system

Abstract

We provide the system. [Solution] An artificial intelligence tool for analyzing biometric information collected from users, A large-scale language processing means for generating diagnostic information in multiple languages ​​based on the aforementioned biometric information, A multilingual interpretation means for presenting the aforementioned diagnostic information to the user and supporting real-time communication with medical professionals, A means for generating personalized plans to optimize tourism behavior based on the user's health status and environmental information, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a 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] It is necessary to solve the difficulties in accessing medical services faced by foreign visitors and foreign residents in Japan, the communication problems due to language barriers, and the difficulties in achieving both medical care and tourism. In particular, the high cost and system complexity associated with multilingual support in medical institutions and real-time provision of medical information are problems. Also, the lack of customized tourism plans based on individual health conditions is an issue.

Means for Solving the Problems

[0005] This invention provides a system having a large-scale language processing means that analyzes biometric information collected from users using artificial intelligence and generates diagnostic information in multiple languages ​​based on the analysis results. Furthermore, this system includes a multilingual interpretation means that presents the diagnostic information to the user and supports real-time communication with medical professionals. In addition, it has a means for generating personalized plans that optimize tourism activities according to the user's health status and environmental information, enabling foreign visitors to Japan to experience medical care and tourism seamlessly. This will eliminate language barriers and enable the provision of high-quality medical services at a low cost.

[0006] "Biometric information" refers to data related to the user's vital functions, such as heart rate, body temperature, and blood pressure.

[0007] "Artificial intelligence means" refers to technologies or algorithms used to analyze input data and perform pattern recognition or anomaly detection.

[0008] "Large-scale language processing means" refers to technologies for understanding and generating natural language, and possesses the function of converting information between multiple languages.

[0009] A "multilingual interpretation method" is a function that accurately translates information between different languages ​​and presents that information in audio or text format.

[0010] "Personalized plan generation method" refers to a technology for creating an optimal action plan tailored to specific conditions, based on the user's health status and environmental circumstances. [Brief explanation of the drawing]

[0011] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, when an emotion engine is combined. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0012] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0013] First, let's explain the terminology used in the following explanation.

[0014] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0015] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0016] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0017] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), and the like.

[0018] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0019] [First Embodiment]

[0020] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0021] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0022] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0023] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0024] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0025] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0026] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0027] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0029] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0030] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0031] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0032] The system of the present invention monitors the user's health status in real time and provides multilingual medical support and travel plans based on that information. The main elements of this system are artificial intelligence means for processing biometric information, multilingual interpretation means using large-scale language processing, and algorithms for generating personalized plans.

[0033] The wearable device used by the user continuously acquires biometric information such as heart rate, body temperature, and blood pressure, and transmits this data to the terminal. Upon receiving the data, the terminal automatically encrypts it and transfers it to the server in a secure state.

[0034] The server utilizes artificial intelligence to analyze received biometric data, detecting anomalies and assessing health status. Based on the analysis results, a large-scale language model is used to generate multilingual diagnostic information. This information is provided to the user via the terminal, and communication with medical professionals is supported as needed. For example, if a doctor explains something in Japanese during a consultation, it is translated into the user's chosen native language and provided in real time.

[0035] Furthermore, the server combines the user's current health status, location information, and environmental information such as weather to suggest the optimal sightseeing plan for each destination. For example, if the user is in good health, it will suggest a plan that includes active activities such as hiking and exploring the local area, while if the user's health is not a concern, it will recommend gentler activities such as visiting museums and art galleries.

[0036] In this way, users can enjoy health-conscious sightseeing while receiving medical services. The system of the present invention is designed to allow foreign visitors to Japan to have a comfortable stay without feeling barriers due to language or cultural differences.

[0037] The following describes the processing flow.

[0038] Step 1:

[0039] Users wear wearable devices while performing their daily activities. The wearable devices measure biometric information such as heart rate, body temperature, and blood pressure in real time and transmit the data to the terminal.

[0040] Step 2:

[0041] The device encrypts biometric information received from wearable devices and transmits the data to the server while protecting privacy. This protects the data from unauthorized access.

[0042] Step 3:

[0043] The server analyzes the received biometric information using an artificial intelligence model. If the analysis detects an abnormal heart rate, it notifies the user of the health risk. It also generates diagnostic information based on the analysis results.

[0044] Step 4:

[0045] The server uses a large-scale language model to translate diagnostic information into multiple languages ​​and generates diagnostic results in the user's selected language. These diagnostic results are accurately communicated in the language specified by the user.

[0046] Step 5:

[0047] The terminal receives multilingual diagnostic information transmitted from the server and presents it to the user. The user can communicate with medical professionals through the terminal, and real-time interpretation is provided as needed.

[0048] Step 6:

[0049] The server comprehensively considers the user's health status, current location, weather information, and other factors to generate the optimal sightseeing plan for the user. It uses reinforcement learning AI to propose personalized plans for each user.

[0050] Step 7:

[0051] The device notifies the user of suggested sightseeing plans and presents options. The user selects activities according to their physical condition and preferences, and prepares to enjoy sightseeing.

[0052] Step 8:

[0053] While the user is sightseeing, the terminal continues to collect biometric information from the wearable device and transmit it to the server. The server monitors this data and immediately issues an alert if any anomalies occur.

[0054] (Example 1)

[0055] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0056] In modern society, understanding health conditions and accurately communicating information in multiple languages ​​are crucial. However, when visitors are placed in different cultural and linguistic environments, obtaining real-time health information and communicating smoothly with local experts can be difficult. Furthermore, without the ability to develop appropriate action plans tailored to their health condition, effective health maintenance and optimization of the tourism experience become challenging. A comprehensive system is needed to address these challenges.

[0057] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0058] In this invention, the server includes information technology means for processing biometric information acquired from the user, large-scale information processing means for creating diagnostic data in multiple languages ​​based on the biometric information, and multilingual translation means for providing the diagnostic data to the user and supporting real-time communication with experts. As a result, the user can grasp their health status in real time, communicate smoothly with experts over language barriers, and develop an individualized action plan, thereby achieving optimal health maintenance and enjoying the experience.

[0059] "Information technology means" refers to technical elements for analyzing and processing biometric information obtained from users, and is a device or system that utilizes computer science and artificial intelligence technology.

[0060] "Large-scale information processing means" refers to technological elements that process large amounts of data quickly and efficiently in order to create multilingual diagnostic data, and utilize natural language processing models and machine learning algorithms.

[0061] A "multilingual translation means" is a system or device that has translation technology to provide users with diagnostic data in multiple languages ​​of their choice and to support communication with experts as needed.

[0062] "Individualized plan generation means" refers to a technological element for formulating an optimal action plan that takes into account the user's health status and environmental information, and is an algorithm-based planning system.

[0063] Users acquire biometric information in real time using wearable sensors. This includes data such as heart rate, body temperature, and blood pressure, which is transmitted to a device via Bluetooth or Wi-Fi. The device uses AES technology to encrypt the received data and securely transmits it to a server. The server runs a system that analyzes the biometric information using information technology tools such as natural language processing and machine learning. This enables the assessment of health status and the detection of abnormal values.

[0064] The analyzed results are processed through a generative AI model as a large-scale information processing tool, generating multilingual diagnostic data as needed. Leveraging a large-scale language model (e.g., GPT-3®), diagnostic information is provided in the user's chosen language. This data is presented to the user on the device in audio or text format, and multilingual translation tools support real-time communication with experts as needed. For example, a translation API can be used to display health information provided in Japanese in English.

[0065] Furthermore, using a personalized plan generation mechanism, the server formulates an optimal action plan considering conditions such as the user's health status, location, and weather. For example, if the user is in good health and able to engage in outdoor activities, it will suggest plans for hiking or sightseeing. On the other hand, if the user is not feeling well, it will recommend activities in quiet places such as art museums or museums.

[0066] As a concrete example, the prompt message might read, "A doctor is explaining about high blood pressure in Japanese. Please translate this information into English for the user in real time." This would enable a system that allows users to monitor their health while enjoying a richer, safer, and more comfortable sightseeing experience.

[0067] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0068] Step 1:

[0069] The user acquires biometric information (heart rate, body temperature, blood pressure, etc.) from a wearable sensor. This data is transmitted to a terminal. The terminal receives this information via Bluetooth or Wi-Fi, encrypts it using AES technology, and ensures security. In this step, biometric information is received as input, and encrypted data is prepared as output.

[0070] Step 2:

[0071] The device sends encrypted biometric information to the server. The HTTPS protocol is used here to ensure the confidentiality of the information. Upon receiving the data, the server uses behavioral information technology (ICT) to analyze the biometric information. Specifically, AI algorithms are used to analyze the data, detecting anomalies and evaluating health status. The input for this step is encrypted biometric information, and the output is analyzed health status data.

[0072] Step 3:

[0073] Based on the analysis results, the server generates multilingual diagnostic data using large-scale information processing capabilities. It utilizes a generation AI model (e.g., GPT-3) to create the content in the user-specified language. The output is diagnostic information written in the selected language.

[0074] Step 4:

[0075] The terminal receives multilingual diagnostic information sent from the server. This information is displayed in the format chosen by the user (audio or text), and communication with experts is supported using multilingual translation tools. Specifically, real-time interpretation is possible through a translation API. Diagnostic information is received as input, and the information is presented to the user visually or audibly as output.

[0076] Step 5:

[0077] The server generates personalized action plans based on the user's health status, location, and environmental information such as weather. The algorithm formulates an optimal sightseeing plan and suggests recommended activities that take health management into consideration. The specific output is an action plan that includes details of activities such as hiking or visiting museums.

[0078] Through these steps, users can manage their health while facilitating smooth communication with local experts and achieving the best possible travel experience.

[0079] (Application Example 1)

[0080] 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."

[0081] In medical tourism, users often face difficulties in obtaining information smoothly and adapting to activities in the local area due to language barriers and health conditions. For foreign travelers in particular, language barriers and changes in health conditions are stressful issues. To solve this problem, a system is needed that utilizes users' biometric information to provide appropriate diagnostic information and travel plans in real time.

[0082] 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.

[0083] In this invention, the server includes data analysis means for analyzing biometric information collected from the user, natural language processing means for generating diagnostic information in multiple languages ​​based on the biometric information, and location information processing means for providing recommended activities within the city using the user's location information. This enables the user to enjoy appropriate sightseeing activities without experiencing language barriers while maintaining their health.

[0084] "Data analysis means" refers to a device or method that analyzes biometric information collected from users to detect abnormalities or evaluate their health status.

[0085] "Natural language processing means" refers to technologies or methods that generate medical diagnostic information in multiple languages ​​and convert it into a language that the user can understand.

[0086] "Translation means" refers to a device or method that has the function of automatically converting information into a language selected by the user and presenting it in audio or text format.

[0087] A "plan generation method" refers to a technology or function that formulates an action plan suitable for the user based on the user's health status and environmental information.

[0088] "Location information processing means" refers to a technology or method that utilizes a user's location information to suggest activities that are appropriate for the surrounding environment.

[0089] The system implementing this invention comprehensively provides health monitoring, multilingual support, and optimization of travel plans. Its main components include a wearable device carried by the user, a terminal (smartphone or smart glasses), and a server for processing data.

[0090] Wearable devices continuously collect biometric information such as the user's heart rate, body temperature, and blood pressure. The device receives this data using communication methods such as Bluetooth, encrypts it, and securely transmits it to a server.

[0091] The server uses an AI analysis engine built in Python to detect abnormal values ​​from biometric data and assess health status. The analyzed information is converted into multilingual diagnostic information using natural language processing technology. At this stage, a generative AI model is utilized to perform language conversion based on prompt text. Users can receive this information in real time via voice or text, supporting effective communication with healthcare professionals.

[0092] Furthermore, the server, through a plan generation mechanism, combines the user's current health status, geographical location, and surrounding environment data to provide an optimized sightseeing plan. This allows users to enjoy sightseeing to the fullest while maintaining their health. For example, if a user's heart rate is normal but their body temperature is slightly elevated, a plan such as "Visit a cool museum" might be suggested.

[0093] A concrete example of a prompt message would be something like, "The user's heart rate is 85, body temperature is 37.2 degrees, and current location is Shinjuku. Please suggest an appropriate activity." This invention enables safe and comfortable health management and sightseeing experiences even in cross-cultural environments.

[0094] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0095] Step 1:

[0096] The user's wearable device collects biometric information such as heart rate, body temperature, and blood pressure. The collected data is transmitted to the terminal via Bluetooth. The input is biometric information, and the output is data transfer to the terminal.

