using AR / VR technology. The input is an individually optimized plan, and the output is visual content. In this step, an environment is created in which the user can check the specific details in advance through the visualization of the plan.

[0424] 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.

[0425] 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.

[0426] 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.

[0427] [Third Embodiment]

[0428] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0429] 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.

[0430] 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).

[0431] 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.

[0432] 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.

[0433] 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).

[0434] 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.

[0435] 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.

[0436] 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.

[0437] 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.

[0438] 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.

[0439] 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".

[0440] This invention combines wearable devices and AI technology to create a system that allows people to self-manage their health even in new environments they encounter. The following describes specific embodiments of the invention.

[0441] First, the user wears a wearable biosensor to collect biometric data such as body temperature and heart rate in real time. This sensor transmits the data to the device via Bluetooth or Wi-Fi.

[0442] The device utilizes an AI model to analyze the received data. This allows it to learn normal health patterns from the data and detect abnormalities when they occur. When an abnormality is detected, the device notifies the user in multiple languages ​​and provides specific instructions regarding their health status.

[0443] Next, the device generates a sightseeing plan based on the user's health status. This uses reinforcement learning technology to consider the user's preferences and environmental conditions, suggesting optimal activities and tourist destinations. These suggestions are presented visually using AR and VR technologies. For example, if the user has a high body temperature, a cool art museum might be recommended, and visual technology allows the user to preview the museum's interior beforehand.

[0444] Furthermore, this system is linked to a server, and data is securely stored in the cloud. The stored data is anonymized to protect personal information and then shared with international research institutions. This sharing supports the expansion of global knowledge and technological advancement in the medical field.

[0445] By integrating the above functions, this invention provides an environment where users can safely enjoy both medical care and tourism simultaneously without feeling any language or cultural barriers.

[0446] The following describes the processing flow.

[0447] Step 1:

[0448] The user wears a wearable biosensor to continuously measure data such as body temperature and heart rate. The wearable device transmits the measured data to the terminal.

[0449] Step 2:

[0450] The device activates an AI algorithm to analyze the received biometric data. This algorithm has the ability to compare historical data with real-time data and detect anomalies.

[0451] Step 3:

[0452] When an anomaly is detected, the device sends an alert to the user. This alert includes health recommendations and countermeasures in multiple languages.

[0453] Step 4:

[0454] The device creates a sightseeing plan based on the user's health status. It utilizes a reinforcement learning model to generate a customized plan that takes into account the user's budget, time, and health condition.

[0455] Step 5:

[0456] The device displays the generated sightseeing plan to the user using AR / VR technology. This allows the user to visually confirm a preview of the places they will visit and the activities they will engage in.

[0457] Step 6:

[0458] Data is sent from the device to the server. The server anonymizes the biometric data and stores it securely.

[0459] Step 7:

[0460] The server shares accumulated data with international research institutions via federated learning technology. This process supports the advancement of medical research.

[0461] (Example 1)

[0462] 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."

[0463] In modern society, users find it difficult to effectively manage their health in different environments, and there is a need for ways to reduce health risks and stay safe and healthy, especially when traveling or visiting new places. Furthermore, providing individually optimized travel plans based on health conditions is challenging, necessitating a system that is intuitive and reassuring for users. Additionally, building a system that utilizes collected data more broadly and effectively to contribute to the advancement of international medical research is another challenge.

[0464] 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.

[0465] In this invention, the server includes means for acquiring biometric data using a wearable information collection device, means for processing the acquired biometric data immediately and identifying abnormalities, and means for providing appropriate instructions to the user in multiple languages ​​based on the processing results. This allows the user to understand their health status in real time and take appropriate countermeasures quickly in the event of an abnormality. Furthermore, by optimizing the movement plan using a generative AI model, it is possible to provide a personalized movement plan tailored to the user's preferences and health status, and intuitive information can be provided through visual means. This realizes a safe, healthy, and highly satisfying experience.

[0466] A "wearable information collection device" is an electronic device that is worn on the body to continuously monitor and acquire the user's biometric data.

[0467] "Biometric data" refers to numerical information that indicates the user's physical condition, such as body temperature, heart rate, and blood pressure.

[0468] "Immediate processing" refers to a process where biometric data is analyzed immediately after being received, and results are obtained quickly.

[0469] "Identifying anomalies" means detecting values ​​that deviate from normal data patterns or sudden changes.

[0470] "Providing appropriate instructions in multiple languages" means presenting necessary actions in multiple languages ​​so that they can be understood regardless of the user's language.

[0471] A "travel plan" is a schedule of destinations and activities suggested to the user based on their health condition and preferences.

[0472] A "generative AI model" is an artificial intelligence algorithm that learns from large amounts of data and enables data analysis and prediction.

[0473] "Visual presentation" refers to a method that allows users to directly understand information through videos and images.

[0474] "Anonymization" is the process of removing personal information from data so that individuals cannot be identified.

[0475] An "international research institution" is an organization that conducts medical and technological research across multiple countries.

[0476] "Learning technology" refers to techniques that use data to improve models and automatically enhance their performance.

[0477] This invention is a system that combines a wearable information collection device with artificial intelligence technology to support the user's health management while providing an optimal travel plan.

[0478] First, the user wears a wearable data collection device. This device acquires biometric data such as body temperature and heart rate in real time and continuously monitors the data. The collected data is transmitted to a device such as a smartphone or tablet via Bluetooth or Wi-Fi. This data acquisition allows the user to easily monitor their own health status.

[0479] The device utilizes a generative AI model to analyze the received biometric data. This AI model is based on frameworks such as TensorFlow and PyTorch, built using Python, and processes the acquired data in real time. This allows it to learn normal health patterns and identify abnormalities when they are detected. For example, it can detect an anomaly when the heart rate deviates from the normal range and take appropriate action.

[0480] If an abnormality is detected, the device employs a method to provide instructions to the user in multiple languages. Specifically, action instructions such as "Stop exercising and take a break" are given in a language the user understands. This allows users to receive health guidance even without language barriers.

[0481] Furthermore, the device uses reinforcement learning technology to generate an optimal travel plan based on the user's health status and preferences. This plan includes potential destinations and activities, which are presented visually using AR and VR technologies. For example, if the user is not feeling well, health-conscious destinations such as indoor art museums or museums will be suggested. Visual technologies such as Google Cardboard allow users to preview the interior of the museum beforehand.

[0482] Furthermore, the collected biometric data and analysis results are securely stored in the cloud via servers. The cloud service accumulates anonymized data, which is then shared with international research institutions, contributing to the advancement of global medical research.

[0483] This system, utilizing a generative AI model, allows users to confidently manage their health and create plans in their new environment. An example of a prompt would be, "Tell me some recommended nearby tourist spots." This enables the system to efficiently provide information tailored to the user's needs.

[0484] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0485] Step 1:

[0486] The user wears a wearable data collection device. This device acquires biometric data such as body temperature and heart rate in real time as part of the user's physical information. The input is the user's biosignals, and the output is formalized biometric data transmitted to a terminal via Bluetooth or Wi-Fi. This device continuously monitors the data using sensors and collects necessary physiological data.

[0487] Step 2:

[0488] The device sends the received biometric data to an AI model for immediate processing. The input is biometric data acquired from a wearable device, which the AI ​​model analyzes and compares to normal health patterns. The output is the identification result of whether or not an anomaly exists. The AI ​​model is built using TensorFlow and PyTorch and identifies anomalies in the data in real time.

