system

Abstract

We provide the system. [Solution] A sensor means for collecting the user's vital data, An analysis means for analyzing the above vital data and detecting abnormalities based on predetermined criteria, A notification means for notifying the user based on the above analysis results, A means of providing content based on user preferences, A means of communication for communicating with family, 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 persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] For the elderly to lead a safe and rich life, daily health management, appropriate communication means, and entertainment according to individual preferences are important. However, it is difficult for elderly people living alone to manage these elements individually, and there are concerns about isolation and an increased health risk. Therefore, a system that comprehensively supports these elements is required.

Means for Solving the Problems

[0005] This invention utilizes sensor means for collecting the user's vital data and analysis means for analyzing the collected data and detecting abnormalities. Furthermore, it includes notification means for notifying the user based on the analysis results, content provision means for providing content based on the user's preferences, and communication means for facilitating communication with family members who live far away. This comprehensively supports the health management, communication, and entertainment of the elderly, thereby reducing isolation and health risks.

[0006] "Sensing means" refers to devices and technologies used to collect a user's vital data.

[0007] "Analysis means" refers to devices or algorithms that analyze collected vital data and detect abnormalities based on predetermined criteria.

[0008] "Notification means" refers to devices or technologies that inform the user of the detection of an anomaly based on the analysis results, and these notifications are made in the form of voice, visuals, vibration, etc.

[0009] "Means of provision" refers to devices and systems used to provide entertainment and information based on the individual preferences of users.

[0010] "Communication means" refers to devices and systems that enable two-way communication between a user and family members located at a distance. [Brief explanation of the drawing]

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

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

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

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

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

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

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

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

[0019] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0032] This invention is a generative AI agent system that comprehensively supports the lives of the elderly. This system has a series of functions that support user health management, entertainment provision, and communication with family members in remote locations.

[0033] health care

[0034] The terminal collects vital data from the wearable device worn by the user. The collected data, such as heart rate and blood pressure, is used to understand the user's daily health status. The server receives this data and analyzes it using AI algorithms. For example, if an abnormal blood pressure fluctuation is detected, the server sends that information to the terminal and notifies the user. This notification serves as a trigger for the user to take appropriate medical action.

[0035] Providing entertainment

[0036] The device learns the user's past preferences and behavioral patterns and generates entertainment content based on them. This includes music, reading, games, and more. The server analyzes the collected data and determines the content best suited to the user. For example, a user seeking relaxation might be offered a playlist of calming music.

[0037] communication

[0038] The server manages the scheduling of video calls with family members. The device automatically starts video calls at the designated time, providing an environment where users and family members can communicate smoothly. This makes it possible to maintain emotional connections that transcend physical distance.

[0039] This system allows seniors to enjoy a richer life tailored to their individual preferences, going beyond mere health monitoring. Furthermore, the use of AI technology enables efficient and personalized life support, supporting a safe and stable life.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The terminal collects vital data from wearable devices worn by the user. This method uses Bluetooth or Wi-Fi connectivity to acquire data in real time.

[0043] Step 2:

[0044] The device transmits the collected vital data to the server via the internet. The data is encrypted and sent through a secure protocol.

[0045] Step 3:

[0046] The server analyzes the received vital data using an AI algorithm. It compares this data with past data and medical standards to detect abnormalities.

[0047] Step 4:

[0048] The server quickly generates an alert if an anomaly is detected based on the analysis results. This alert includes the type of anomaly and recommended actions.

[0049] Step 5:

[0050] The device receives alert notifications from the server. These notifications are communicated directly to the user via pop-up messages or audio alerts.

[0051] Step 6:

[0052] The device receives entertainment content from the server based on the user's preferences. Personalized content is delivered by utilizing the user's past action logs.

[0053] Step 7:

[0054] The server holds call data for automatically scheduling video calls with family members. A connection is established between the user's and family members' devices.

[0055] Step 8:

[0056] Users consume entertainment content on their devices as needed and communicate with family through video calls. This enriches their daily lives.

[0057] (Example 1)

[0058] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0059] There is a need for a system that provides integrated support for the health management of the elderly, the provision of individually optimized entertainment, and the smooth communication with family and friends who live far away. Existing technologies often provide these elements separately, making it difficult for the elderly and their families to have a consistent experience that allows them to live their daily lives with peace of mind.