[0097] Step 2:

[0098] The terminal encrypts the received biometric information and transfers it to the server via a secure communication method. The input is biometric information from a wearable device, which is encrypted as part of the data processing, and the output is secure data transmission to the server.

[0099] Step 3:

[0100] The server uses an AI analysis engine to analyze biometric data, detect anomalies, and assess health status. The input is biometric data received from the terminal, health assessment is performed through data calculations, and the output is the analyzed health information.

[0101] Step 4:

[0102] Using natural language processing, the server converts analyzed health information into multilingual diagnostic information. The input is analyzed health information, language conversion is performed using a generative AI model, and the output is multilingual diagnostic information.

[0103] Step 5:

[0104] The server sends the generated diagnostic information to the terminal, and the user receives the information in audio or text format. Input is multilingual diagnostic information, and output is provided in the format selected by the user.

[0105] Step 6:

[0106] The server uses a plan generation method that combines the user's current location and environmental information to optimize the sightseeing plan. The input is the user's location and health status, and the optimal sightseeing plan is generated through data processing; the output is a customized sightseeing plan.

[0107] Step 7:

[0108] The server sends an optimized sightseeing plan to the terminal, and the user reviews the plan and adjusts their actions accordingly. The input is the optimized sightseeing plan, and the output is the user's reflection of their action plan.

[0109] 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.

[0110] This invention aims to realize a system that provides more accurate diagnoses and personalized services by evaluating not only the user's health status but also their emotional state. This system is designed to provide users with customized diagnoses and travel plans by combining biometric information analysis and emotion recognition. The main components include artificial intelligence means, large-scale language processing means, multilingual interpretation means, personalized plan generation means, and an emotion engine.

[0111] Users continuously collect biometric information such as heart rate and body temperature through wearable devices. This information is transmitted to a server via the device. The server uses artificial intelligence to evaluate the user's health status based on this biometric information.

[0112] Meanwhile, the emotion engine analyzes the user's voice and text data to evaluate their emotional state. This emotion analysis is used to generate diagnostic information and respond to the user. For example, if the diagnostic results are likely to induce anxiety, the emotion engine adjusts the wording to provide a sense of reassurance.

[0113] The server generates diagnostic information in multiple languages, taking into account the user's health and emotional state, and provides it to the user through the terminal. It supports real-time communication in the user's chosen language, ensuring smooth interaction with medical professionals. Based on the emotional state, emotional tone is added to the translated content as needed.

[0114] Furthermore, the server generates a sightseeing plan based on the user's health and emotional state. The plan is dynamically adjusted according to the user's sensitivities; for example, if the emotional state indicates a need for relaxation, it suggests visiting calmer tourist destinations.

[0115] This system will allow users to have a more fulfilling medical and tourism experience, and will provide an environment where foreign visitors can overcome language and emotional barriers and enjoy their stay in Japan with peace of mind.

[0116] The following describes the processing flow.

[0117] Step 1:

[0118] Users wear wearable devices while going about their daily lives. The wearable devices collect biometric information such as heart rate, body temperature, and blood pressure in real time and transmit it to the device.

[0119] Step 2:

[0120] The terminal encrypts the received biometric information and securely transmits it to the server. During this process, it verifies data integrity and performs redundant processing to prevent data loss.

[0121] Step 3:

[0122] The server receives biometric information and analyzes the user's health status using artificial intelligence. Based on the analysis results, it detects abnormal health indicators and sends alerts to medical institutions as needed.

[0123] Step 4:

[0124] The device collects voice and text data spoken by the user and sends it to the server. The server uses an emotion engine to analyze this data and recognize the user's emotional state.

[0125] Step 5:

[0126] The server generates multilingual diagnostic information based on the analyzed health and emotional states. The diagnostic information is adjusted according to the emotional state to include expressions that alleviate the user's anxiety.

[0127] Step 6:

[0128] The server uses large-scale language processing to translate diagnostic information into multiple languages ​​and sends it to the user's terminal. The terminal then presents this information to the user, supporting real-time communication with healthcare professionals.

[0129] Step 7:

[0130] The server generates sightseeing plans by combining the user's health status, emotional state, location information, and weather information. Reinforcement learning AI suggests the optimal plan based on the user's preferences and sensibilities.

[0131] Step 8:

[0132] The device presents the user with a generated sightseeing plan and offers options. It considers the user's emotional state to present the plan in an engaging way and assist in their selection.

[0133] Step 9:

[0134] While sightseeing, the device continues to collect biometric information from the wearable device and transmit it to the server. The server monitors this data, checks the user's health status in real time, and sends appropriate feedback as needed.

[0135] (Example 2)

[0136] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0137] In the modern healthcare and travel industries, there is a growing need to simultaneously understand users' health and emotional states and provide personalized diagnostic information and travel plans. However, conventional systems have struggled to integrate and analyze biometric and emotional data effectively, and to provide diagnoses and travel plans in multiple languages. Furthermore, they lacked sufficient automatic detection of abnormal data and real-time conversational support in the user's preferred language.

[0138] 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.

[0139] In this invention, the server includes intelligent means for analyzing biometric data collected from the user, language processing means for generating diagnostic guidance in multiple languages ​​based on the biometric data, and means for analyzing the user's emotional information using an emotion engine and adjusting the diagnostic guidance. This allows the user to quickly receive personalized diagnostic information based on their health and emotional state in multiple languages, and enables smooth communication with experts in real time.

[0140] A "user" is an entity that provides biometric data and emotional information and receives services from the system.

[0141] "Biometric data" refers to information that indicates the user's physical condition, such as heart rate and body temperature.

[0142] An "intelligent tool" is a system that uses artificial intelligence technology to analyze biometric data and perform processing to evaluate health status.

[0143] "Language processing means" refers to technology for expressing diagnostic guidance generated based on biometric data in multiple languages.

[0144] An "emotion engine" is a technology that analyzes emotional information from a user's voice or text and evaluates their emotional state.

[0145] A "diagnostic guide" is a document that organizes and provides information about the user's health status, and is presented in multiple languages.

[0146] "Interpretation methods" refer to technologies that translate diagnostic guidance and conversations with experts into the user's chosen language and present them in audio or text format.

[0147] An "action plan" refers to a travel or activity plan optimized based on the user's health status and emotional information.

[0148] This invention is a system that comprehensively analyzes a user's health and emotional state. The user wears a wearable device to collect biometric data such as heart rate and body temperature. This data is transmitted to a server via the terminal. The server analyzes this biometric data using artificial intelligence means and evaluates the user's health state.

[0149] Meanwhile, the user inputs voice or text data through their device. The server uses an emotion engine to analyze this data and evaluate the user's emotional state. This emotional information is used to adjust diagnostic guidance and respond to the user. The emotion engine utilizes natural language processing technology to identify emotions such as positive and negative from the input data.

[0150] By using a generative AI model, the server generates diagnostic guidance in multiple languages ​​based on the user's health and emotional state. The terminal automatically translates this information into the user's selected language and provides it to the user in voice or text format. This enables users to communicate with experts in real time, overcoming language barriers.

[0151] Furthermore, the server uses personalized guidance generation to formulate an action plan tailored to the user's health and emotional state. For example, if the user is seeking relaxation, it can recommend visiting a quiet tourist destination.

[0152] For example, if a user enters the prompt "I've been busy lately and want to relax," the server will analyze their emotional state and suggest a travel plan to promote relaxation. This allows users to receive services optimized according to their health and emotional state.

[0153] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0154] Step 1:

[0155] Users collect biometric data such as heart rate and body temperature using wearable devices. The collected data is transmitted to the terminal in real time. The input is biometric data, which serves as the initial data for the system.

[0156] Step 2:

[0157] The device transmits the received biometric data to the server. The device transmits the data via Bluetooth or Wi-Fi, and it is securely transmitted to the server. The input is the biometric data acquired by the device, and the output is the data transfer to the server.

[0158] Step 3:

[0159] The server analyzes biometric data using intelligent means. Specifically, it applies AI algorithms to evaluate the user's health status. For example, it checks for abnormalities in pulse rate and calculates health indicators. The input is biometric data acquired from the terminal, and the output is the health evaluation result.

[0160] Step 4:

[0161] The user provides voice or text data to the device to input their emotional state. This records the user's current emotions. The input is voice or text, and the output is the transmission of emotion data to the server.

[0162] Step 5:

[0163] The server uses an emotion engine to analyze emotion data. It analyzes input speech and text using natural language processing to identify emotion categories (positive, negative, etc.). The input is emotion data, and the output is an emotion evaluation result.

[0164] Step 6:

[0165] The server integrates health and emotional states to generate diagnostic guidance. Using a generative AI model, it creates diagnostic guidance expressed in multiple languages. The input consists of health assessment results and emotional assessment results, and the output is multilingual diagnostic guidance.

[0166] Step 7:

[0167] The terminal receives diagnostic guidance generated from the server and presents it to the user. The diagnostic guidance is automatically provided in the language selected by the user. The input is multilingual diagnostic guidance, and the output is information presented to the user.

[0168] Step 8:

[0169] The server generates an action plan based on the user's health and emotional state. Using a personalized guidance generation method, it can suggest quiet tourist destinations if the user is seeking relaxation. The input is the health assessment result and the emotional assessment result, and the output is an individualized action plan.

[0170] (Application Example 2)

[0171] 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 device 14 will be referred to as the "terminal."

[0172] In modern society, there is a challenge in that users find it difficult to accurately assess their own health and emotional state and to receive appropriate health care and relaxation at home based on that assessment. Furthermore, there is a challenge in how to present information combining health and emotional states to users in an easily understandable way and provide personalized services.

[0173] 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.

[0174] In this invention, the server includes data processing means for analyzing biometric information collected from the user, information generation means for providing personalized health care and entertainment based on the biometric information and emotional state, and response support means for presenting the generated information to the user and supporting dialogue. This enables the user to receive personalized services tailored to their health and emotional state in real time at home, thereby improving their quality of life.

[0175] "Data processing means" refers to a device or method for analyzing biometric information collected from a user and evaluating their health status and emotional state.

[0176] "Information generation means" refers to a device or method for creating information to provide personalized health care or entertainment based on biological information and emotional states.

[0177] "Response support means" refers to a device or method for presenting generated information to the user and facilitating smooth dialogue with the user.

[0178] "Adjustment means" refers to a device or method for optimizing the user's behavior and environment based on their health and emotional state.

[0179] The system for carrying out this invention evaluates the user's biometric information and emotional state and provides personalized services based on that evaluation. The main components of the system are data processing means, information generation means, response support means, and adjustment means. The following describes how these components work together.

[0180] Users continuously collect biometric information such as heart rate and body temperature using wearable devices. This data is transmitted to a server via a smartphone. The server analyzes the biometric information using data processing tools to evaluate the user's health and emotional state. AI models such as TENSORFLOW® and PyTorch are used for this analysis.

[0181] The server's information generation mechanism generates personalized health care and entertainment suggestions based on evaluation results. This information is generated in multiple languages ​​using the Google Cloud Translation API. For example, if a user needs relaxation, the server might suggest calming music or visual content.

[0182] The generated information is presented to the user by a response support system. This process allows for dialogue via voice or text, and the information is automatically converted to the user's preferred format as needed. For example, if it is determined that the user is experiencing stress, a suggestion such as, "Shall we play some calming music today?" might be made.

[0183] An example of a prompt would be, "Design a dialogue flow for an AI model that suggests relaxing music when the user is feeling stressed." This would allow the user to enjoy a personalized experience and support relaxation at home.

[0184] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0185] Step 1:

[0186] The user obtains biometric information (heart rate, body temperature, etc.) from a wearable device. This data is transmitted in real time to a server via a smartphone. The input is biometric information from the wearable device, and the output is biometric data stored on the server. Data transfer is performed via Bluetooth or Wi-Fi.

[0187] Step 2:

[0188] The server analyzes the received biometric information using data processing tools to evaluate the user's health status. This process utilizes an AI model, with data processing performed using either TensorFlow or PyTorch. The input is biometric data stored on the server, and the output is the health status evaluation result. The analyzed data is added to the user's health status list.

[0189] Step 3:

[0190] The server uses emotional information obtained from voice or text messages to determine the user's emotional state. This information is processed by an emotion recognition engine. The input is voice or text data, and the output is an evaluation of the user's emotional state. Natural language processing techniques are used for processing, and the data is stored as an indicator of emotion.

[0191] Step 4:

[0192] The server combines health and emotional state assessments and uses information generation tools to suggest personalized health care and entertainment. Multilingual content is also generated using the Google Cloud Translation API. Input is health and emotional assessment results, and output is personalized suggestion information. This information is prepared along with entertainment categories.