[0489] Step 3:

[0490] When an anomaly is detected, the device sends instructions to the user in multiple languages. The input is the analysis result indicating the anomaly, and the output is an instruction message to the user. Specifically, the user is given instructions in a language they understand, such as "Stop exercising." This allows the user to take appropriate action immediately.

[0491] Step 4:

[0492] The device further utilizes a generative AI model to create travel plans tailored to the user's health status and preferences. Inputs are user preference data and current health status, while output is an optimized travel schedule and destination list. Reinforcement learning techniques are used to optimize the plan, which is then presented to the user visually through AR or VR technology. This plan makes it easier for the user to choose health-conscious activities.

[0493] Step 5:

[0494] The generated data and analysis results are stored in the cloud by the server. The input is the original biometric data and its analysis results, and the output is an anonymized dataset on the cloud. This allows for the sharing of information with international research institutions while protecting personal information, contributing to the advancement of medical research. Cloud services such as AWS may be used in this process.

[0495] (Application Example 1)

[0496] 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."

[0497] The objective of this invention is to enable citizens residing in smart cities to efficiently monitor their daily health status, detect abnormalities early, and take appropriate action. Furthermore, it aims to allow users to continue their daily lives and sports activities with peace of mind, even when experiencing health problems, without causing them stress. In addition, we hope to contribute to improving the quality of life for users by proposing activities and environments tailored to their health status.

[0498] 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.

[0499] In this invention, the server includes means for acquiring biometric data using a wearable biosensor, means for analyzing the biometric data in real time and detecting abnormalities, and means for transmitting information to the nearest medical institution based on the analysis results. This enables timely management of the user's health status and allows for prompt and appropriate medical response when an abnormality is detected.

[0500] A "wearable biosensor" is a small electronic device worn by an individual to collect biometric data in real time.

[0501] "Biometric data" refers to physiological information that indicates an individual's health status, such as body temperature and heart rate.

[0502] "Real-time analysis" is a technology that processes acquired data immediately and generates results quickly.

[0503] Anomaly detection is the process of identifying data that deviates from normal health patterns.

[0504] "Multilingual instructions" is a function that provides instructions derived from analysis results in different languages ​​that the user can understand.

[0505] An "activity plan" is a plan that includes daily activities and places to visit, tailored to the user's health condition and preferences.

[0506] "Virtual reality technology" is a technology that uses digital imaging technology to simulate experiences that are the same as those in the real world.

[0507] "Anonymization" is a technique that protects privacy by processing data in a way that makes it impossible to identify individuals.

[0508] An "academic research institution" is an organization whose purpose is to conduct scientific investigations and research and to create new knowledge.

[0509] "Nearest medical institution" refers to the facility that provides medical services geographically closest to the target user.

[0510] The system for implementing the present invention consists of a wearable biosensor, a terminal device such as a smartphone or tablet, and a server connected to the cloud. The user wears the wearable biosensor and acquires biometric data such as body temperature and heart rate. This wearable device transmits the acquired data to the terminal device via Bluetooth or Wi-Fi.

[0511] The terminal device is equipped with software that implements a generative AI model, allowing for real-time analysis of biometric data. This analysis learns normal health patterns, and the device has a function to notify the user if an abnormality is detected. Furthermore, it periodically sends health data to the nearest medical institution, enabling prompt medical intervention as needed.

[0512] Furthermore, the server uses reinforcement learning techniques to generate activity plans based on the user's preferences and health status. This plan is then presented to the user visually using virtual reality technology. Specifically, a user with a fever can be suggested a cool museum or park, and detailed information about it can be virtually guided through the site.

[0513] To ensure data security, the server anonymizes the accumulated biometric data and shares it with international academic research institutions. This allows for contributions to medical research while protecting the privacy of individual users.

[0514] As a concrete example, when a traveler visiting a smart city wears a wearable device and experiences health problems, the application detects the abnormality and provides a notification prompting them to visit a medical facility immediately. It also provides activity suggestions based on the user's health status using a generative AI model. An example of a prompt message is, "Detect health abnormalities based on data from the wearable device and generate appropriate action suggestions within the smart city."

[0515] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0516] Step 1:

[0517] The user wears a wearable biosensor to acquire biometric data such as body temperature and heart rate. This sensor transmits this data to a device via Bluetooth or Wi-Fi. The input data is biometric information, and the output is the transmitted biometric data. Data transmission is performed by the communication module on the sensor side.

[0518] Step 2:

[0519] The device inputs received biometric data into a generating AI model for real-time analysis. Through this analysis, it learns normal health patterns and has the ability to detect abnormalities. The input is the received biometric data, and the output indicates whether or not an abnormality is present. Data processing is performed using neural network analysis.

[0520] Step 3:

[0521] Based on the analysis results, the terminal immediately notifies the user if an anomaly is detected. During this process, multilingual notification messages are generated and displayed to the user. The input is the result of the anomaly detection, and the output is the notification to the user. Natural language processing is used to generate the messages.

[0522] Step 4:

[0523] The server generates an activity plan using reinforcement learning techniques based on the user's health status and preferences. The generated plan includes actions and destinations tailored to the user's health condition. The input is the user's health status and preference data, and the output is the generated activity plan. A reinforcement learning algorithm is used for plan generation.

[0524] Step 5:

[0525] The server provides the user with the generated activity plan using virtual reality technology. Specifically, it offers virtual tours of places the user will visit and route guidance. The input is the activity plan, and the output is the experience information from the virtual reality. A VR application is used to present the virtual reality.

[0526] Step 6:

[0527] The server anonymizes the accumulated biometric data and securely shares it with international academic research institutions. This step involves data anonymization and secure transmission. The input is biometric data, and the output is anonymized research data. Data de-identification techniques and encryption protocols are used for implementation.

[0528] 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.

[0529] This invention is a system that analyzes a user's biometric information and emotional state in combination, and provides personalized medical and tourism experiences based on that analysis. The specific configuration and operation are as follows.

[0530] First, the user wears a wearable biosensor to collect biometric data such as body temperature and heart rate. Simultaneously, an emotion engine analyzes the user's emotional state from their facial expressions and voice. This makes it possible to monitor both physical health and emotional state.

[0531] The device analyzes collected biometric and emotional data. An AI algorithm is used to learn the user's normal health and emotional patterns from the data, enabling real-time anomaly detection and response to emotional changes.

[0532] Subsequently, the device provides multilingual instructions that take into account the user's health and emotional state. For example, if the user is feeling stressed, it will generate instructions recommending relaxing tourist destinations. This process includes a function to dynamically update the instructions in response to changes in the user's emotions.

[0533] In addition, the device uses a reinforcement learning model to create a travel plan tailored to the user's health and emotional state. This plan reflects the results of the user's emotional analysis to provide the optimal travel experience. For example, if the user is feeling happy, a plan including activities that further enhance that feeling will be presented.

[0534] Furthermore, the device uses AR / VR technology to visually provide users with details of the plan, allowing them to check planned tourist destinations and activities in advance. In cases of emotional instability, additional information may be provided to grab their attention.

[0535] Finally, the server securely stores the acquired data in the cloud, anonymizes it, and shares it with research institutions. This sharing facilitates international research on the relationship between emotions and health. It also contributes to improving the system's accuracy through continuous feedback.

[0536] In this way, the present invention realizes advanced and personalized medical and travel experiences that meet the needs of users.

[0537] The following describes the processing flow.