[0060] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0061] In this invention, the server includes recording means for collecting biometric data, diagnostic means, communication means for issuing warnings, distribution means for providing preference information, and connection means for communicating with individuals. This enables real-time management of health status, provision of personalized entertainment, and easy communication.

[0062] "Biometric data" refers to numerical physical information such as heart rate, blood pressure, and body temperature used to evaluate a user's health status.

[0063] "Recording means" is a general term for devices and systems used to collect and store biometric data.

[0064] "Diagnostic methods" refer to techniques and technologies used to analyze collected biological data and detect abnormalities in health conditions.

[0065] "Communication methods" refer to communication functions and mechanisms for notifying users of analysis results and warning information.

[0066] "Means of providing preference information" refers to the technologies and processes for creating and delivering content based on users' past behavior and preferences.

[0067] "Means of connection for communicating with people" refers to methods or devices that enable the exchange of information with people in remote locations using communication networks such as the internet.

[0068] This invention is a comprehensive life support system for the elderly, integrating health management, entertainment provision, and communication promotion. Specific embodiments for implementing this invention are described below.

[0069] health care

[0070] The device collects the user's biometric data using a smartwatch or other wearable device. This allows for real-time acquisition of data such as heart rate, blood pressure, and body temperature, which is then aggregated on the connected device via Bluetooth.

[0071] The server receives this biometric data and analyzes it using an AI algorithm. This analysis allows the system to detect abnormalities in the collected data and send immediate warnings to the user.

[0072] For example, if a user's blood pressure rises suddenly, the server sends a notification to the terminal, providing the user with a message such as, "Your blood pressure is high. Please consult a doctor."

[0073] Providing entertainment

[0074] The device stores the user's past music playback and game play history and sends that data to the server.

[0075] The server uses a generative AI model to learn user preferences and deliver optimal entertainment content. This includes user-specific music playlists and interesting reading material.

[0076] For example, if the server determines that the user is seeking relaxation, it will suggest a playlist of calming music through the device.

[0077] communication

[0078] The server schedules and manages video calls between the user and family members in remote locations. Based on the call time set by the user, the device automatically starts the video call.

[0079] The device establishes a connection between the user and their family when a video call is initiated, providing an environment that supports smooth communication.

[0080] For example, if a video call with family is scheduled for 3 PM every Saturday, the device will automatically start the video call at that time, allowing the user to easily enjoy the conversation.

[0081] Example prompt: "Please explain the mechanism of an AI system that monitors the health status of elderly people and issues alerts in case of abnormalities."

[0082] Thus, this invention utilizes a generative AI model to provide lifestyle support tailored to individual needs, thereby helping elderly people live safe and fulfilling lives.

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] The terminal collects the user's biometric data (heart rate, blood pressure, body temperature) in real time from the wearable device. This data is sent to the terminal and aggregated on a smartphone via Bluetooth. The input is biometric information from the wearable device, and the output is vital data stored on the terminal.

[0086] Step 2:

[0087] The device transmits aggregated biometric data to a server via the internet. The server receives this data and begins analysis processing using an AI algorithm. The input is the biometric data transferred from the device, and the output is a diagnostic result indicating whether or not there are abnormalities. The data is compared to health standards to detect abnormalities in heart rate and blood pressure.

[0088] Step 3:

[0089] Based on the analysis results, the server sends a warning notification to the terminal if necessary. This can be an audio notification or displayed as a message on the screen. The input is the diagnostic result, and the output is the warning notification conveyed to the user.

[0090] Step 4:

[0091] The device collects the user's music playback history and behavioral patterns and sends this data to the server. The input is past preference data, and the output is data to be sent to the server.

[0092] Step 5:

[0093] The server analyzes the received preference data using a generating AI model to determine the most suitable entertainment content for the user. The input is preference data, and the output is recommended entertainment content. The server generates lists of music, reading materials, and other similar content.

[0094] Step 6:

[0095] The server sends appropriate entertainment content to the device. The device presents the content to the user, making it easily accessible. The input is content information from the server, and the output is a list of content on the user's screen.

[0096] Step 7:

[0097] The server manages the scheduling of video calls between the user and their family and instructs the device to automatically start the call at the scheduled time. The input is the schedule information, and the output is the instruction to start the video call.