[0193] Step 5:

[0194] The terminal presents the user with personalized suggestion information received from the server. Response support means enable interaction via voice or text. Input is suggestion information from the server, and output is information presented to the user on the terminal. This presentation aims to create a relaxing environment for the user.

[0195] 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.

[0196] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0197] 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.

[0198] [Second Embodiment]

[0199] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0200] 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.

[0201] 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).

[0202] 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.

[0203] 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.

[0204] 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).

[0205] 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.

[0206] 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.

[0207] 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.

[0208] 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.

[0209] 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.

[0210] 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".

[0211] The system of the present invention monitors the user's health status in real time and provides multilingual medical support and travel plans based on that information. The main elements of this system are artificial intelligence means for processing biometric information, multilingual interpretation means using large-scale language processing, and algorithms for generating personalized plans.

[0212] The wearable device used by the user continuously acquires biometric information such as heart rate, body temperature, and blood pressure, and transmits this data to the terminal. Upon receiving the data, the terminal automatically encrypts it and transfers it to the server in a secure state.

[0213] The server utilizes artificial intelligence to analyze received biometric data, detecting anomalies and assessing health status. Based on the analysis results, a large-scale language model is used to generate multilingual diagnostic information. This information is provided to the user via the terminal, and communication with medical professionals is supported as needed. For example, if a doctor explains something in Japanese during a consultation, it is translated into the user's chosen native language and provided in real time.

[0214] Furthermore, the server combines the user's current health status, location information, and environmental information such as weather to suggest the optimal sightseeing plan for each destination. For example, if the user is in good health, it will suggest a plan that includes active activities such as hiking and exploring the local area, while if the user's health is not a concern, it will recommend gentler activities such as visiting museums and art galleries.

[0215] In this way, users can enjoy health-conscious sightseeing while receiving medical services. The system of the present invention is designed to allow foreign visitors to Japan to have a comfortable stay without feeling barriers due to language or cultural differences.

[0216] The following describes the processing flow.

[0217] Step 1:

[0218] Users wear wearable devices while performing their daily activities. The wearable devices measure biometric information such as heart rate, body temperature, and blood pressure in real time and transmit the data to the terminal.

[0219] Step 2:

[0220] The device encrypts biometric information received from wearable devices and transmits the data to the server while protecting privacy. This protects the data from unauthorized access.

[0221] Step 3:

[0222] The server analyzes the received biometric information using an artificial intelligence model. If the analysis detects an abnormal heart rate, it notifies the user of the health risk. It also generates diagnostic information based on the analysis results.

[0223] Step 4:

[0224] The server uses a large-scale language model to translate diagnostic information into multiple languages ​​and generates diagnostic results in the user's selected language. These diagnostic results are accurately communicated in the language specified by the user.

[0225] Step 5:

[0226] The terminal receives multilingual diagnostic information transmitted from the server and presents it to the user. The user can communicate with medical professionals through the terminal, and real-time interpretation is provided as needed.

[0227] Step 6:

[0228] The server comprehensively considers the user's health status, current location, weather information, and other factors to generate the optimal sightseeing plan for the user. It uses reinforcement learning AI to propose personalized plans for each user.

[0229] Step 7:

[0230] The device notifies the user of suggested sightseeing plans and presents options. The user selects activities according to their physical condition and preferences, and prepares to enjoy sightseeing.

[0231] Step 8:

[0232] While the user is sightseeing, the terminal continues to collect biometric information from the wearable device and transmit it to the server. The server monitors this data and immediately issues an alert if any anomalies occur.

[0233] (Example 1)

[0234] 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."

[0235] In modern society, understanding health conditions and accurately communicating information in multiple languages ​​are crucial. However, when visitors are placed in different cultural and linguistic environments, obtaining real-time health information and communicating smoothly with local experts can be difficult. Furthermore, without the ability to develop appropriate action plans tailored to their health condition, effective health maintenance and optimization of the tourism experience become challenging. A comprehensive system is needed to address these challenges.

[0236] 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.

[0237] In this invention, the server includes information technology means for processing biometric information acquired from the user, large-scale information processing means for creating diagnostic data in multiple languages ​​based on the biometric information, and multilingual translation means for providing the diagnostic data to the user and supporting real-time communication with experts. As a result, the user can grasp their health status in real time, communicate smoothly with experts over language barriers, and develop an individualized action plan, thereby achieving optimal health maintenance and enjoying the experience.

[0238] "Information technology means" refers to technical elements for analyzing and processing biometric information obtained from users, and is a device or system that utilizes computer science and artificial intelligence technology.

[0239] "Large-scale information processing means" refers to technological elements that process large amounts of data quickly and efficiently in order to create multilingual diagnostic data, and utilize natural language processing models and machine learning algorithms.

[0240] A "multilingual translation means" is a system or device that has translation technology to provide users with diagnostic data in multiple languages ​​of their choice and to support communication with experts as needed.

[0241] "Individualized plan generation means" refers to a technological element for formulating an optimal action plan that takes into account the user's health status and environmental information, and is an algorithm-based planning system.

[0242] Users acquire biometric information in real time using wearable sensors. This includes data such as heart rate, body temperature, and blood pressure, which is transmitted to a device via Bluetooth or Wi-Fi. The device uses AES technology to encrypt the received data and securely transmits it to a server. The server runs a system that analyzes the biometric information using information technology tools such as natural language processing and machine learning. This enables the assessment of health status and the detection of abnormal values.

[0243] The analyzed results are processed through a generative AI model as a large-scale information processing tool, generating multilingual diagnostic data as needed. Leveraging a large-scale language model (e.g., GPT-3), diagnostic information is provided in the user's chosen language. This data is presented to the user on the device in audio or text format, and multilingual translation tools support real-time communication with experts as needed. For example, a translation API can be used to display health information provided in Japanese in English.

[0244] Furthermore, using a personalized plan generation mechanism, the server formulates an optimal action plan considering conditions such as the user's health status, location, and weather. For example, if the user is in good health and able to engage in outdoor activities, it will suggest plans for hiking or sightseeing. On the other hand, if the user is not feeling well, it will recommend activities in quiet places such as art museums or museums.

[0245] As a concrete example, the prompt message might read, "A doctor is explaining about high blood pressure in Japanese. Please translate this information into English for the user in real time." This would enable a system that allows users to monitor their health while enjoying a richer, safer, and more comfortable sightseeing experience.

[0246] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0247] Step 1:

[0248] The user acquires biometric information (heart rate, body temperature, blood pressure, etc.) from a wearable sensor. This data is transmitted to a terminal. The terminal receives this information via Bluetooth or Wi-Fi, encrypts it using AES technology, and ensures security. In this step, biometric information is received as input, and encrypted data is prepared as output.

[0249] Step 2:

[0250] The device sends encrypted biometric information to the server. The HTTPS protocol is used here to ensure the confidentiality of the information. Upon receiving the data, the server uses behavioral information technology (ICT) to analyze the biometric information. Specifically, AI algorithms are used to analyze the data, detecting anomalies and evaluating health status. The input for this step is encrypted biometric information, and the output is analyzed health status data.

[0251] Step 3:

[0252] Based on the analysis results, the server generates multilingual diagnostic data using large-scale information processing capabilities. It utilizes a generation AI model (e.g., GPT-3) to create the content in the user-specified language. The output is diagnostic information written in the selected language.

[0253] Step 4:

[0254] The terminal receives multilingual diagnostic information sent from the server. This information is displayed in the format chosen by the user (audio or text), and communication with experts is supported using multilingual translation tools. Specifically, real-time interpretation is possible through a translation API. Diagnostic information is received as input, and the information is presented to the user visually or audibly as output.

[0255] Step 5:

[0256] The server generates personalized action plans based on the user's health status, location, and environmental information such as weather. The algorithm formulates an optimal sightseeing plan and suggests recommended activities that take health management into consideration. The specific output is an action plan that includes details of activities such as hiking or visiting museums.

[0257] Through these steps, users can manage their health while facilitating smooth communication with local experts and achieving the best possible travel experience.

[0258] (Application Example 1)

[0259] 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."

[0260] In medical tourism, users often face difficulties in obtaining information smoothly and adapting to activities in the local area due to language barriers and health conditions. For foreign travelers in particular, language barriers and changes in health conditions are stressful issues. To solve this problem, a system is needed that utilizes users' biometric information to provide appropriate diagnostic information and travel plans in real time.

[0261] 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.

[0262] In this invention, the server includes data analysis means for analyzing biometric information collected from the user, natural language processing means for generating diagnostic information in multiple languages ​​based on the biometric information, and location information processing means for providing recommended activities within the city using the user's location information. This enables the user to enjoy appropriate sightseeing activities without experiencing language barriers while maintaining their health.

[0263] "Data analysis means" refers to a device or method that analyzes biometric information collected from users to detect abnormalities or evaluate their health status.

[0264] "Natural language processing means" refers to technologies or methods that generate medical diagnostic information in multiple languages ​​and convert it into a language that the user can understand.

[0265] "Translation means" refers to a device or method that has the function of automatically converting information into a language selected by the user and presenting it in audio or text format.

[0266] A "plan generation method" refers to a technology or function that formulates an action plan suitable for the user based on the user's health status and environmental information.

[0267] "Location information processing means" refers to a technology or method that utilizes a user's location information to suggest activities that are appropriate for the surrounding environment.

[0268] The system implementing this invention comprehensively provides health monitoring, multilingual support, and optimization of travel plans. Its main components include a wearable device carried by the user, a terminal (smartphone or smart glasses), and a server for processing data.

[0269] Wearable devices continuously collect biometric information such as the user's heart rate, body temperature, and blood pressure. The device receives this data using communication methods such as Bluetooth, encrypts it, and securely transmits it to a server.

[0270] The server uses an AI analysis engine built in Python to detect abnormal values ​​from biometric data and assess health status. The analyzed information is converted into multilingual diagnostic information using natural language processing technology. At this stage, a generative AI model is utilized to perform language conversion based on prompt text. Users can receive this information in real time via voice or text, supporting effective communication with healthcare professionals.

[0271] Furthermore, the server, through a plan generation mechanism, combines the user's current health status, geographical location, and surrounding environment data to provide an optimized sightseeing plan. This allows users to enjoy sightseeing to the fullest while maintaining their health. For example, if a user's heart rate is normal but their body temperature is slightly elevated, a plan such as "Visit a cool museum" might be suggested.

[0272] A concrete example of a prompt message would be something like, "The user's heart rate is 85, body temperature is 37.2 degrees, and current location is Shinjuku. Please suggest an appropriate activity." This invention enables safe and comfortable health management and sightseeing experiences even in cross-cultural environments.

[0273] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0274] Step 1:

[0275] The user's wearable device collects biometric information such as heart rate, body temperature, and blood pressure. The collected data is transmitted to the terminal via Bluetooth. The input is biometric information, and the output is data transfer to the terminal.

[0276] Step 2:

[0277] The terminal encrypts the received biometric information and transfers it to the server via a secure communication method. The input is biometric information from a wearable device, which is encrypted as part of the data processing, and the output is secure data transmission to the server.

[0278] Step 3:

[0279] The server uses an AI analysis engine to analyze biometric information, detect abnormal values, and evaluate the health status. The input is the biometric information received from the terminal, the health assessment is performed through data calculation, and the output is the analyzed health information.

[0280] Step 4:

[0281] Using natural language processing means, the server converts the analyzed health information into diagnostic information in multiple languages. The input is the analyzed health information, language conversion is performed using a generated AI model, and the output is diagnostic information in multiple languages.

[0282] Step 5:

[0283] The server transmits the generated diagnostic information to the terminal, and the user obtains the information in voice or text form. The input is the diagnostic information in multiple languages, and the output is the information provided in the form selected by the user.

[0284] Step 6:

[0285] The server combines the user's current location information and environmental information and uses a planning generation means to optimize the tourism plan. The input is the user's location information and health status, an optimal tourism plan is generated through data processing, and the output is a customized tourism plan.

[0286] Step 7:

[0287] The server sends the optimized tourism plan to the terminal, and the user checks the plan and adjusts their actions. The input is the optimized tourism plan, and the output is the reflection in the user's action plan.

[0288] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform specific processing using the user's emotion.

[0289] This invention aims to realize a system that provides more accurate diagnoses and personalized services by evaluating not only the user's health status but also their emotional state. This system is designed to provide users with customized diagnoses and travel plans by combining biometric information analysis and emotion recognition. The main components include artificial intelligence means, large-scale language processing means, multilingual interpretation means, personalized plan generation means, and an emotion engine.

[0290] Users continuously collect biometric information such as heart rate and body temperature through wearable devices. This information is transmitted to a server via the device. The server uses artificial intelligence to evaluate the user's health status based on this biometric information.