[0538] Step 1:

[0539] The user wears a wearable biosensor to measure biometric information such as body temperature and heart rate. Simultaneously, a device with a built-in emotion engine collects emotional data from facial expressions and voice. The terminal receives this data.

[0540] Step 2:

[0541] The device analyzes received biometric and emotional data using an AI algorithm. This allows it to learn normal health conditions and emotional patterns, and detect abnormalities and emotional changes.

[0542] Step 3:

[0543] The device provides the user with appropriate instructions in multiple languages ​​based on detected anomalies and emotional states. Specifically, if the user is stressed, instructions suggesting a relaxing environment will be generated.

[0544] Step 4:

[0545] The device generates a sightseeing plan based on the user's health and emotional state. The reinforcement learning model considers the user's budget and preferences to select the most suitable activities.

[0546] Step 5:

[0547] The device visually displays the generated sightseeing plan to the user using AR / VR technology. This allows the user to check the details of the suggested sightseeing destinations and activities in advance.

[0548] Step 6:

[0549] The device monitors the user's emotional state in real time and dynamically adjusts the sightseeing plan as needed. For example, if the user becomes excited, it might consider adding an active activity to the plan.

[0550] Step 7:

[0551] The server securely stores all data in the cloud, anonymizes it, and shares it with international research institutions. This data sharing will advance research on the relationship between emotions and health.

[0552] (Example 2)

[0553] 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."

[0554] In recent years, there has been a growing need for personalized health management and lifestyle improvements, but existing systems struggle to provide individualized medical guidance and travel experiences for each user. Furthermore, there is a demand for more accurate health management and personalized recommendations through integrated analysis of biometric information and emotional states. Additionally, securely sharing collected personal data and utilizing it for international research remains a challenge.

[0555] 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.

[0556] In this invention, the server includes means for acquiring physiological information and emotional state using an information gathering device, means for analyzing the acquired information and detecting abnormalities, and means for providing the user with customized instructions in multiple languages ​​based on the analysis. This enables personalized health and behavioral suggestions.

[0557] An "information gathering device" is a device used to acquire a user's physiological information and emotional state, and includes wearable sensors, cameras, and microphones.

[0558] "Physiological information" refers to numerical data that indicates the user's physical condition, such as body temperature and heart rate.

[0559] "Emotional state" refers to the psychological state analyzed based on the user's facial expressions and voice analysis.

[0560] "Detecting anomalies" means identifying data that deviates from normal health conditions or emotional patterns.

[0561] "Customized instructions in multiple languages" means providing advice and instructions that are individually tailored in multiple languages ​​based on the user's health condition and emotions.

[0562] An "activity plan" is a suggestion of places to visit and activities to do, generated while taking into account the user's health and emotional state.

[0563] "Providing information using visual technology" means using technologies such as AR and VR to visually present information and experiences to users.

[0564] "Providing collected data anonymized" means processing the data in a way that prevents individuals from being identified and then securely sharing it with research institutions and other organizations.

[0565] "Reinforcement learning technology" is a machine learning method that finds the optimal strategy through trial and error and provides individually tailored plans based on the user's requirements and preferences.

[0566] This invention is a system that acquires and analyzes a user's physiological information and emotional state to provide personalized medical and lifestyle suggestions. The specific operation is as follows:

[0567] The user wears a wearable biosensor, which acts as an information gathering device, to acquire physiological information such as body temperature and heart rate. This biosensor continuously collects everyday data and transmits it to a terminal using wireless communication. At the same time, the user's facial expressions and voice are captured by a camera and microphone, and this data is used to analyze their emotional state.

[0568] The device analyzes collected physiological and emotional data in real time. Machine learning algorithms are used for the analysis, particularly to learn normal health and emotional patterns for anomaly detection. Based on the analysis results, a generative AI model is used to provide the user with customized instructions in multiple languages. These instructions appear as notifications on the user's smartphone, prompting specific actions for health improvement or behavioral suggestions. For example, if the analysis indicates the user is feeling fatigued, instructions such as "We recommend taking a walk in a park to refresh yourself" might be provided.

[0569] Furthermore, the device applies reinforcement learning technology to create an activity plan optimized for the user's state. This plan takes into account the user's preferences and emotional state and is presented to the user using visual technology. AR and VR technologies allow users to virtually experience visited locations and activities, and they can review the plan details before departure.

[0570] The server securely stores the collected and analyzed data in the cloud. During this process, the data is anonymized to protect individual privacy and shared with research institutions, contributing to the advancement of international research. Furthermore, feedback from the data can be used to improve the system's accuracy.

[0571] An example of a prompt sentence to input into a generative AI model would be, "Please suggest relaxing tourist destinations that are recommended when the user is feeling stressed."

[0572] This system analyzes the user's health and emotional state and provides multilingual instructions and personalized activity plans based on that analysis, thereby delivering a highly personalized experience to the user.

[0573] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0574] Step 1:

[0575] The user wears a wearable device to collect physiological data such as body temperature and heart rate. This data is transmitted wirelessly to a terminal. Physiological data is the input, and data transmission to the terminal is the output. The device records the data with a timestamp and periodically transfers it to the terminal.

[0576] Step 2:

[0577] The user acquires facial and audio data through their smartphone's camera and microphone. This activates an emotion engine that analyzes the user's emotional state. The input consists of facial and audio data, and the output is the analyzed emotional state. The emotion recognition algorithm extracts facial features and generates an emotion score.

[0578] Step 3:

[0579] The device integrates collected physiological and emotional information and analyzes the data using an AI algorithm. This process involves data preprocessing, including noise reduction, before the normalized data is input to the AI ​​module. The output provides anomaly detection results compared to the user's normal state. The AI ​​performs pattern recognition and provides evaluations that form the basis for real-time notifications.

[0580] Step 4:

[0581] Based on the analysis results, the device uses a generative AI model to create customized instructions for the user in multiple languages. The input is the analysis results, and the output is instructions displayed on the user's smartphone. This provides the user with an appropriate action plan tailored to their specific health and emotional state.

[0582] Step 5:

[0583] The device applies reinforcement learning techniques to create an optimized activity plan based on the user's preferences and emotional state. The input is user profile data and analysis results, and the output is a personalized activity plan. This allows the user to receive detailed recommendations for tourist destinations and activities.

[0584] Step 6:

[0585] The device utilizes AR / VR technology to provide a visualization of the generated activity plan. The activity plan is the input, and the visualized information is presented to the AR / VR device as output. Based on this information, the user can virtually experience the visited locations and make decisions.

[0586] Step 7:

[0587] The server stores all physiological information, emotional states, and analysis results in the cloud, anonymizing the data. All collected data is the input, and securely stored anonymized data is the output. The server shares this data with international research institutions to help with continuous system improvement.

[0588] (Application Example 2)

[0589] 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."

[0590] Conventional systems struggled to efficiently provide individualized support that considered users' health and emotional states, as well as offer concrete suggestions for daily life actions. Furthermore, the lack of real-time analysis of user data for anomaly detection and the ability to respond quickly to such anomalies posed challenges in maintaining users' health and improving their quality of life. Additionally, the security of data sharing for international research using such systems was insufficient.

[0591] 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.

[0592] In this invention, the server includes means for acquiring biometric information using a wearable sensor device, means for analyzing the acquired biometric information and emotional state in real time and detecting anomalies, means for providing the user with appropriate action suggestions in multiple languages ​​based on the analysis results, means for generating application plans according to the user's health and emotional state, means for providing the generated application plans to the user visually and allowing them to confirm them via a monitoring device, means for anonymizing the accumulated data and securely sharing it with international research facilities, and means for controlling a physical agent capable of performing optimal actions based on the user's biometric information and emotional state. This enables highly personalized support for daily life tailored to the user's health and emotional state.