[0098] Step 8:

[0099] The device launches the video call app at the time specified by the user and automatically establishes a connection with family members. The input is the call initiation command from the server, and the output is the communication connection established by the call initiation.

[0100] Through this series of processing steps, users can receive comprehensive support ranging from health management to entertainment and communication assistance.

[0101] (Application Example 1)

[0102] 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."

[0103] There is a lack of integrated support systems that meet the health management, entertainment, and communication needs of older adults. This results in insufficient support for older adults to live safe and comfortable lives.

[0104] 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.

[0105] In this invention, the server includes means for collecting physiological data, means for identifying abnormalities based on criteria, and means for providing optimized digital information. This enables real-time monitoring of the health status of the elderly, provision of entertainment tailored to individual preferences, and efficient communication with people in remote locations.

[0106] "Physiological data" refers to information about the user's body, including vital signs such as heart rate and blood pressure.

[0107] "Sensing means" refers to devices and methods for collecting physiological data, such as wearable devices.

[0108] "Analysis means" refers to algorithms and devices used to analyze collected data and identify anomalies and trends.

[0109] "Communication methods" refer to methods or devices for conveying information to users or stakeholders based on analysis results, and include sending notification messages.

[0110] "Means of delivery" refers to systems and methods for supplying information and services tailored to user preferences, such as recommendations for entertainment content.

[0111] "Communication means" refers to methods or devices that enable the exchange of information with a person in a remote location, and video call functions are an example of this.

[0112] "Real-time monitoring" refers to the process of instantly understanding and continuously observing the user's health status.

[0113] "Optimized digital information" refers to information that is structured in a personalized manner based on the user's past preferences and behavior.

[0114] This invention incorporates the following elements to realize a system that comprehensively supports the lives of the elderly. The server collects information via sensor means to acquire physiological data from wearable devices worn by the user. Specific examples of devices include health management devices that monitor heart rate and blood pressure. The data collected by the sensor means is transmitted to a server in the cloud, where anomalies are identified by AI-based analysis means.

[0115] When the analysis system processes the data, if an anomaly is detected, the user and relevant caregivers are notified in real time via a notification system. This allows for the rapid implementation of appropriate medical measures. The hardware consists of a standard communication device for internet connectivity, while the software side utilizes machine learning libraries such as TENSORFLOW® and Scikit-learn to handle AI analysis.

[0116] Simultaneously, optimized digital information, i.e., entertainment content, is delivered to users based on their past preferences using various delivery methods. This involves APIs from music streaming services and movie viewing platforms, for example, providing users with personalized content through Spotify or Netflix.

[0117] Furthermore, depending on the communication method, the server can schedule video calls with family and friends and notify the user in advance that the call will connect. This helps maintain emotional connections with family members who are in remote locations. For example, by utilizing the Google® Calendar API, smooth communication can be achieved by automatically connecting video calls at predetermined times.

[0118] An example of a prompt message would be: "Build an app that monitors Fitbit data in real time, sends notifications to care staff if an anomaly is detected, and provides recommended entertainment activities."

[0119] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0120] Step 1:

[0121] The terminal acquires physiological data from the wearable device worn by the user. This data includes heart rate and blood pressure. The acquired data is transmitted to the terminal using communication methods such as Bluetooth and stored in a format prepared for subsequent processing. The input is physiological data, and the output is the formatted data stored on the terminal.

[0122] Step 2:

[0123] The server receives physiological data transmitted from the terminal. This data is stored in a database and then analyzed using an AI algorithm. Specifically, a machine learning model is used to analyze the data to evaluate whether anomalies exist. The input is physiological data, and the output is the anomaly detection result.

[0124] Step 3:

[0125] If the analysis results are abnormal, the server will send a notification to the terminal using a notification system. The notification will include the detected abnormality and recommended actions. This action will enable users and caregivers to take prompt action. The input is the abnormality detection result, and the output is the notification information.

[0126] Step 4:

[0127] The device uses a delivery method to reference the user's past preference data and suggests optimized digital information, i.e., entertainment content, to the user. For example, via a music streaming service API, calming music is provided to a user who wants to relax. The input is the user's preference data, and the output is the suggested entertainment content.