[0291] Meanwhile, the emotion engine analyzes the user's voice and text data to evaluate their emotional state. This emotion analysis is used to generate diagnostic information and respond to the user. For example, if the diagnostic results are likely to induce anxiety, the emotion engine adjusts the wording to provide a sense of reassurance.

[0292] The server generates diagnostic information in multiple languages, taking into account the user's health and emotional state, and provides it to the user through the terminal. It supports real-time communication in the user's chosen language, ensuring smooth interaction with medical professionals. Based on the emotional state, emotional tone is added to the translated content as needed.

[0293] Furthermore, the server generates a sightseeing plan based on the user's health and emotional state. The plan is dynamically adjusted according to the user's sensitivities; for example, if the emotional state indicates a need for relaxation, it suggests visiting calmer tourist destinations.

[0294] This system will allow users to have a more fulfilling medical and tourism experience, and will provide an environment where foreign visitors can overcome language and emotional barriers and enjoy their stay in Japan with peace of mind.

[0295] The following describes the processing flow.

[0296] Step 1:

[0297] Users wear wearable devices while going about their daily lives. The wearable devices collect biometric information such as heart rate, body temperature, and blood pressure in real time and transmit it to the device.

[0298] Step 2:

[0299] The terminal encrypts the received biometric information and securely transmits it to the server. During this process, it verifies data integrity and performs redundant processing to prevent data loss.

[0300] Step 3:

[0301] The server receives biometric information and analyzes the user's health status using artificial intelligence. Based on the analysis results, it detects abnormal health indicators and sends alerts to medical institutions as needed.

[0302] Step 4:

[0303] The device collects voice and text data spoken by the user and sends it to the server. The server uses an emotion engine to analyze this data and recognize the user's emotional state.

[0304] Step 5:

[0305] The server generates multilingual diagnostic information based on the analyzed health and emotional states. The diagnostic information is adjusted according to the emotional state to include expressions that alleviate the user's anxiety.

[0306] Step 6:

[0307] The server uses large-scale language processing to translate diagnostic information into multiple languages ​​and sends it to the user's terminal. The terminal then presents this information to the user, supporting real-time communication with healthcare professionals.

[0308] Step 7:

[0309] The server combines the user's health status, emotional state, location information, and weather information to generate a travel plan. Based on the reinforcement learning AI, an optimal plan based on the user's preferences and sensitivities is proposed.

[0310] Step 8:

[0311] The terminal presents the generated travel plan to the user and provides options. Considering the user's emotional state, the plan is introduced in an interesting way to assist in the selection.

[0312] Step 9:

[0313] Even during the trip, the terminal continues to collect biometric information from the wearable device and transmits it to the server. The server monitors the data and monitors the user's health status in real time, and transmits appropriate feedback as needed.

[0314] (Example 2)

[0315] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0316] In the modern medical and travel industries, there is an increasing need to simultaneously grasp the user's health status and emotional state and provide personalized diagnostic information and travel plans. However, in conventional systems, it has been difficult to integrally analyze biometric data and emotional information and effectively provide diagnoses and travel plans in multiple languages. Furthermore, automatic detection of abnormal data and real-time dialogue support in the language desired by the user have been insufficient.

[0317] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following respective means.

[0318] In this invention, the server includes intelligent means for analyzing biometric data collected from the user, language processing means for generating diagnostic guidance in multiple languages ​​based on the biometric data, and means for analyzing the user's emotional information using an emotion engine and adjusting the diagnostic guidance. This allows the user to quickly receive personalized diagnostic information based on their health and emotional state in multiple languages, and enables smooth communication with experts in real time.

[0319] A "user" is an entity that provides biometric data and emotional information and receives services from the system.

[0320] "Biometric data" refers to information that indicates the user's physical condition, such as heart rate and body temperature.

[0321] An "intelligent tool" is a system that uses artificial intelligence technology to analyze biometric data and perform processing to evaluate health status.

[0322] "Language processing means" refers to technology for expressing diagnostic guidance generated based on biometric data in multiple languages.

[0323] An "emotion engine" is a technology that analyzes emotional information from a user's voice or text and evaluates their emotional state.

[0324] A "diagnostic guide" is a document that organizes and provides information about the user's health status, and is presented in multiple languages.

[0325] "Interpretation methods" refer to technologies that translate diagnostic guidance and conversations with experts into the user's chosen language and present them in audio or text format.

[0326] An "action plan" refers to a travel or activity plan optimized based on the user's health status and emotional information.

[0327] This invention is a system that comprehensively analyzes a user's health and emotional state. The user wears a wearable device to collect biometric data such as heart rate and body temperature. This data is transmitted to a server via the terminal. The server analyzes this biometric data using artificial intelligence means and evaluates the user's health state.

[0328] Meanwhile, the user inputs voice or text data through their device. The server uses an emotion engine to analyze this data and evaluate the user's emotional state. This emotional information is used to adjust diagnostic guidance and respond to the user. The emotion engine utilizes natural language processing technology to identify emotions such as positive and negative from the input data.

[0329] By using a generative AI model, the server generates diagnostic guidance in multiple languages ​​based on the user's health and emotional state. The terminal automatically translates this information into the user's selected language and provides it to the user in voice or text format. This enables users to communicate with experts in real time, overcoming language barriers.

[0330] Furthermore, the server uses personalized guidance generation to formulate an action plan tailored to the user's health and emotional state. For example, if the user is seeking relaxation, it can recommend visiting a quiet tourist destination.

[0331] For example, if a user enters the prompt "I've been busy lately and want to relax," the server will analyze their emotional state and suggest a travel plan to promote relaxation. This allows users to receive services optimized according to their health and emotional state.

[0332] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0333] Step 1:

[0334] Users collect biometric data such as heart rate and body temperature using wearable devices. The collected data is transmitted to the terminal in real time. The input is biometric data, which serves as the initial data for the system.

[0335] Step 2:

[0336] The device transmits the received biometric data to the server. The device transmits the data via Bluetooth or Wi-Fi, and it is securely transmitted to the server. The input is the biometric data acquired by the device, and the output is the data transfer to the server.

[0337] Step 3:

[0338] The server analyzes biometric data using intelligent means. Specifically, it applies AI algorithms to evaluate the user's health status. For example, it checks for abnormalities in pulse rate and calculates health indicators. The input is biometric data acquired from the terminal, and the output is the health evaluation result.

[0339] Step 4:

[0340] The user provides voice or text data to the device to input their emotional state. This records the user's current emotions. The input is voice or text, and the output is the transmission of emotion data to the server.

[0341] Step 5:

[0342] The server uses an emotion engine to analyze emotion data. It analyzes input speech and text using natural language processing to identify emotion categories (positive, negative, etc.). The input is emotion data, and the output is an emotion evaluation result.

[0343] Step 6:

[0344] The server integrates health and emotional states to generate diagnostic guidance. Using a generative AI model, it creates diagnostic guidance expressed in multiple languages. The input consists of health assessment results and emotional assessment results, and the output is multilingual diagnostic guidance.

[0345] Step 7:

[0346] The terminal receives diagnostic guidance generated from the server and presents it to the user. The diagnostic guidance is automatically provided in the language selected by the user. The input is multilingual diagnostic guidance, and the output is information presented to the user.

[0347] Step 8:

[0348] The server generates an action plan based on the user's health and emotional state. Using a personalized guidance generation method, it can suggest quiet tourist destinations if the user is seeking relaxation. The input is the health assessment result and the emotional assessment result, and the output is an individualized action plan.

[0349] (Application Example 2)

[0350] 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."

[0351] In modern society, there is a challenge in that users find it difficult to accurately assess their own health and emotional state and to receive appropriate health care and relaxation at home based on that assessment. Furthermore, there is a challenge in how to present information combining health and emotional states to users in an easily understandable way and provide personalized services.

[0352] 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.

[0353] In this invention, the server includes data processing means for analyzing biometric information collected from the user, information generation means for providing personalized health care and entertainment based on the biometric information and emotional state, and response support means for presenting the generated information to the user and supporting dialogue. This enables the user to receive personalized services tailored to their health and emotional state in real time at home, thereby improving their quality of life.

[0354] "Data processing means" refers to a device or method for analyzing biometric information collected from a user and evaluating their health status and emotional state.

[0355] "Information generation means" refers to a device or method for creating information to provide personalized health care or entertainment based on biological information and emotional states.

[0356] "Response support means" refers to a device or method for presenting generated information to the user and facilitating smooth dialogue with the user.

[0357] "Adjustment means" refers to a device or method for optimizing the user's behavior and environment based on their health and emotional state.

[0358] The system for carrying out this invention evaluates the user's biometric information and emotional state and provides personalized services based on that evaluation. The main components of the system are data processing means, information generation means, response support means, and adjustment means. The following describes how these components work together.

[0359] Users continuously collect biometric information such as heart rate and body temperature using wearable devices. This data is transmitted to a server via a smartphone. The server analyzes the biometric information using data processing tools to evaluate the user's health and emotional state. AI models such as TensorFlow and PyTorch are used for this analysis.

[0360] The server's information generation mechanism generates personalized health care and entertainment suggestions based on evaluation results. This information is generated in multiple languages ​​using the Google Cloud Translation API. For example, if a user needs relaxation, the server might suggest calming music or visual content.

[0361] The generated information is presented to the user by a response support system. This process allows for dialogue via voice or text, and the information is automatically converted to the user's preferred format as needed. For example, if it is determined that the user is experiencing stress, a suggestion such as, "Shall we play some calming music today?" might be made.

[0362] An example of a prompt would be, "Design a dialogue flow for an AI model that suggests relaxing music when the user is feeling stressed." This would allow the user to enjoy a personalized experience and support relaxation at home.

[0363] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0364] Step 1:

[0365] The user obtains biometric information (heart rate, body temperature, etc.) from a wearable device. This data is transmitted in real time to a server via a smartphone. The input is biometric information from the wearable device, and the output is biometric data stored on the server. Data transfer is performed via Bluetooth or Wi-Fi.

[0366] Step 2:

[0367] The server analyzes the received biometric information using data processing tools to evaluate the user's health status. This process utilizes an AI model, with data processing performed using either TensorFlow or PyTorch. The input is biometric data stored on the server, and the output is the health status evaluation result. The analyzed data is added to the user's health status list.

[0368] Step 3:

[0369] The server uses emotional information obtained from voice or text messages to determine the user's emotional state. This information is processed by an emotion recognition engine. The input is voice or text data, and the output is an evaluation of the user's emotional state. Natural language processing techniques are used for processing, and the data is stored as an indicator of emotion.

[0370] Step 4:

[0371] The server combines health and emotional state assessments and uses information generation tools to suggest personalized health care and entertainment. Multilingual content is also generated using the Google Cloud Translation API. Input is health and emotional assessment results, and output is personalized suggestion information. This information is prepared along with entertainment categories.

[0372] Step 5:

[0373] The terminal presents the user with personalized suggestion information received from the server. Response support means enable interaction via voice or text. Input is suggestion information from the server, and output is information presented to the user on the terminal. This presentation aims to create a relaxing environment for the user.

[0374] 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.

[0375] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0376] 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.

[0377] [Third Embodiment]

[0378] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0379] 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.

[0380] 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).

[0381] 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.

[0382] 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.

[0383] 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).

[0384] 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.

[0385] 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.

[0386] 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.

[0387] 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.

[0388] 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.

[0389] 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".

[0390] The system of the present invention monitors the user's health status in real time and provides multilingual medical support and travel plans based on that information. The main elements of this system are artificial intelligence means for processing biometric information, multilingual interpretation means using large-scale language processing, and algorithms for generating personalized plans.

[0391] The wearable device used by the user continuously acquires biometric information such as heart rate, body temperature, and blood pressure, and transmits this data to the terminal. Upon receiving the data, the terminal automatically encrypts it and transfers it to the server in a secure state.

[0392] The server utilizes artificial intelligence to analyze received biometric data, detecting anomalies and assessing health status. Based on the analysis results, a large-scale language model is used to generate multilingual diagnostic information. This information is provided to the user via the terminal, and communication with medical professionals is supported as needed. For example, if a doctor explains something in Japanese during a consultation, it is translated into the user's chosen native language and provided in real time.

[0393] Furthermore, the server combines the user's current health status, location information, and environmental information such as weather to suggest the optimal sightseeing plan for each destination. For example, if the user is in good health, it will suggest a plan that includes active activities such as hiking and exploring the local area, while if the user's health is not a concern, it will recommend gentler activities such as visiting museums and art galleries.