[0593] A "wearable sensor device" is a device that is attached to a user's body to continuously measure and acquire their biometric information.

[0594] "Biometric information" refers to data that indicates the user's physical condition, such as body temperature, heart rate, and blood oxygen saturation.

[0595] "Emotional state" refers to the user's psychological condition and is information obtained by analyzing facial expressions, voice, and other factors.

[0596] "Real-time analysis" is a process that collects data, performs analysis immediately on the spot, and produces results.

[0597] "Anomaly detection" refers to identifying changes in health or emotions as phenomena that deviate from the standard state based on analyzed data.

[0598] "Action suggestions" refer to recommending activities and behaviors that are appropriate for the user's current health and emotional state.

[0599] "Providing information in multiple languages" refers to a method of translating and distributing information and instructions in multiple languages ​​for users with different native languages.

[0600] An "application plan" refers to specific plans and action proposals that are feasible in daily life, based on the user's situation.

[0601] "Providing information through visual means" refers to a method of presenting information to users visually using images and videos to aid their understanding.

[0602] A "monitor device" is a device that displays information to the user, enabling them to check and operate it.

[0603] "Anonymization" is a process that removes elements that can identify an individual from collected data, thereby protecting privacy.

[0604] An "international research facility" is an organization or institution that conducts research activities and utilizes data across multiple countries.

[0605] A "physical agent" is an artificial entity that controls specific devices or equipment to assist users in performing their actions.

[0606] The system for realizing this invention consists of three parties: a user, a terminal, and a server. The user wears a wearable sensor device to acquire biometric information such as body temperature and heart rate. This allows for continuous monitoring of the user's health status. Furthermore, an emotion recognition algorithm can be used to analyze the user's emotional state in real time from their facial expressions and voice.

[0607] The device analyzes collected biometric information and emotional states in real time using an AI algorithm, detecting deviations from normal states as abnormalities. This enables the generation of appropriate action suggestions based on the user's health and emotional state, and provides information in multiple languages. Suggestions could include, for example, playing music for relaxation or recommending exercises.

[0608] The server securely stores data transmitted from the terminal in the cloud and anonymizes the data. The anonymized data is shared with international research institutions and contributes to research exploring the relationship between emotional states and health. Furthermore, when generating user application plans, reinforcement learning algorithms can be used to provide suggestions optimized for individual preferences. The generated application plans are visually presented to the user through AR / VR technology to aid visual understanding.

[0609] For example, if a user feels stressed after work, the system might suggest playing relaxation music and plan a walking route for the next day. An example of a prompt might be, "Based on the user's biometric information and emotions, let's suggest the most suitable relaxation method. For example, what methods would you suggest if the user is tired?"

[0610] This will enable users to receive appropriate support based on their health and emotional state, thereby improving their quality of life.

[0611] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0612] Step 1:

[0613] The user wears a wearable sensor device. The sensor acquires biometric information such as body temperature and heart rate. The input is the user's physical data, and the output is the acquired biometric information. Based on this information, the sensor continuously collects the user's biometric data and transmits it to the terminal.

[0614] Step 2:

[0615] The device receives collected biometric information and voice input, and uses an emotion recognition algorithm to analyze the user's emotional state. The input is biometric information and voice data, and the output is the user's emotional state. In this process, voice and facial expression data are analyzed, and emotions are identified by AI.

[0616] Step 3:

[0617] The device uses an AI algorithm to analyze acquired biometric information and emotional state in real time, detecting deviations from a normal state as abnormalities. The output is a diagnostic result regarding the user's condition. In this step, data is compared to detect health abnormalities in the user.

[0618] Step 4:

[0619] The device generates appropriate action suggestions based on the analysis results and provides them to the user in multiple languages. The input is the diagnostic result, and the output is a guideline for action suggestions. Specifically, this includes playing relaxation music and providing action recommendations tailored to the user's physical condition.

[0620] Step 5:

[0621] The server receives data transmitted from the terminal in Kitami and stores it in secure cloud storage. The input is anonymized user data, and the output is securely stored data. In this step, the data is anonymized and made shareable with international research institutions.

[0622] Step 6:

[0623] The server uses a reinforcement learning algorithm to generate application plans optimized for the user's interests and preferences. The input consists of collected data and user history, and the output is a individually optimized plan. This process learns from past data and generates suggestions tailored to the user.

[0624] Step 7:

[0625] The generated application plan is visually presented to the user from the device using AR / VR technology. The input is an individually optimized plan, and the output is visual content. In this step, an environment is created in which the user can check the specific details in advance through the visualization of the plan.

[0626] 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.

[0627] 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.

[0628] 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.

[0629] [Fourth Embodiment]

[0630] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0631] 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.

[0632] 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).

[0633] 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.

[0634] 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.

[0635] 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).

[0636] 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.

[0637] 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.

[0638] 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.

[0639] 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.

[0640] 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.

[0641] 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.

[0642] 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".

[0643] This invention combines wearable devices and AI technology to create a system that allows people to self-manage their health even in new environments they encounter. The following describes specific embodiments of the invention.

[0644] First, the user wears a wearable biosensor to collect biometric data such as body temperature and heart rate in real time. This sensor transmits the data to the device via Bluetooth or Wi-Fi.

[0645] The device utilizes an AI model to analyze the received data. This allows it to learn normal health patterns from the data and detect abnormalities when they occur. When an abnormality is detected, the device notifies the user in multiple languages ​​and provides specific instructions regarding their health status.

[0646] Next, the device generates a sightseeing plan based on the user's health status. This uses reinforcement learning technology to consider the user's preferences and environmental conditions, suggesting optimal activities and tourist destinations. These suggestions are presented visually using AR and VR technologies. For example, if the user has a high body temperature, a cool art museum might be recommended, and visual technology allows the user to preview the museum's interior beforehand.

[0647] Furthermore, this system is linked to a server, and data is securely stored in the cloud. The stored data is anonymized to protect personal information and then shared with international research institutions. This sharing supports the expansion of global knowledge and technological advancement in the medical field.

[0648] By integrating the above functions, this invention provides an environment where users can safely enjoy both medical care and tourism simultaneously without feeling any language or cultural barriers.

[0649] The following describes the processing flow.

[0650] Step 1:

[0651] The user wears a wearable biosensor to continuously measure data such as body temperature and heart rate. The wearable device transmits the measured data to the terminal.

[0652] Step 2:

[0653] The device activates an AI algorithm to analyze the received biometric data. This algorithm has the ability to compare historical data with real-time data and detect anomalies.

[0654] Step 3:

[0655] When an anomaly is detected, the device sends an alert to the user. This alert includes health recommendations and countermeasures in multiple languages.

[0656] Step 4:

[0657] The device creates a sightseeing plan based on the user's health status. It utilizes a reinforcement learning model to generate a customized plan that takes into account the user's budget, time, and health condition.

[0658] Step 5:

[0659] The device displays the generated sightseeing plan to the user using AR / VR technology. This allows the user to visually confirm a preview of the places they will visit and the activities they will engage in.

[0660] Step 6:

[0661] Data is sent from the device to the server. The server anonymizes the biometric data and stores it securely.

[0662] Step 7:

[0663] The server shares accumulated data with international research institutions via federated learning technology. This process supports the advancement of medical research.

[0664] (Example 1)

[0665] 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".

[0666] In modern society, users find it difficult to effectively manage their health in different environments, and there is a need for ways to reduce health risks and stay safe and healthy, especially when traveling or visiting new places. Furthermore, providing individually optimized travel plans based on health conditions is challenging, necessitating a system that is intuitive and reassuring for users. Additionally, building a system that utilizes collected data more broadly and effectively to contribute to the advancement of international medical research is another challenge.

[0667] 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.

[0668] In this invention, the server includes means for acquiring biometric data using a wearable information collection device, means for processing the acquired biometric data immediately and identifying abnormalities, and means for providing appropriate instructions to the user in multiple languages ​​based on the processing results. This allows the user to understand their health status in real time and take appropriate countermeasures quickly in the event of an abnormality. Furthermore, by optimizing the movement plan using a generative AI model, it is possible to provide a personalized movement plan tailored to the user's preferences and health status, and intuitive information can be provided through visual means. This realizes a safe, healthy, and highly satisfying experience.

[0669] A "wearable information collection device" is an electronic device that is worn on the body to continuously monitor and acquire the user's biometric data.

[0670] "Biometric data" refers to numerical information that indicates the user's physical condition, such as body temperature, heart rate, and blood pressure.

[0671] "Immediate processing" refers to a process where biometric data is analyzed immediately after being received, and results are obtained quickly.

[0672] "Identifying anomalies" means detecting values ​​that deviate from normal data patterns or sudden changes.

[0673] "Providing appropriate instructions in multiple languages" means presenting necessary actions in multiple languages ​​so that they can be understood regardless of the user's language.

[0674] A "travel plan" is a schedule of destinations and activities suggested to the user based on their health condition and preferences.

[0675] A "generative AI model" is an artificial intelligence algorithm that learns from large amounts of data and enables data analysis and prediction.

[0676] "Visual presentation" refers to a method that allows users to directly understand information through videos and images.

[0677] "Anonymization" is the process of removing personal information from data so that individuals cannot be identified.

[0678] An "international research institution" is an organization that conducts medical and technological research across multiple countries.

[0679] "Learning technology" refers to techniques that use data to improve models and automatically enhance their performance.

[0680] This invention is a system that combines a wearable information collection device with artificial intelligence technology to support the user's health management while providing an optimal travel plan.

[0681] First, the user wears a wearable data collection device. This device acquires biometric data such as body temperature and heart rate in real time and continuously monitors the data. The collected data is transmitted to a device such as a smartphone or tablet via Bluetooth or Wi-Fi. This data acquisition allows the user to easily monitor their own health status.

[0682] The device utilizes a generative AI model to analyze the received biometric data. This AI model is based on frameworks such as TensorFlow and PyTorch, built using Python, and processes the acquired data in real time. This allows it to learn normal health patterns and identify abnormalities when they are detected. For example, it can detect an anomaly when the heart rate deviates from the normal range and take appropriate action.

[0683] If an abnormality is detected, the device employs a method to provide instructions to the user in multiple languages. Specifically, action instructions such as "Stop exercising and take a break" are given in a language the user understands. This allows users to receive health guidance even without language barriers.

[0684] Furthermore, the device uses reinforcement learning technology to generate an optimal travel plan based on the user's health status and preferences. This plan includes potential destinations and activities, which are presented visually using AR and VR technologies. For example, if the user is not feeling well, health-conscious destinations such as indoor art museums or museums will be suggested. Visual technologies such as Google Cardboard allow users to preview the interior of the museum beforehand.

[0685] Furthermore, the collected biometric data and analysis results are securely stored in the cloud via servers. The cloud service accumulates anonymized data, which is then shared with international research institutions, contributing to the advancement of global medical research.

[0686] This system, utilizing a generative AI model, allows users to confidently manage their health and create plans in their new environment. An example of a prompt would be, "Tell me some recommended nearby tourist spots." This enables the system to efficiently provide information tailored to the user's needs.

[0687] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0688] Step 1:

[0689] The user wears a wearable data collection device. This device acquires biometric data such as body temperature and heart rate in real time as part of the user's physical information. The input is the user's biosignals, and the output is formalized biometric data transmitted to a terminal via Bluetooth or Wi-Fi. This device continuously monitors the data using sensors and collects necessary physiological data.

[0690] Step 2:

[0691] The device sends the received biometric data to an AI model for immediate processing. The input is biometric data acquired from a wearable device, which the AI ​​model analyzes and compares to normal health patterns. The output is the identification result of whether or not an anomaly exists. The AI ​​model is built using TensorFlow and PyTorch and identifies anomalies in the data in real time.

[0692] Step 3:

[0693] When an anomaly is detected, the device sends instructions to the user in multiple languages. The input is the analysis result indicating the anomaly, and the output is an instruction message to the user. Specifically, the user is given instructions in a language they understand, such as "Stop exercising." This allows the user to take appropriate action immediately.

[0694] Step 4:

[0695] The device further utilizes a generative AI model to create travel plans tailored to the user's health status and preferences. Inputs are user preference data and current health status, while output is an optimized travel schedule and destination list. Reinforcement learning techniques are used to optimize the plan, which is then presented to the user visually through AR or VR technology. This plan makes it easier for the user to choose health-conscious activities.

[0696] Step 5:

[0697] The generated data and analysis results are stored in the cloud by the server. The input is the original biometric data and its analysis results, and the output is an anonymized dataset on the cloud. This allows for the sharing of information with international research institutions while protecting personal information, contributing to the advancement of medical research. Cloud services such as AWS may be used in this process.

[0698] (Application Example 1)

[0699] 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".

[0700] The objective of this invention is to enable citizens residing in smart cities to efficiently monitor their daily health status, detect abnormalities early, and take appropriate action. Furthermore, it aims to allow users to continue their daily lives and sports activities with peace of mind, even when experiencing health problems, without causing them stress. In addition, we hope to contribute to improving the quality of life for users by proposing activities and environments tailored to their health status.

[0701] 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.

[0702] In this invention, the server includes means for acquiring biometric data using a wearable biosensor, means for analyzing the biometric data in real time and detecting abnormalities, and means for transmitting information to the nearest medical institution based on the analysis results. This enables timely management of the user's health status and allows for prompt and appropriate medical response when an abnormality is detected.

[0703] A "wearable biosensor" is a small electronic device worn by an individual to collect biometric data in real time.

[0704] "Biometric data" refers to physiological information that indicates an individual's health status, such as body temperature and heart rate.

[0705] "Real-time analysis" is a technology that processes acquired data immediately and generates results quickly.

[0706] Anomaly detection is the process of identifying data that deviates from normal health patterns.

[0707] "Multilingual instructions" is a function that provides instructions derived from analysis results in different languages ​​that the user can understand.

[0708] An "activity plan" is a plan that includes daily activities and places to visit, tailored to the user's health condition and preferences.

[0709] "Virtual reality technology" is a technology that uses digital imaging technology to simulate experiences that are the same as those in the real world.

[0710] "Anonymization" is a technique that protects privacy by processing data in a way that makes it impossible to identify individuals.

[0711] An "academic research institution" is an organization whose purpose is to conduct scientific investigations and research and to create new knowledge.

[0712] "Nearest medical institution" refers to the facility that provides medical services geographically closest to the target user.

[0713] The system for implementing the present invention consists of a wearable biosensor, a terminal device such as a smartphone or tablet, and a server connected to the cloud. The user wears the wearable biosensor and acquires biometric data such as body temperature and heart rate. This wearable device transmits the acquired data to the terminal device via Bluetooth or Wi-Fi.