[0394] In this way, users can enjoy health-conscious sightseeing while receiving medical services. The system of the present invention is designed to allow foreign visitors to Japan to have a comfortable stay without feeling barriers due to language or cultural differences.

[0395] The following describes the processing flow.

[0396] Step 1:

[0397] Users wear wearable devices while performing their daily activities. The wearable devices measure biometric information such as heart rate, body temperature, and blood pressure in real time and transmit the data to the terminal.

[0398] Step 2:

[0399] The device encrypts biometric information received from wearable devices and transmits the data to the server while protecting privacy. This protects the data from unauthorized access.

[0400] Step 3:

[0401] The server analyzes the received biometric information using an artificial intelligence model. If the analysis detects an abnormal heart rate, it notifies the user of the health risk. It also generates diagnostic information based on the analysis results.

[0402] Step 4:

[0403] The server uses a large-scale language model to translate diagnostic information into multiple languages ​​and generates diagnostic results in the user's selected language. These diagnostic results are accurately communicated in the language specified by the user.

[0404] Step 5:

[0405] The terminal receives multilingual diagnostic information transmitted from the server and presents it to the user. The user can communicate with medical professionals through the terminal, and real-time interpretation is provided as needed.

[0406] Step 6:

[0407] The server comprehensively considers the user's health status, current location, weather information, and other factors to generate the optimal sightseeing plan for the user. It uses reinforcement learning AI to propose personalized plans for each user.

[0408] Step 7:

[0409] The device notifies the user of suggested sightseeing plans and presents options. The user selects activities according to their physical condition and preferences, and prepares to enjoy sightseeing.

[0410] Step 8:

[0411] While the user is sightseeing, the terminal continues to collect biometric information from the wearable device and transmit it to the server. The server monitors this data and immediately issues an alert if any anomalies occur.

[0412] (Example 1)

[0413] 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."

[0414] In modern society, understanding health conditions and accurately communicating information in multiple languages ​​are crucial. However, when visitors are placed in different cultural and linguistic environments, obtaining real-time health information and communicating smoothly with local experts can be difficult. Furthermore, without the ability to develop appropriate action plans tailored to their health condition, effective health maintenance and optimization of the tourism experience become challenging. A comprehensive system is needed to address these challenges.

[0415] 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.

[0416] In this invention, the server includes information technology means for processing biometric information acquired from the user, large-scale information processing means for creating diagnostic data in multiple languages ​​based on the biometric information, and multilingual translation means for providing the diagnostic data to the user and supporting real-time communication with experts. As a result, the user can grasp their health status in real time, communicate smoothly with experts over language barriers, and develop an individualized action plan, thereby achieving optimal health maintenance and enjoying the experience.

[0417] "Information technology means" refers to technical elements for analyzing and processing biometric information obtained from users, and is a device or system that utilizes computer science and artificial intelligence technology.

[0418] "Large-scale information processing means" refers to technological elements that process large amounts of data quickly and efficiently in order to create multilingual diagnostic data, and utilize natural language processing models and machine learning algorithms.

[0419] A "multilingual translation means" is a system or device that has translation technology to provide users with diagnostic data in multiple languages ​​of their choice and to support communication with experts as needed.

[0420] "Individualized plan generation means" refers to a technological element for formulating an optimal action plan that takes into account the user's health status and environmental information, and is an algorithm-based planning system.

[0421] Users acquire biometric information in real time using wearable sensors. This includes data such as heart rate, body temperature, and blood pressure, which is transmitted to a device via Bluetooth or Wi-Fi. The device uses AES technology to encrypt the received data and securely transmits it to a server. The server runs a system that analyzes the biometric information using information technology tools such as natural language processing and machine learning. This enables the assessment of health status and the detection of abnormal values.

[0422] The analyzed results are processed through a generative AI model as a large-scale information processing tool, generating multilingual diagnostic data as needed. Leveraging a large-scale language model (e.g., GPT-3), diagnostic information is provided in the user's chosen language. This data is presented to the user on the device in audio or text format, and multilingual translation tools support real-time communication with experts as needed. For example, a translation API can be used to display health information provided in Japanese in English.

[0423] Furthermore, using a personalized plan generation mechanism, the server formulates an optimal action plan considering conditions such as the user's health status, location, and weather. For example, if the user is in good health and able to engage in outdoor activities, it will suggest plans for hiking or sightseeing. On the other hand, if the user is not feeling well, it will recommend activities in quiet places such as art museums or museums.

[0424] As a concrete example, the prompt message might read, "A doctor is explaining about high blood pressure in Japanese. Please translate this information into English for the user in real time." This would enable a system that allows users to monitor their health while enjoying a richer, safer, and more comfortable sightseeing experience.

[0425] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0426] Step 1:

[0427] The user acquires biometric information (heart rate, body temperature, blood pressure, etc.) from a wearable sensor. This data is transmitted to a terminal. The terminal receives this information via Bluetooth or Wi-Fi, encrypts it using AES technology, and ensures security. In this step, biometric information is received as input, and encrypted data is prepared as output.

[0428] Step 2:

[0429] The device sends encrypted biometric information to the server. The HTTPS protocol is used here to ensure the confidentiality of the information. Upon receiving the data, the server uses behavioral information technology (ICT) to analyze the biometric information. Specifically, AI algorithms are used to analyze the data, detecting anomalies and evaluating health status. The input for this step is encrypted biometric information, and the output is analyzed health status data.

[0430] Step 3:

[0431] Based on the analysis results, the server generates multilingual diagnostic data using large-scale information processing capabilities. It utilizes a generation AI model (e.g., GPT-3) to create the content in the user-specified language. The output is diagnostic information written in the selected language.

[0432] Step 4:

[0433] The terminal receives multilingual diagnostic information sent from the server. This information is displayed in the format chosen by the user (audio or text), and communication with experts is supported using multilingual translation tools. Specifically, real-time interpretation is possible through a translation API. Diagnostic information is received as input, and the information is presented to the user visually or audibly as output.

[0434] Step 5:

[0435] The server generates personalized action plans based on the user's health status, location, and environmental information such as weather. The algorithm formulates an optimal sightseeing plan and suggests recommended activities that take health management into consideration. The specific output is an action plan that includes details of activities such as hiking or visiting museums.

[0436] Through these steps, users can manage their health while facilitating smooth communication with local experts and achieving the best possible travel experience.

[0437] (Application Example 1)

[0438] 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."

[0439] In medical tourism, users often face difficulties in obtaining information smoothly and adapting to activities in the local area due to language barriers and health conditions. For foreign travelers in particular, language barriers and changes in health conditions are stressful issues. To solve this problem, a system is needed that utilizes users' biometric information to provide appropriate diagnostic information and travel plans in real time.

[0440] 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.

[0441] In this invention, the server includes data analysis means for analyzing biometric information collected from the user, natural language processing means for generating diagnostic information in multiple languages ​​based on the biometric information, and location information processing means for providing recommended activities within the city using the user's location information. This enables the user to enjoy appropriate sightseeing activities without experiencing language barriers while maintaining their health.

[0442] "Data analysis means" refers to a device or method that analyzes biometric information collected from users to detect abnormalities or evaluate their health status.

[0443] "Natural language processing means" refers to technologies or methods that generate medical diagnostic information in multiple languages ​​and convert it into a language that the user can understand.

[0444] "Translation means" refers to a device or method that has the function of automatically converting information into a language selected by the user and presenting it in audio or text format.

[0445] A "plan generation method" refers to a technology or function that formulates an action plan suitable for the user based on the user's health status and environmental information.

[0446] "Location information processing means" refers to a technology or method that utilizes a user's location information to suggest activities that are appropriate for the surrounding environment.

[0447] The system implementing this invention comprehensively provides health monitoring, multilingual support, and optimization of travel plans. Its main components include a wearable device carried by the user, a terminal (smartphone or smart glasses), and a server for processing data.

[0448] Wearable devices continuously collect biometric information such as the user's heart rate, body temperature, and blood pressure. The device receives this data using communication methods such as Bluetooth, encrypts it, and securely transmits it to a server.

[0449] The server uses an AI analysis engine built in Python to detect abnormal values ​​from biometric data and assess health status. The analyzed information is converted into multilingual diagnostic information using natural language processing technology. At this stage, a generative AI model is utilized to perform language conversion based on prompt text. Users can receive this information in real time via voice or text, supporting effective communication with healthcare professionals.

[0450] Furthermore, the server, through a plan generation mechanism, combines the user's current health status, geographical location, and surrounding environment data to provide an optimized sightseeing plan. This allows users to enjoy sightseeing to the fullest while maintaining their health. For example, if a user's heart rate is normal but their body temperature is slightly elevated, a plan such as "Visit a cool museum" might be suggested.

[0451] A concrete example of a prompt message would be something like, "The user's heart rate is 85, body temperature is 37.2 degrees, and current location is Shinjuku. Please suggest an appropriate activity." This invention enables safe and comfortable health management and sightseeing experiences even in cross-cultural environments.

[0452] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0453] Step 1:

[0454] The user's wearable device collects biometric information such as heart rate, body temperature, and blood pressure. The collected data is transmitted to the terminal via Bluetooth. The input is biometric information, and the output is data transfer to the terminal.

[0455] Step 2:

[0456] The terminal encrypts the received biometric information and transfers it to the server via a secure communication method. The input is biometric information from a wearable device, which is encrypted as part of the data processing, and the output is secure data transmission to the server.

[0457] Step 3:

[0458] The server uses an AI analysis engine to analyze biometric data, detect anomalies, and assess health status. The input is biometric data received from the terminal, health assessment is performed through data calculations, and the output is the analyzed health information.

[0459] Step 4:

[0460] Using natural language processing, the server converts analyzed health information into multilingual diagnostic information. The input is analyzed health information, language conversion is performed using a generative AI model, and the output is multilingual diagnostic information.

[0461] Step 5:

[0462] The server sends the generated diagnostic information to the terminal, and the user receives the information in audio or text format. Input is multilingual diagnostic information, and output is provided in the format selected by the user.

[0463] Step 6:

[0464] The server uses a plan generation method that combines the user's current location and environmental information to optimize the sightseeing plan. The input is the user's location and health status, and the optimal sightseeing plan is generated through data processing; the output is a customized sightseeing plan.

[0465] Step 7:

[0466] The server sends an optimized sightseeing plan to the terminal, and the user reviews the plan and adjusts their actions accordingly. The input is the optimized sightseeing plan, and the output is the user's reflection of their action plan.

[0467] 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.

[0468] This invention aims to realize a system that provides more accurate diagnoses and personalized services by evaluating not only the user's health status but also their emotional state. This system is designed to provide users with customized diagnoses and travel plans by combining biometric information analysis and emotion recognition. The main components include artificial intelligence means, large-scale language processing means, multilingual interpretation means, personalized plan generation means, and an emotion engine.

[0469] Users continuously collect biometric information such as heart rate and body temperature through wearable devices. This information is transmitted to a server via the device. The server uses artificial intelligence to evaluate the user's health status based on this biometric information.

[0470] Meanwhile, the emotion engine analyzes the user's voice and text data to evaluate their emotional state. This emotion analysis is used to generate diagnostic information and respond to the user. For example, if the diagnostic results are likely to induce anxiety, the emotion engine adjusts the wording to provide a sense of reassurance.

[0471] The server generates diagnostic information in multiple languages, taking into account the user's health and emotional state, and provides it to the user through the terminal. It supports real-time communication in the user's chosen language, ensuring smooth interaction with medical professionals. Based on the emotional state, emotional tone is added to the translated content as needed.

[0472] Furthermore, the server generates a sightseeing plan based on the user's health and emotional state. The plan is dynamically adjusted according to the user's sensitivities; for example, if the emotional state indicates a need for relaxation, it suggests visiting calmer tourist destinations.

[0473] This system will allow users to have a more fulfilling medical and tourism experience, and will provide an environment where foreign visitors can overcome language and emotional barriers and enjoy their stay in Japan with peace of mind.

[0474] The following describes the processing flow.

[0475] Step 1:

[0476] Users wear wearable devices while going about their daily lives. The wearable devices collect biometric information such as heart rate, body temperature, and blood pressure in real time and transmit it to the device.

[0477] Step 2:

[0478] The terminal encrypts the received biometric information and securely transmits it to the server. During this process, it verifies data integrity and performs redundant processing to prevent data loss.

[0479] Step 3:

[0480] The server receives biometric information and analyzes the user's health status using artificial intelligence. Based on the analysis results, it detects abnormal health indicators and sends alerts to medical institutions as needed.

[0481] Step 4:

[0482] The device collects voice and text data spoken by the user and sends it to the server. The server uses an emotion engine to analyze this data and recognize the user's emotional state.