[0714] The terminal device is equipped with software that implements a generative AI model, allowing for real-time analysis of biometric data. This analysis learns normal health patterns, and the device has a function to notify the user if an abnormality is detected. Furthermore, it periodically sends health data to the nearest medical institution, enabling prompt medical intervention as needed.

[0715] Furthermore, the server uses reinforcement learning techniques to generate activity plans based on the user's preferences and health status. This plan is then presented to the user visually using virtual reality technology. Specifically, a user with a fever can be suggested a cool museum or park, and detailed information about it can be virtually guided through the site.

[0716] To ensure data security, the server anonymizes the accumulated biometric data and shares it with international academic research institutions. This allows for contributions to medical research while protecting the privacy of individual users.

[0717] As a concrete example, when a traveler visiting a smart city wears a wearable device and experiences health problems, the application detects the abnormality and provides a notification prompting them to visit a medical facility immediately. It also provides activity suggestions based on the user's health status using a generative AI model. An example of a prompt message is, "Detect health abnormalities based on data from the wearable device and generate appropriate action suggestions within the smart city."

[0718] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0719] Step 1:

[0720] The user wears a wearable biosensor to acquire biometric data such as body temperature and heart rate. This sensor transmits this data to a device via Bluetooth or Wi-Fi. The input data is biometric information, and the output is the transmitted biometric data. Data transmission is performed by the communication module on the sensor side.

[0721] Step 2:

[0722] The device inputs received biometric data into a generating AI model for real-time analysis. Through this analysis, it learns normal health patterns and has the ability to detect abnormalities. The input is the received biometric data, and the output indicates whether or not an abnormality is present. Data processing is performed using neural network analysis.

[0723] Step 3:

[0724] Based on the analysis results, the terminal immediately notifies the user if an anomaly is detected. During this process, multilingual notification messages are generated and displayed to the user. The input is the result of the anomaly detection, and the output is the notification to the user. Natural language processing is used to generate the messages.

[0725] Step 4:

[0726] The server generates an activity plan using reinforcement learning techniques based on the user's health status and preferences. The generated plan includes actions and destinations tailored to the user's health condition. The input is the user's health status and preference data, and the output is the generated activity plan. A reinforcement learning algorithm is used for plan generation.

[0727] Step 5:

[0728] The server provides the user with the generated activity plan using virtual reality technology. Specifically, it offers virtual tours of places the user will visit and route guidance. The input is the activity plan, and the output is the experience information from the virtual reality. A VR application is used to present the virtual reality.

[0729] Step 6:

[0730] The server anonymizes the accumulated biometric data and securely shares it with international academic research institutions. This step involves data anonymization and secure transmission. The input is biometric data, and the output is anonymized research data. Data de-identification techniques and encryption protocols are used for implementation.

[0731] 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.

[0732] This invention is a system that analyzes a user's biometric information and emotional state in combination, and provides personalized medical and tourism experiences based on that analysis. The specific configuration and operation are as follows.

[0733] First, the user wears a wearable biosensor to collect biometric data such as body temperature and heart rate. Simultaneously, an emotion engine analyzes the user's emotional state from their facial expressions and voice. This makes it possible to monitor both physical health and emotional state.

[0734] The device analyzes collected biometric and emotional data. An AI algorithm is used to learn the user's normal health and emotional patterns from the data, enabling real-time anomaly detection and response to emotional changes.

[0735] Subsequently, the device provides multilingual instructions that take into account the user's health and emotional state. For example, if the user is feeling stressed, it will generate instructions recommending relaxing tourist destinations. This process includes a function to dynamically update the instructions in response to changes in the user's emotions.

[0736] In addition, the device uses a reinforcement learning model to create a travel plan tailored to the user's health and emotional state. This plan reflects the results of the user's emotional analysis to provide the optimal travel experience. For example, if the user is feeling happy, a plan including activities that further enhance that feeling will be presented.

[0737] Furthermore, the device uses AR / VR technology to visually provide users with details of the plan, allowing them to check planned tourist destinations and activities in advance. In cases of emotional instability, additional information may be provided to grab their attention.

[0738] Finally, the server securely stores the acquired data in the cloud, anonymizes it, and shares it with research institutions. This sharing facilitates international research on the relationship between emotions and health. It also contributes to improving the system's accuracy through continuous feedback.

[0739] In this way, the present invention realizes advanced and personalized medical and travel experiences that meet the needs of users.

[0740] The following describes the processing flow.

[0741] Step 1:

[0742] The user wears a wearable biosensor to measure biometric information such as body temperature and heart rate. Simultaneously, a device with a built-in emotion engine collects emotional data from facial expressions and voice. The terminal receives this data.

[0743] Step 2:

[0744] The device analyzes received biometric and emotional data using an AI algorithm. This allows it to learn normal health conditions and emotional patterns, and detect abnormalities and emotional changes.

[0745] Step 3:

[0746] The device provides the user with appropriate instructions in multiple languages ​​based on detected anomalies and emotional states. Specifically, if the user is stressed, instructions suggesting a relaxing environment will be generated.

[0747] Step 4:

[0748] The device generates a sightseeing plan based on the user's health and emotional state. The reinforcement learning model considers the user's budget and preferences to select the most suitable activities.

[0749] Step 5:

[0750] The device visually displays the generated sightseeing plan to the user using AR / VR technology. This allows the user to check the details of the suggested sightseeing destinations and activities in advance.

[0751] Step 6:

[0752] The device monitors the user's emotional state in real time and dynamically adjusts the sightseeing plan as needed. For example, if the user becomes excited, it might consider adding an active activity to the plan.

[0753] Step 7:

[0754] The server securely stores all data in the cloud, anonymizes it, and shares it with international research institutions. This data sharing will advance research on the relationship between emotions and health.

[0755] (Example 2)

[0756] 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".

[0757] In recent years, there has been a growing need for personalized health management and lifestyle improvements, but existing systems struggle to provide individualized medical guidance and travel experiences for each user. Furthermore, there is a demand for more accurate health management and personalized recommendations through integrated analysis of biometric information and emotional states. Additionally, securely sharing collected personal data and utilizing it for international research remains a challenge.

[0758] 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.

[0759] In this invention, the server includes means for acquiring physiological information and emotional state using an information gathering device, means for analyzing the acquired information and detecting abnormalities, and means for providing the user with customized instructions in multiple languages ​​based on the analysis. This enables personalized health and behavioral suggestions.

[0760] An "information gathering device" is a device used to acquire a user's physiological information and emotional state, and includes wearable sensors, cameras, and microphones.

[0761] "Physiological information" refers to numerical data that indicates the user's physical condition, such as body temperature and heart rate.

[0762] "Emotional state" refers to the psychological state analyzed based on the user's facial expressions and voice analysis.

[0763] "Detecting anomalies" means identifying data that deviates from normal health conditions or emotional patterns.

[0764] "Customized instructions in multiple languages" means providing advice and instructions that are individually tailored in multiple languages ​​based on the user's health condition and emotions.

[0765] An "activity plan" is a suggestion of places to visit and activities to do, generated while taking into account the user's health and emotional state.

[0766] "Providing information using visual technology" means using technologies such as AR and VR to visually present information and experiences to users.

[0767] "Providing collected data anonymized" means processing the data in a way that prevents individuals from being identified and then securely sharing it with research institutions and other organizations.

[0768] "Reinforcement learning technology" is a machine learning method that finds the optimal strategy through trial and error and provides individually tailored plans based on the user's requirements and preferences.

[0769] This invention is a system that acquires and analyzes a user's physiological information and emotional state to provide personalized medical and lifestyle suggestions. The specific operation is as follows:

[0770] The user wears a wearable biosensor, which acts as an information gathering device, to acquire physiological information such as body temperature and heart rate. This biosensor continuously collects everyday data and transmits it to a terminal using wireless communication. At the same time, the user's facial expressions and voice are captured by a camera and microphone, and this data is used to analyze their emotional state.

[0771] The device analyzes collected physiological and emotional data in real time. Machine learning algorithms are used for the analysis, particularly to learn normal health and emotional patterns for anomaly detection. Based on the analysis results, a generative AI model is used to provide the user with customized instructions in multiple languages. These instructions appear as notifications on the user's smartphone, prompting specific actions for health improvement or behavioral suggestions. For example, if the analysis indicates the user is feeling fatigued, instructions such as "We recommend taking a walk in a park to refresh yourself" might be provided.

[0772] Furthermore, the device applies reinforcement learning technology to create an activity plan optimized for the user's state. This plan takes into account the user's preferences and emotional state and is presented to the user using visual technology. AR and VR technologies allow users to virtually experience visited locations and activities, and they can review the plan details before departure.

[0773] The server securely stores the collected and analyzed data in the cloud. During this process, the data is anonymized to protect individual privacy and shared with research institutions, contributing to the advancement of international research. Furthermore, feedback from the data can be used to improve the system's accuracy.

[0774] An example of a prompt sentence to input into a generative AI model would be, "Please suggest relaxing tourist destinations that are recommended when the user is feeling stressed."

[0775] This system analyzes the user's health and emotional state and provides multilingual instructions and personalized activity plans based on that analysis, thereby delivering a highly personalized experience to the user.

[0776] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0777] Step 1:

[0778] The user wears a wearable device to collect physiological data such as body temperature and heart rate. This data is transmitted wirelessly to a terminal. Physiological data is the input, and data transmission to the terminal is the output. The device records the data with a timestamp and periodically transfers it to the terminal.

[0779] Step 2:

[0780] The user acquires facial and audio data through their smartphone's camera and microphone. This activates an emotion engine that analyzes the user's emotional state. The input consists of facial and audio data, and the output is the analyzed emotional state. The emotion recognition algorithm extracts facial features and generates an emotion score.

[0781] Step 3:

[0782] The device integrates collected physiological and emotional information and analyzes the data using an AI algorithm. This process involves data preprocessing, including noise reduction, before the normalized data is input to the AI ​​module. The output provides anomaly detection results compared to the user's normal state. The AI ​​performs pattern recognition and provides evaluations that form the basis for real-time notifications.

[0783] Step 4:

[0784] Based on the analysis results, the device uses a generative AI model to create customized instructions for the user in multiple languages. The input is the analysis results, and the output is instructions displayed on the user's smartphone. This provides the user with an appropriate action plan tailored to their specific health and emotional state.

[0785] Step 5:

[0786] The device applies reinforcement learning techniques to create an optimized activity plan based on the user's preferences and emotional state. The input is user profile data and analysis results, and the output is a personalized activity plan. This allows the user to receive detailed recommendations for tourist destinations and activities.

[0787] Step 6:

[0788] The device utilizes AR / VR technology to provide a visualization of the generated activity plan. The activity plan is the input, and the visualized information is presented to the AR / VR device as output. Based on this information, the user can virtually experience the visited locations and make decisions.

[0789] Step 7:

[0790] The server stores all physiological information, emotional states, and analysis results in the cloud, anonymizing the data. All collected data is the input, and securely stored anonymized data is the output. The server shares this data with international research institutions to help with continuous system improvement.

[0791] (Application Example 2)

[0792] 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".

[0793] Conventional systems struggled to efficiently provide individualized support that considered users' health and emotional states, as well as offer concrete suggestions for daily life actions. Furthermore, the lack of real-time analysis of user data for anomaly detection and the ability to respond quickly to such anomalies posed challenges in maintaining users' health and improving their quality of life. Additionally, the security of data sharing for international research using such systems was insufficient.

[0794] 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.

[0795] In this invention, the server includes means for acquiring biometric information using a wearable sensor device, means for analyzing the acquired biometric information and emotional state in real time and detecting anomalies, means for providing the user with appropriate action suggestions in multiple languages ​​based on the analysis results, means for generating application plans according to the user's health and emotional state, means for providing the generated application plans to the user visually and allowing them to confirm them via a monitoring device, means for anonymizing the accumulated data and securely sharing it with international research facilities, and means for controlling a physical agent capable of performing optimal actions based on the user's biometric information and emotional state. This enables highly personalized support for daily life tailored to the user's health and emotional state.

[0796] A "wearable sensor device" is a device that is attached to a user's body to continuously measure and acquire their biometric information.

[0797] "Biometric information" refers to data that indicates the user's physical condition, such as body temperature, heart rate, and blood oxygen saturation.

[0798] "Emotional state" refers to the user's psychological condition and is information obtained by analyzing facial expressions, voice, and other factors.

[0799] "Real-time analysis" is a process that collects data, performs analysis immediately on the spot, and produces results.

[0800] "Anomaly detection" refers to identifying changes in health or emotions as phenomena that deviate from the standard state based on analyzed data.

[0801] "Action suggestions" refer to recommending activities and behaviors that are appropriate for the user's current health and emotional state.

[0802] "Providing information in multiple languages" refers to a method of translating and distributing information and instructions in multiple languages ​​for users with different native languages.

[0803] An "application plan" refers to specific plans and action proposals that are feasible in daily life, based on the user's situation.

[0804] "Providing information through visual means" refers to a method of presenting information to users visually using images and videos to aid their understanding.

[0805] A "monitor device" is a device that displays information to the user, enabling them to check and operate it.

[0806] "Anonymization" is a process that removes elements that can identify an individual from collected data, thereby protecting privacy.

[0807] An "international research facility" is an organization or institution that conducts research activities and utilizes data across multiple countries.

[0808] A "physical agent" is an artificial entity that controls specific devices or equipment to assist users in performing their actions.

[0809] The system for realizing this invention consists of three parties: a user, a terminal, and a server. The user wears a wearable sensor device to acquire biometric information such as body temperature and heart rate. This allows for continuous monitoring of the user's health status. Furthermore, an emotion recognition algorithm can be used to analyze the user's emotional state in real time from their facial expressions and voice.

[0810] The device analyzes collected biometric information and emotional states in real time using an AI algorithm, detecting deviations from normal states as abnormalities. This enables the generation of appropriate action suggestions based on the user's health and emotional state, and provides information in multiple languages. Suggestions could include, for example, playing music for relaxation or recommending exercises.

[0811] The server securely stores data transmitted from the terminal in the cloud and anonymizes the data. The anonymized data is shared with international research institutions and contributes to research exploring the relationship between emotional states and health. Furthermore, when generating user application plans, reinforcement learning algorithms can be used to provide suggestions optimized for individual preferences. The generated application plans are visually presented to the user through AR / VR technology to aid visual understanding.

[0812] For example, if a user feels stressed after work, the system might suggest playing relaxation music and plan a walking route for the next day. An example of a prompt might be, "Based on the user's biometric information and emotions, let's suggest the most suitable relaxation method. For example, what methods would you suggest if the user is tired?"