[0483] Step 5:

[0484] The server generates multilingual diagnostic information based on the analyzed health and emotional states. The diagnostic information is adjusted according to the emotional state to include expressions that alleviate the user's anxiety.

[0485] Step 6:

[0486] The server uses large-scale language processing to translate diagnostic information into multiple languages ​​and sends it to the user's terminal. The terminal then presents this information to the user, supporting real-time communication with healthcare professionals.

[0487] Step 7:

[0488] The server generates sightseeing plans by combining the user's health status, emotional state, location information, and weather information. Reinforcement learning AI suggests the optimal plan based on the user's preferences and sensibilities.

[0489] Step 8:

[0490] The device presents the user with a generated sightseeing plan and offers options. It considers the user's emotional state to present the plan in an engaging way and assist in their selection.

[0491] Step 9:

[0492] While sightseeing, the device continues to collect biometric information from the wearable device and transmit it to the server. The server monitors this data, checks the user's health status in real time, and sends appropriate feedback as needed.

[0493] (Example 2)

[0494] 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."

[0495] In the modern healthcare and travel industries, there is a growing need to simultaneously understand users' health and emotional states and provide personalized diagnostic information and travel plans. However, conventional systems have struggled to integrate and analyze biometric and emotional data effectively, and to provide diagnoses and travel plans in multiple languages. Furthermore, they lacked sufficient automatic detection of abnormal data and real-time conversational support in the user's preferred language.

[0496] 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.

[0497] In this invention, the server includes intelligent means for analyzing biometric data collected from the user, language processing means for generating diagnostic guidance in multiple languages ​​based on the biometric data, and means for analyzing the user's emotional information using an emotion engine and adjusting the diagnostic guidance. This allows the user to quickly receive personalized diagnostic information based on their health and emotional state in multiple languages, and enables smooth communication with experts in real time.

[0498] A "user" is an entity that provides biometric data and emotional information and receives services from the system.

[0499] "Biometric data" refers to information that indicates the user's physical condition, such as heart rate and body temperature.

[0500] An "intelligent tool" is a system that uses artificial intelligence technology to analyze biometric data and perform processing to evaluate health status.

[0501] "Language processing means" refers to technology for expressing diagnostic guidance generated based on biometric data in multiple languages.

[0502] An "emotion engine" is a technology that analyzes emotional information from a user's voice or text and evaluates their emotional state.

[0503] A "diagnostic guide" is a document that organizes and provides information about the user's health status, and is presented in multiple languages.

[0504] "Interpretation methods" refer to technologies that translate diagnostic guidance and conversations with experts into the user's chosen language and present them in audio or text format.

[0505] An "action plan" refers to a travel or activity plan optimized based on the user's health status and emotional information.

[0506] This invention is a system that comprehensively analyzes a user's health and emotional state. The user wears a wearable device to collect biometric data such as heart rate and body temperature. This data is transmitted to a server via the terminal. The server analyzes this biometric data using artificial intelligence means and evaluates the user's health state.

[0507] Meanwhile, the user inputs voice or text data through their device. The server uses an emotion engine to analyze this data and evaluate the user's emotional state. This emotional information is used to adjust diagnostic guidance and respond to the user. The emotion engine utilizes natural language processing technology to identify emotions such as positive and negative from the input data.

[0508] By using a generative AI model, the server generates diagnostic guidance in multiple languages ​​based on the user's health and emotional state. The terminal automatically translates this information into the user's selected language and provides it to the user in voice or text format. This enables users to communicate with experts in real time, overcoming language barriers.

[0509] Furthermore, the server uses personalized guidance generation to formulate an action plan tailored to the user's health and emotional state. For example, if the user is seeking relaxation, it can recommend visiting a quiet tourist destination.

[0510] For example, if a user enters the prompt "I've been busy lately and want to relax," the server will analyze their emotional state and suggest a travel plan to promote relaxation. This allows users to receive services optimized according to their health and emotional state.

[0511] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0512] Step 1:

[0513] Users collect biometric data such as heart rate and body temperature using wearable devices. The collected data is transmitted to the terminal in real time. The input is biometric data, which serves as the initial data for the system.

[0514] Step 2:

[0515] The device transmits the received biometric data to the server. The device transmits the data via Bluetooth or Wi-Fi, and it is securely transmitted to the server. The input is the biometric data acquired by the device, and the output is the data transfer to the server.

[0516] Step 3:

[0517] The server analyzes biometric data using intelligent means. Specifically, it applies AI algorithms to evaluate the user's health status. For example, it checks for abnormalities in pulse rate and calculates health indicators. The input is biometric data acquired from the terminal, and the output is the health evaluation result.

[0518] Step 4:

[0519] The user provides voice or text data to the device to input their emotional state. This records the user's current emotions. The input is voice or text, and the output is the transmission of emotion data to the server.

[0520] Step 5:

[0521] The server uses an emotion engine to analyze emotion data. It analyzes input speech and text using natural language processing to identify emotion categories (positive, negative, etc.). The input is emotion data, and the output is an emotion evaluation result.

[0522] Step 6:

[0523] The server integrates health and emotional states to generate diagnostic guidance. Using a generative AI model, it creates diagnostic guidance expressed in multiple languages. The input consists of health assessment results and emotional assessment results, and the output is multilingual diagnostic guidance.

[0524] Step 7:

[0525] The terminal receives diagnostic guidance generated from the server and presents it to the user. The diagnostic guidance is automatically provided in the language selected by the user. The input is multilingual diagnostic guidance, and the output is information presented to the user.

[0526] Step 8:

[0527] The server generates an action plan based on the user's health and emotional state. Using a personalized guidance generation method, it can suggest quiet tourist destinations if the user is seeking relaxation. The input is the health assessment result and the emotional assessment result, and the output is an individualized action plan.

[0528] (Application Example 2)

[0529] 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."

[0530] In modern society, there is a challenge in that users find it difficult to accurately assess their own health and emotional state and to receive appropriate health care and relaxation at home based on that assessment. Furthermore, there is a challenge in how to present information combining health and emotional states to users in an easily understandable way and provide personalized services.

[0531] 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.

[0532] In this invention, the server includes data processing means for analyzing biometric information collected from the user, information generation means for providing personalized health care and entertainment based on the biometric information and emotional state, and response support means for presenting the generated information to the user and supporting dialogue. This enables the user to receive personalized services tailored to their health and emotional state in real time at home, thereby improving their quality of life.

[0533] "Data processing means" refers to a device or method for analyzing biometric information collected from a user and evaluating their health status and emotional state.

[0534] "Information generation means" refers to a device or method for creating information to provide personalized health care or entertainment based on biological information and emotional states.

[0535] "Response support means" refers to a device or method for presenting generated information to the user and facilitating smooth dialogue with the user.

[0536] "Adjustment means" refers to a device or method for optimizing the user's behavior and environment based on their health and emotional state.

[0537] The system for carrying out this invention evaluates the user's biometric information and emotional state and provides personalized services based on that evaluation. The main components of the system are data processing means, information generation means, response support means, and adjustment means. The following describes how these components work together.

[0538] Users continuously collect biometric information such as heart rate and body temperature using wearable devices. This data is transmitted to a server via a smartphone. The server analyzes the biometric information using data processing tools to evaluate the user's health and emotional state. AI models such as TensorFlow and PyTorch are used for this analysis.

[0539] The server's information generation mechanism generates personalized health care and entertainment suggestions based on evaluation results. This information is generated in multiple languages ​​using the Google Cloud Translation API. For example, if a user needs relaxation, the server might suggest calming music or visual content.

[0540] The generated information is presented to the user by a response support system. This process allows for dialogue via voice or text, and the information is automatically converted to the user's preferred format as needed. For example, if it is determined that the user is experiencing stress, a suggestion such as, "Shall we play some calming music today?" might be made.

[0541] An example of a prompt would be, "Design a dialogue flow for an AI model that suggests relaxing music when the user is feeling stressed." This would allow the user to enjoy a personalized experience and support relaxation at home.

[0542] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0543] Step 1:

[0544] The user obtains biometric information (heart rate, body temperature, etc.) from a wearable device. This data is transmitted in real time to a server via a smartphone. The input is biometric information from the wearable device, and the output is biometric data stored on the server. Data transfer is performed via Bluetooth or Wi-Fi.

[0545] Step 2:

[0546] The server analyzes the received biometric information using data processing tools to evaluate the user's health status. This process utilizes an AI model, with data processing performed using either TensorFlow or PyTorch. The input is biometric data stored on the server, and the output is the health status evaluation result. The analyzed data is added to the user's health status list.

[0547] Step 3:

[0548] The server uses emotional information obtained from voice or text messages to determine the user's emotional state. This information is processed by an emotion recognition engine. The input is voice or text data, and the output is an evaluation of the user's emotional state. Natural language processing techniques are used for processing, and the data is stored as an indicator of emotion.

[0549] Step 4:

[0550] The server combines health and emotional state assessments and uses information generation tools to suggest personalized health care and entertainment. Multilingual content is also generated using the Google Cloud Translation API. Input is health and emotional assessment results, and output is personalized suggestion information. This information is prepared along with entertainment categories.

[0551] Step 5:

[0552] The terminal presents the user with personalized suggestion information received from the server. Response support means enable interaction via voice or text. Input is suggestion information from the server, and output is information presented to the user on the terminal. This presentation aims to create a relaxing environment for the user.

[0553] 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.

[0554] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0555] 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.

[0556] [Fourth Embodiment]

[0557] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0558] 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.

[0559] 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).

[0560] 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.

[0561] 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.

[0562] 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).

[0563] 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.

[0564] 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.

[0565] 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.

[0566] 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.

[0567] 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.

[0568] 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.

[0569] 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".

[0570] The system of the present invention monitors the user's health status in real time and provides multilingual medical support and travel plans based on that information. The main elements of this system are artificial intelligence means for processing biometric information, multilingual interpretation means using large-scale language processing, and algorithms for generating personalized plans.

[0571] The wearable device used by the user continuously acquires biometric information such as heart rate, body temperature, and blood pressure, and transmits this data to the terminal. Upon receiving the data, the terminal automatically encrypts it and transfers it to the server in a secure state.

[0572] The server utilizes artificial intelligence to analyze received biometric data, detecting anomalies and assessing health status. Based on the analysis results, a large-scale language model is used to generate multilingual diagnostic information. This information is provided to the user via the terminal, and communication with medical professionals is supported as needed. For example, if a doctor explains something in Japanese during a consultation, it is translated into the user's chosen native language and provided in real time.

[0573] Furthermore, the server combines the user's current health status, location information, and environmental information such as weather to suggest the optimal sightseeing plan for each destination. For example, if the user is in good health, it will suggest a plan that includes active activities such as hiking and exploring the local area, while if the user's health is not a concern, it will recommend gentler activities such as visiting museums and art galleries.

[0574] In this way, users can enjoy health-conscious sightseeing while receiving medical services. The system of the present invention is designed to allow foreign visitors to Japan to have a comfortable stay without feeling barriers due to language or cultural differences.

[0575] The following describes the processing flow.

[0576] Step 1:

[0577] Users wear wearable devices while performing their daily activities. The wearable devices measure biometric information such as heart rate, body temperature, and blood pressure in real time and transmit the data to the terminal.

[0578] Step 2:

[0579] The device encrypts biometric information received from wearable devices and transmits the data to the server while protecting privacy. This protects the data from unauthorized access.

[0580] Step 3:

[0581] The server analyzes the received biometric information using an artificial intelligence model. If the analysis detects an abnormal heart rate, it notifies the user of the health risk. It also generates diagnostic information based on the analysis results.

[0582] Step 4:

[0583] The server uses a large-scale language model to translate diagnostic information into multiple languages ​​and generates diagnostic results in the user's selected language. These diagnostic results are accurately communicated in the language specified by the user.

[0584] Step 5:

[0585] The terminal receives multilingual diagnostic information transmitted from the server and presents it to the user. The user can communicate with medical professionals through the terminal, and real-time interpretation is provided as needed.

[0586] Step 6:

[0587] The server comprehensively considers the user's health status, current location, weather information, and other factors to generate the optimal sightseeing plan for the user. It uses reinforcement learning AI to propose personalized plans for each user.

[0588] Step 7:

[0589] The device notifies the user of suggested sightseeing plans and presents options. The user selects activities according to their physical condition and preferences, and prepares to enjoy sightseeing.

[0590] Step 8:

[0591] While the user is sightseeing, the terminal continues to collect biometric information from the wearable device and transmit it to the server. The server monitors this data and immediately issues an alert if any anomalies occur.

[0592] (Example 1)

[0593] 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".

[0594] In modern society, understanding health conditions and accurately communicating information in multiple languages ​​are crucial. However, when visitors are placed in different cultural and linguistic environments, obtaining real-time health information and communicating smoothly with local experts can be difficult. Furthermore, without the ability to develop appropriate action plans tailored to their health condition, effective health maintenance and optimization of the tourism experience become challenging. A comprehensive system is needed to address these challenges.

[0595] 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.

[0596] In this invention, the server includes information technology means for processing biometric information acquired from the user, large-scale information processing means for creating diagnostic data in multiple languages ​​based on the biometric information, and multilingual translation means for providing the diagnostic data to the user and supporting real-time communication with experts. As a result, the user can grasp their health status in real time, communicate smoothly with experts over language barriers, and develop an individualized action plan, thereby achieving optimal health maintenance and enjoying the experience.

[0597] "Information technology means" refers to technical elements for analyzing and processing biometric information obtained from users, and is a device or system that utilizes computer science and artificial intelligence technology.

[0598] "Large-scale information processing means" refers to technological elements that process large amounts of data quickly and efficiently in order to create multilingual diagnostic data, and utilize natural language processing models and machine learning algorithms.

[0599] A "multilingual translation means" is a system or device that has translation technology to provide users with diagnostic data in multiple languages ​​of their choice and to support communication with experts as needed.

[0600] "Individualized plan generation means" refers to a technological element for formulating an optimal action plan that takes into account the user's health status and environmental information, and is an algorithm-based planning system.

[0601] Users acquire biometric information in real time using wearable sensors. This includes data such as heart rate, body temperature, and blood pressure, which is transmitted to a device via Bluetooth or Wi-Fi. The device uses AES technology to encrypt the received data and securely transmits it to a server. The server runs a system that analyzes the biometric information using information technology tools such as natural language processing and machine learning. This enables the assessment of health status and the detection of abnormal values.

[0602] The analyzed results are processed through a generative AI model as a large-scale information processing tool, generating multilingual diagnostic data as needed. Leveraging a large-scale language model (e.g., GPT-3), diagnostic information is provided in the user's chosen language. This data is presented to the user on the device in audio or text format, and multilingual translation tools support real-time communication with experts as needed. For example, a translation API can be used to display health information provided in Japanese in English.

[0603] Furthermore, using a personalized plan generation mechanism, the server formulates an optimal action plan considering conditions such as the user's health status, location, and weather. For example, if the user is in good health and able to engage in outdoor activities, it will suggest plans for hiking or sightseeing. On the other hand, if the user is not feeling well, it will recommend activities in quiet places such as art museums or museums.

[0604] As a concrete example, the prompt message might read, "A doctor is explaining about high blood pressure in Japanese. Please translate this information into English for the user in real time." This would enable a system that allows users to monitor their health while enjoying a richer, safer, and more comfortable sightseeing experience.

[0605] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0606] Step 1:

[0607] The user acquires biometric information (heart rate, body temperature, blood pressure, etc.) from a wearable sensor. This data is transmitted to a terminal. The terminal receives this information via Bluetooth or Wi-Fi, encrypts it using AES technology, and ensures security. In this step, biometric information is received as input, and encrypted data is prepared as output.

[0608] Step 2:

[0609] The device sends encrypted biometric information to the server. The HTTPS protocol is used here to ensure the confidentiality of the information. Upon receiving the data, the server uses behavioral information technology (ICT) to analyze the biometric information. Specifically, AI algorithms are used to analyze the data, detecting anomalies and evaluating health status. The input for this step is encrypted biometric information, and the output is analyzed health status data.

[0610] Step 3:

[0611] Based on the analysis results, the server generates multilingual diagnostic data using large-scale information processing capabilities. It utilizes a generation AI model (e.g., GPT-3) to create the content in the user-specified language. The output is diagnostic information written in the selected language.

[0612] Step 4:

[0613] The terminal receives multilingual diagnostic information sent from the server. This information is displayed in the format chosen by the user (audio or text), and communication with experts is supported using multilingual translation tools. Specifically, real-time interpretation is possible through a translation API. Diagnostic information is received as input, and the information is presented to the user visually or audibly as output.

[0614] Step 5:

[0615] The server generates personalized action plans based on the user's health status, location, and environmental information such as weather. The algorithm formulates an optimal sightseeing plan and suggests recommended activities that take health management into consideration. The specific output is an action plan that includes details of activities such as hiking or visiting museums.

[0616] Through these steps, users can manage their health while facilitating smooth communication with local experts and achieving the best possible travel experience.

[0617] (Application Example 1)

[0618] 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".

[0619] In medical tourism, users often face difficulties in obtaining information smoothly and adapting to activities in the local area due to language barriers and health conditions. For foreign travelers in particular, language barriers and changes in health conditions are stressful issues. To solve this problem, a system is needed that utilizes users' biometric information to provide appropriate diagnostic information and travel plans in real time.

[0620] 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.

[0621] In this invention, the server includes data analysis means for analyzing biometric information collected from the user, natural language processing means for generating diagnostic information in multiple languages ​​based on the biometric information, and location information processing means for providing recommended activities within the city using the user's location information. This enables the user to enjoy appropriate sightseeing activities without experiencing language barriers while maintaining their health.

[0622] "Data analysis means" refers to a device or method that analyzes biometric information collected from users to detect abnormalities or evaluate their health status.

[0623] "Natural language processing means" refers to technologies or methods that generate medical diagnostic information in multiple languages ​​and convert it into a language that the user can understand.

[0624] "Translation means" refers to a device or method that has the function of automatically converting information into a language selected by the user and presenting it in audio or text format.

[0625] A "plan generation method" refers to a technology or function that formulates an action plan suitable for the user based on the user's health status and environmental information.

[0626] "Location information processing means" refers to a technology or method that utilizes a user's location information to suggest activities that are appropriate for the surrounding environment.

[0627] The system implementing this invention comprehensively provides health monitoring, multilingual support, and optimization of travel plans. Its main components include a wearable device carried by the user, a terminal (smartphone or smart glasses), and a server for processing data.

[0628] Wearable devices continuously collect biometric information such as the user's heart rate, body temperature, and blood pressure. The device receives this data using communication methods such as Bluetooth, encrypts it, and securely transmits it to a server.

[0629] The server uses an AI analysis engine built in Python to detect abnormal values ​​from biometric data and assess health status. The analyzed information is converted into multilingual diagnostic information using natural language processing technology. At this stage, a generative AI model is utilized to perform language conversion based on prompt text. Users can receive this information in real time via voice or text, supporting effective communication with healthcare professionals.

[0630] Furthermore, the server, through a plan generation mechanism, combines the user's current health status, geographical location, and surrounding environment data to provide an optimized sightseeing plan. This allows users to enjoy sightseeing to the fullest while maintaining their health. For example, if a user's heart rate is normal but their body temperature is slightly elevated, a plan such as "Visit a cool museum" might be suggested.

[0631] A concrete example of a prompt message would be something like, "The user's heart rate is 85, body temperature is 37.2 degrees, and current location is Shinjuku. Please suggest an appropriate activity." This invention enables safe and comfortable health management and sightseeing experiences even in cross-cultural environments.

[0632] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0633] Step 1:

[0634] The user's wearable device collects biometric information such as heart rate, body temperature, and blood pressure. The collected data is transmitted to the terminal via Bluetooth. The input is biometric information, and the output is data transfer to the terminal.

[0635] Step 2:

[0636] The terminal encrypts the received biometric information and transfers it to the server via a secure communication method. The input is biometric information from a wearable device, which is encrypted as part of the data processing, and the output is secure data transmission to the server.

[0637] Step 3:

[0638] The server uses an AI analysis engine to analyze biometric data, detect anomalies, and assess health status. The input is biometric data received from the terminal, health assessment is performed through data calculations, and the output is the analyzed health information.

[0639] Step 4:

[0640] Using natural language processing, the server converts analyzed health information into multilingual diagnostic information. The input is analyzed health information, language conversion is performed using a generative AI model, and the output is multilingual diagnostic information.

[0641] Step 5:

[0642] The server sends the generated diagnostic information to the terminal, and the user receives the information in audio or text format. Input is multilingual diagnostic information, and output is provided in the format selected by the user.

[0643] Step 6:

[0644] The server uses a plan generation method that combines the user's current location and environmental information to optimize the sightseeing plan. The input is the user's location and health status, and the optimal sightseeing plan is generated through data processing; the output is a customized sightseeing plan.

[0645] Step 7:

[0646] The server sends an optimized sightseeing plan to the terminal, and the user reviews the plan and adjusts their actions accordingly. The input is the optimized sightseeing plan, and the output is the user's reflection of their action plan.

[0647] 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.

[0648] This invention aims to realize a system that provides more accurate diagnoses and personalized services by evaluating not only the user's health status but also their emotional state. This system is designed to provide users with customized diagnoses and travel plans by combining biometric information analysis and emotion recognition. The main components include artificial intelligence means, large-scale language processing means, multilingual interpretation means, personalized plan generation means, and an emotion engine.

[0649] Users continuously collect biometric information such as heart rate and body temperature through wearable devices. This information is transmitted to a server via the device. The server uses artificial intelligence to evaluate the user's health status based on this biometric information.

[0650] Meanwhile, the emotion engine analyzes the user's voice and text data to evaluate their emotional state. This emotion analysis is used to generate diagnostic information and respond to the user. For example, if the diagnostic results are likely to induce anxiety, the emotion engine adjusts the wording to provide a sense of reassurance.

[0651] The server generates diagnostic information in multiple languages, taking into account the user's health and emotional state, and provides it to the user through the terminal. It supports real-time communication in the user's chosen language, ensuring smooth interaction with medical professionals. Based on the emotional state, emotional tone is added to the translated content as needed.

[0652] Furthermore, the server generates a sightseeing plan based on the user's health and emotional state. The plan is dynamically adjusted according to the user's sensitivities; for example, if the emotional state indicates a need for relaxation, it suggests visiting calmer tourist destinations.

[0653] This system will allow users to have a more fulfilling medical and tourism experience, and will provide an environment where foreign visitors can overcome language and emotional barriers and enjoy their stay in Japan with peace of mind.

[0654] The following describes the processing flow.

[0655] Step 1:

[0656] Users wear wearable devices while going about their daily lives. The wearable devices collect biometric information such as heart rate, body temperature, and blood pressure in real time and transmit it to the device.

[0657] Step 2:

[0658] The terminal encrypts the received biometric information and securely transmits it to the server. During this process, it verifies data integrity and performs redundant processing to prevent data loss.

[0659] Step 3:

[0660] The server receives biometric information and analyzes the user's health status using artificial intelligence. Based on the analysis results, it detects abnormal health indicators and sends alerts to medical institutions as needed.

[0661] Step 4:

[0662] The device collects voice and text data spoken by the user and sends it to the server. The server uses an emotion engine to analyze this data and recognize the user's emotional state.

[0663] Step 5:

[0664] The server generates multilingual diagnostic information based on the analyzed health and emotional states. The diagnostic information is adjusted according to the emotional state to include expressions that alleviate the user's anxiety.

[0665] Step 6:

[0666] The server uses large-scale language processing to translate diagnostic information into multiple languages ​​and sends it to the user's terminal. The terminal then presents this information to the user, supporting real-time communication with healthcare professionals.

[0667] Step 7:

[0668] The server generates sightseeing plans by combining the user's health status, emotional state, location information, and weather information. Reinforcement learning AI suggests the optimal plan based on the user's preferences and sensibilities.

[0669] Step 8:

[0670] The device presents the user with a generated sightseeing plan and offers options. It considers the user's emotional state to present the plan in an engaging way and assist in their selection.

[0671] Step 9:

[0672] While sightseeing, the device continues to collect biometric information from the wearable device and transmit it to the server. The server monitors this data, checks the user's health status in real time, and sends appropriate feedback as needed.

[0673] (Example 2)

[0674] 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".

[0675] In the modern healthcare and travel industries, there is a growing need to simultaneously understand users' health and emotional states and provide personalized diagnostic information and travel plans. However, conventional systems have struggled to integrate and analyze biometric and emotional data effectively, and to provide diagnoses and travel plans in multiple languages. Furthermore, they lacked sufficient automatic detection of abnormal data and real-time conversational support in the user's preferred language.

[0676] 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.

[0677] In this invention, the server includes intelligent means for analyzing biometric data collected from the user, language processing means for generating diagnostic guidance in multiple languages ​​based on the biometric data, and means for analyzing the user's emotional information using an emotion engine and adjusting the diagnostic guidance. This allows the user to quickly receive personalized diagnostic information based on their health and emotional state in multiple languages, and enables smooth communication with experts in real time.