[0813] This will enable users to receive appropriate support based on their health and emotional state, thereby improving their quality of life.

[0814] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0815] Step 1:

[0816] The user wears a wearable sensor device. The sensor acquires biometric information such as body temperature and heart rate. The input is the user's physical data, and the output is the acquired biometric information. Based on this information, the sensor continuously collects the user's biometric data and transmits it to the terminal.

[0817] Step 2:

[0818] The device receives collected biometric information and voice input, and uses an emotion recognition algorithm to analyze the user's emotional state. The input is biometric information and voice data, and the output is the user's emotional state. In this process, voice and facial expression data are analyzed, and emotions are identified by AI.

[0819] Step 3:

[0820] The device uses an AI algorithm to analyze acquired biometric information and emotional state in real time, detecting deviations from a normal state as abnormalities. The output is a diagnostic result regarding the user's condition. In this step, data is compared to detect health abnormalities in the user.

[0821] Step 4:

[0822] The device generates appropriate action suggestions based on the analysis results and provides them to the user in multiple languages. The input is the diagnostic result, and the output is a guideline for action suggestions. Specifically, this includes playing relaxation music and providing action recommendations tailored to the user's physical condition.

[0823] Step 5:

[0824] The server receives data transmitted from the terminal in Kitami and stores it in secure cloud storage. The input is anonymized user data, and the output is securely stored data. In this step, the data is anonymized and made shareable with international research institutions.

[0825] Step 6:

[0826] The server uses a reinforcement learning algorithm to generate application plans optimized for the user's interests and preferences. The input consists of collected data and user history, and the output is a individually optimized plan. This process learns from past data and generates suggestions tailored to the user.

[0827] Step 7:

[0828] The generated application plan is visually presented to the user from the device using AR / VR technology. The input is an individually optimized plan, and the output is visual content. In this step, an environment is created in which the user can check the specific details in advance through the visualization of the plan.

[0829] 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.

[0830] 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.

[0831] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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."

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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.

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0850] The following is further disclosed regarding the embodiments described above.

[0851] (Claim 1)

[0852] A means of acquiring biometric information using a wearable biosensor,

[0853] A means of analyzing acquired biometric information in real time and detecting anomalies,

[0854] A means of providing appropriate instructions to the user in multiple languages ​​based on the analysis results,

[0855] A means of generating a sightseeing plan tailored to the user's health condition,

[0856] A means of visually presenting the generated sightseeing plan to the user,

[0857] A means of anonymizing accumulated data and sharing it with international research institutions,

[0858] A system that includes this.

[0859] (Claim 2)

[0860] The system according to claim 1, comprising means for automatically generating a warning and notifying the user in response to the detection of an abnormality in the user's health condition.

[0861] (Claim 3)

[0862] The system according to claim 1, comprising means for providing a plan optimized to the user's preferences using reinforcement learning in the generation of a sightseeing plan.

[0863] "Example 1"

[0864] (Claim 1)

[0865] A means of acquiring biometric data using a wearable information collection device,

[0866] A means for immediately processing acquired biometric data and identifying abnormalities,

[0867] A means of providing users with appropriate instructions in multiple languages ​​based on the processing results,

[0868] A means for generating a travel plan tailored to the user's health condition,

[0869] A means of visually providing the generated travel plan to the user,

[0870] A means of anonymizing stored information and sharing it with international research institutions,

[0871] A means for optimizing travel plans using a generative AI model,

[0872] A means of generating prompt statements to instruct the system's operation,

[0873] A system that includes this.

[0874] (Claim 2)

[0875] The system according to claim 1, comprising means for automatically generating a warning and notifying the user in response to the identification of an abnormality in the user's health condition.

[0876] (Claim 3)

[0877] The system according to claim 1, comprising means for providing a travel plan optimized to the user's preferences using learning technology in the generation of a travel plan.

[0878] "Application Example 1"

[0879] (Claim 1)

[0880] A means of acquiring biometric data using a wearable biosensor,

[0881] A means of analyzing acquired biometric data in real time and detecting anomalies,

[0882] A means of providing appropriate instructions to users in multiple languages ​​based on the analysis results,

[0883] A means of generating activity plans tailored to the user's health condition and proposing a comfortable environment,

[0884] A means of using virtual reality technology to visually present the generated activity plan to the user,

[0885] A means of anonymizing accumulated information and sharing it with international academic research institutions,

[0886] A means of transmitting information to the nearest medical institution in response to the detection of an abnormality in the user's health condition,

[0887] A system that includes this.

[0888] (Claim 2)

[0889] The system according to claim 1, comprising means for automatically generating a warning and notifying the user in response to the detection of an abnormality in the user's health condition.

[0890] (Claim 3)

[0891] The system according to claim 1, comprising means for providing a plan optimized to the user's preferences using learning technology in the generation of an activity plan.

[0892] "Example 2 of combining an emotion engine"

[0893] (Claim 1)

[0894] A means of acquiring physiological information and emotional state using an information gathering device,

[0895] A means of detecting abnormalities by analyzing acquired physiological information and emotional states and comparing them with normal patterns,

[0896] A means of providing users with customized instructions in multiple languages ​​based on the analysis results,

[0897] A means for generating an activity plan based on the user's condition,

[0898] A means of providing the generated activity plan to the user using visual technology,

[0899] A means of anonymizing the collected data and providing it to international research institutions,

[0900] A system that includes this.

[0901] (Claim 2)

[0902] The system according to claim 1, comprising means for automatically generating a warning and providing notification upon detection of an abnormality in health status.

[0903] (Claim 3)

[0904] The system according to claim 1, comprising means for providing a plan optimized to the user's preferences using reinforcement learning techniques in the generation of an activity plan.

[0905] "Application example 2 when combining with an emotional engine"

[0906] (Claim 1)

[0907] A means of acquiring biometric information using a wearable sensor device,

[0908] A means to analyze acquired biometric information and emotional states in real time and detect abnormalities,

[0909] A means of providing users with appropriate action suggestions in multiple languages ​​based on the analysis results,

[0910] A means for generating application plans that correspond to the user's health and emotional state,

[0911] A means of providing the generated application plan to the user visually and allowing them to confirm it via a monitoring device,

[0912] A means to anonymize accumulated data and securely share it with international research institutions,

[0913] A means for controlling a physical agent capable of performing optimal actions based on the user's biometric information and emotional state,

[0914] A system that includes this.

[0915] (Claim 2)

[0916] The system according to claim 1, comprising means for automatically generating a warning and notifying the user in response to anomaly detection based on the user's health status or emotional state.

[0917] (Claim 3)

[0918] The system according to claim 1, comprising means for generating application plans using a reinforcement learning algorithm to make suggestions optimized to the user's preferences. [Explanation of Symbols]

[0919] 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

1. A means of acquiring biometric data using a wearable biosensor, A means of analyzing acquired biometric data in real time and detecting anomalies, A means of providing appropriate instructions to users in multiple languages ​​based on the analysis results, A means of generating activity plans tailored to the user's health condition and proposing a comfortable environment, A means of using virtual reality technology to visually present the generated activity plan to the user, A means of anonymizing accumulated information and sharing it with international academic research institutions, A means of transmitting information to the nearest medical institution in response to the detection of an abnormality in the user's health condition, A system that includes this.

2. The system according to claim 1, comprising means for automatically generating a warning and notifying the user in response to the detection of an abnormality in the user's health condition.

3. The system according to claim 1, comprising means for providing a plan optimized to the user's preferences using learning technology in the generation of an activity plan.

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