[0678] A "user" is an entity that provides biometric data and emotional information and receives services from the system.

[0679] "Biometric data" refers to information that indicates the user's physical condition, such as heart rate and body temperature.

[0680] An "intelligent tool" is a system that uses artificial intelligence technology to analyze biometric data and perform processing to evaluate health status.

[0681] "Language processing means" refers to technology for expressing diagnostic guidance generated based on biometric data in multiple languages.

[0682] An "emotion engine" is a technology that analyzes emotional information from a user's voice or text and evaluates their emotional state.

[0683] A "diagnostic guide" is a document that organizes and provides information about the user's health status, and is presented in multiple languages.

[0684] "Interpretation methods" refer to technologies that translate diagnostic guidance and conversations with experts into the user's chosen language and present them in audio or text format.

[0685] An "action plan" refers to a travel or activity plan optimized based on the user's health status and emotional information.

[0686] This invention is a system that comprehensively analyzes a user's health and emotional state. The user wears a wearable device to collect biometric data such as heart rate and body temperature. This data is transmitted to a server via the terminal. The server analyzes this biometric data using artificial intelligence means and evaluates the user's health state.

[0687] Meanwhile, the user inputs voice or text data through their device. The server uses an emotion engine to analyze this data and evaluate the user's emotional state. This emotional information is used to adjust diagnostic guidance and respond to the user. The emotion engine utilizes natural language processing technology to identify emotions such as positive and negative from the input data.

[0688] By using a generative AI model, the server generates diagnostic guidance in multiple languages ​​based on the user's health and emotional state. The terminal automatically translates this information into the user's selected language and provides it to the user in voice or text format. This enables users to communicate with experts in real time, overcoming language barriers.

[0689] Furthermore, the server uses personalized guidance generation to formulate an action plan tailored to the user's health and emotional state. For example, if the user is seeking relaxation, it can recommend visiting a quiet tourist destination.

[0690] For example, if a user enters the prompt "I've been busy lately and want to relax," the server will analyze their emotional state and suggest a travel plan to promote relaxation. This allows users to receive services optimized according to their health and emotional state.

[0691] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0692] Step 1:

[0693] Users collect biometric data such as heart rate and body temperature using wearable devices. The collected data is transmitted to the terminal in real time. The input is biometric data, which serves as the initial data for the system.

[0694] Step 2:

[0695] The device transmits the received biometric data to the server. The device transmits the data via Bluetooth or Wi-Fi, and it is securely transmitted to the server. The input is the biometric data acquired by the device, and the output is the data transfer to the server.

[0696] Step 3:

[0697] The server analyzes biometric data using intelligent means. Specifically, it applies AI algorithms to evaluate the user's health status. For example, it checks for abnormalities in pulse rate and calculates health indicators. The input is biometric data acquired from the terminal, and the output is the health evaluation result.

[0698] Step 4:

[0699] The user provides voice or text data to the device to input their emotional state. This records the user's current emotions. The input is voice or text, and the output is the transmission of emotion data to the server.

[0700] Step 5:

[0701] The server uses an emotion engine to analyze emotion data. It analyzes input speech and text using natural language processing to identify emotion categories (positive, negative, etc.). The input is emotion data, and the output is an emotion evaluation result.

[0702] Step 6:

[0703] The server integrates health and emotional states to generate diagnostic guidance. Using a generative AI model, it creates diagnostic guidance expressed in multiple languages. The input consists of health assessment results and emotional assessment results, and the output is multilingual diagnostic guidance.

[0704] Step 7:

[0705] The terminal receives diagnostic guidance generated from the server and presents it to the user. The diagnostic guidance is automatically provided in the language selected by the user. The input is multilingual diagnostic guidance, and the output is information presented to the user.

[0706] Step 8:

[0707] The server generates an action plan based on the user's health and emotional state. Using a personalized guidance generation method, it can suggest quiet tourist destinations if the user is seeking relaxation. The input is the health assessment result and the emotional assessment result, and the output is an individualized action plan.

[0708] (Application Example 2)

[0709] 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".

[0710] In modern society, there is a challenge in that users find it difficult to accurately assess their own health and emotional state and to receive appropriate health care and relaxation at home based on that assessment. Furthermore, there is a challenge in how to present information combining health and emotional states to users in an easily understandable way and provide personalized services.

[0711] 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.

[0712] In this invention, the server includes data processing means for analyzing biometric information collected from the user, information generation means for providing personalized health care and entertainment based on the biometric information and emotional state, and response support means for presenting the generated information to the user and supporting dialogue. This enables the user to receive personalized services tailored to their health and emotional state in real time at home, thereby improving their quality of life.

[0713] "Data processing means" refers to a device or method for analyzing biometric information collected from a user and evaluating their health status and emotional state.

[0714] "Information generation means" refers to a device or method for creating information to provide personalized health care or entertainment based on biological information and emotional states.

[0715] "Response support means" refers to a device or method for presenting generated information to the user and facilitating smooth dialogue with the user.

[0716] "Adjustment means" refers to a device or method for optimizing the user's behavior and environment based on their health and emotional state.

[0717] The system for carrying out this invention evaluates the user's biometric information and emotional state and provides personalized services based on that evaluation. The main components of the system are data processing means, information generation means, response support means, and adjustment means. The following describes how these components work together.

[0718] Users continuously collect biometric information such as heart rate and body temperature using wearable devices. This data is transmitted to a server via a smartphone. The server analyzes the biometric information using data processing tools to evaluate the user's health and emotional state. AI models such as TensorFlow and PyTorch are used for this analysis.

[0719] The server's information generation mechanism generates personalized health care and entertainment suggestions based on evaluation results. This information is generated in multiple languages ​​using the Google Cloud Translation API. For example, if a user needs relaxation, the server might suggest calming music or visual content.

[0720] The generated information is presented to the user by a response support system. This process allows for dialogue via voice or text, and the information is automatically converted to the user's preferred format as needed. For example, if it is determined that the user is experiencing stress, a suggestion such as, "Shall we play some calming music today?" might be made.

[0721] An example of a prompt would be, "Design a dialogue flow for an AI model that suggests relaxing music when the user is feeling stressed." This would allow the user to enjoy a personalized experience and support relaxation at home.

[0722] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0723] Step 1:

[0724] The user obtains biometric information (heart rate, body temperature, etc.) from a wearable device. This data is transmitted in real time to a server via a smartphone. The input is biometric information from the wearable device, and the output is biometric data stored on the server. Data transfer is performed via Bluetooth or Wi-Fi.

[0725] Step 2:

[0726] The server analyzes the received biometric information using data processing tools to evaluate the user's health status. This process utilizes an AI model, with data processing performed using either TensorFlow or PyTorch. The input is biometric data stored on the server, and the output is the health status evaluation result. The analyzed data is added to the user's health status list.

[0727] Step 3:

[0728] The server uses emotional information obtained from voice or text messages to determine the user's emotional state. This information is processed by an emotion recognition engine. The input is voice or text data, and the output is an evaluation of the user's emotional state. Natural language processing techniques are used for processing, and the data is stored as an indicator of emotion.

[0729] Step 4:

[0730] The server combines health and emotional state assessments and uses information generation tools to suggest personalized health care and entertainment. Multilingual content is also generated using the Google Cloud Translation API. Input is health and emotional assessment results, and output is personalized suggestion information. This information is prepared along with entertainment categories.

[0731] Step 5:

[0732] The terminal presents the user with personalized suggestion information received from the server. Response support means enable interaction via voice or text. Input is suggestion information from the server, and output is information presented to the user on the terminal. This presentation aims to create a relaxing environment for the user.

[0733] 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.

[0734] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0735] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0736] 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.

[0737] 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.

[0738] 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.

[0739] 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.

[0740] 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.

[0741] 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."

[0742] 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.

[0743] 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.

[0744] 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.

[0745] 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.

[0746] 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.

[0747] 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.

[0748] 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.

[0749] 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.

[0750] 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.

[0751] 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.

[0752] 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.

[0753] 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.

[0754] The following is further disclosed regarding the embodiments described above.

[0755] (Claim 1)

[0756] An artificial intelligence tool for analyzing biometric information collected from users,

[0757] A large-scale language processing means for generating diagnostic information in multiple languages ​​based on the aforementioned biometric information,

[0758] A multilingual interpretation means for presenting the aforementioned diagnostic information to the user and supporting real-time communication with medical professionals,

[0759] A means for generating personalized plans to optimize tourism behavior based on the user's health status and environmental information,

[0760] A system that includes this.

[0761] (Claim 2)

[0762] The system according to claim 1, wherein the artificial intelligence means has a function to automatically detect abnormal values ​​and issue an alert.

[0763] (Claim 3)

[0764] The system according to claim 1, wherein the multilingual translation means has a function to automatically translate into a language selected by the user and present it in audio or text format.

[0765] "Example 1"

[0766] (Claim 1)

[0767] Information technology means for processing biometric information obtained from users,

[0768] A large-scale information processing means for creating diagnostic data in multiple languages ​​based on the aforementioned biological information,

[0769] A multilingual translation means for providing the aforementioned diagnostic data to the user and supporting real-time communication with experts,

[0770] A means for generating individual plans to optimize action plans based on the user's health status and surrounding information,

[0771] A system that includes this.

[0772] (Claim 2)

[0773] The system according to claim 1, wherein the information technology means has a function to automatically detect abnormal values ​​and issue a warning.

[0774] (Claim 3)

[0775] The system according to claim 1, wherein the multilingual translation means has a function to automatically convert to a language selected by the user and display it in audio or text format.

[0776] "Application Example 1"

[0777] (Claim 1)

[0778] A data analysis method for analyzing biometric information collected from users,

[0779] A natural language processing means that generates diagnostic information in multiple languages ​​based on the aforementioned biometric information,

[0780] A translation means for presenting the aforementioned diagnostic information to the user and supporting real-time communication,

[0781] A means for generating a plan to optimize actions based on the user's health status and surrounding information,

[0782] A location information processing means for providing recommended activities within a city using the user's location information,

[0783] A system that includes this.

[0784] (Claim 2)

[0785] The system according to claim 1, wherein the data analysis means has a function to automatically detect abnormal values ​​and issue alerts.

[0786] (Claim 3)

[0787] The system according to claim 1, wherein the translation means has a function to automatically convert to a language selected by the user and present it in audio or text format.

[0788] "Example 2 of combining an emotion engine"

[0789] (Claim 1)

[0790] An intelligent means for analyzing biometric data collected from users,

[0791] A language processing means for generating diagnostic guidance in multiple languages ​​based on the aforementioned biometric data,

[0792] A means for analyzing user emotional information using an emotion engine and adjusting diagnostic guidance,

[0793] The aforementioned diagnostic guidance is presented to the user, and an interpretation means is provided to support real-time dialogue with experts.

[0794] A means for generating personalized guidance to optimize action plans based on the user's health status and emotional information,

[0795] A system that includes this.

[0796] (Claim 2)

[0797] The system according to claim 1, wherein the intelligent means has a function to automatically detect abnormal data and issue a warning.

[0798] (Claim 3)

[0799] The system according to claim 1, wherein the translation means has a function to automatically convert to the user's selected language and present it in audio or text format.

[0800] "Application example 2 when combining with an emotional engine"

[0801] (Claim 1)

[0802] A data processing means for analyzing biometric information collected from users,

[0803] Information generation means for providing personalized health care and entertainment based on the aforementioned biometric information and emotional state,

[0804] The generated information is presented to the user, and a response support means is provided to support the dialogue.

[0805] A means for optimizing behavior based on the user's health and emotional state,

[0806] A system that includes this.

[0807] (Claim 2)

[0808] The system according to claim 1, wherein the data processing means has a function to automatically detect abnormal values ​​and issue warnings.

[0809] (Claim 3)

[0810] The system according to claim 1, wherein the response support means has a function to automatically convert to a method of expression selected by the user and present it in audio or text format. [Explanation of symbols]

[0811] 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. An artificial intelligence tool for analyzing biometric information collected from users, A large-scale language processing means for generating diagnostic information in multiple languages ​​based on the aforementioned biometric information, A multilingual interpretation means for presenting the aforementioned diagnostic information to the user and supporting real-time communication with medical professionals, A means for generating personalized plans to optimize tourism behavior based on the user's health status and environmental information, A system that includes this.

2. The system according to claim 1, wherein the artificial intelligence means has a function to automatically detect abnormal values ​​and issue an alert.

3. The system according to claim 1, wherein the multilingual translation means has a function to automatically translate into the language selected by the user and present it in audio or text format.

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