[0128] Step 5:

[0129] The server uses communication methods to schedule video calls with family and friends and configures the system to automatically connect at the specified time. The terminal sends a notification to the user informing them of the time the call will begin. The input is the call schedule information, and the output is the preparation for starting the video call.

[0130] 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.

[0131] This invention relates to a generative AI agent system equipped with an emotion engine that analyzes the user's vital data and emotional state to comprehensively support the lives of the elderly. This system includes a variety of functions for user health management, personalized entertainment provision, and enhancing communication with family.

[0132] Emotional Recognition and Health Management

[0133] The device uses an emotion engine to analyze the user's facial expressions and voice along with their vital data to recognize their emotions. This data is collected from multiple sensors and sent to a server. The server analyzes this information using an AI algorithm to comprehensively evaluate the user's health and emotional state. For example, if the server determines that the user is experiencing stress, it will suggest a relaxing environment to help reduce stress.

[0134] Optimizing entertainment

[0135] The server generates and provides entertainment content based on the user's emotional state, as recognized by the emotion engine. The terminal delivers the received content to the user and supports their selection as needed. For example, if the server determines that the user is feeling down, uplifting music or video content will be suggested preferentially.

[0136] Emotion-based communication support

[0137] Communication with family members is further optimized based on the results of emotion recognition. The server considers the user's emotional state and suggests contacting family members at the appropriate time. Furthermore, it can analyze changes in emotions in real time during a call and use the results to help deepen the conversation. For example, before a call begins, it can determine if the user is relaxed and use that information to provide advice on how to tailor the conversation.

[0138] In this way, this system utilizes an emotion engine to support the user's mental and physical health in an integrated manner, providing an innovative approach to improving the quality of life for the elderly.

[0139] The following describes the processing flow.

[0140] Step 1:

[0141] The terminal collects vital data from the wearable device worn by the user. At the same time, it uses a camera and microphone to capture the user's facial expressions and voice, and passes this data to the emotion engine.

[0142] Step 2:

[0143] The device packages the collected vital and emotional data and sends it to a server via the internet. The data is encrypted to protect privacy.

[0144] Step 3:

[0145] The server uses AI to analyze received vital data and assess the user's health status. Furthermore, an emotion engine processes emotional data to identify the user's emotional state.

[0146] Step 4:

[0147] Based on the analysis results, the server comprehensively assesses the user's health and emotional state and determines the necessary response or alert. If an anomaly is detected, an alert is generated immediately.

[0148] Step 5:

[0149] The device receives alerts and status information from the server and notifies the user. Notifications are made via voice messages, visual alerts, or vibrations to attract the user's attention.

[0150] Step 6:

[0151] The server generates and sends optimized entertainment content to the device based on the user's emotional state. The content is designed to improve the user's mood.

[0152] Step 7:

[0153] The device provides the user with received entertainment content. The user can interact with and enjoy it. User feedback is logged so that it can be used to improve future services.

[0154] Step 8:

[0155] The server schedules video calls with family members, taking into account the user's emotional state. By contacting them at the appropriate time, it helps reduce feelings of isolation and supports smoother communication.

[0156] (Example 2)

[0157] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0158] In modern society, the health management and emotional support issues faced by the elderly are significant. However, conventional technologies lack the means to comprehensively analyze users' vital data and emotional data to provide immediate and appropriate health management guidance and emotional care. This lack contributes to a decline in the quality of life for the elderly.

[0159] 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.

[0160] In this invention, the server includes detection means for collecting the user's vital data and emotional data, analysis means for analyzing the vital data and emotional data and evaluating the user's health and emotional state through a generated AI model, and recommendation means for providing the user with a relaxing environment based on the analysis results. This makes it possible to grasp the user's physical and mental state in real time and provide appropriate health management and mental support.

[0161] "Vital data" refers to numerical data that indicates the basic health status of a user's body, such as heart rate, body temperature, and blood pressure.

[0162] "Emotional data" refers to data about a user's emotional state, inferred from their facial expressions, tone of voice, and other factors.

[0163] A "generative AI model" is an algorithm that uses artificial intelligence to analyze data and predict a user's emotions and health status.

[0164] "Detection means" refers to equipment or technology for collecting a user's vital data and emotional data.

[0165] An "analysis tool" is a system that analyzes collected data and objectively evaluates the user's condition.

[0166] "Recommended means of providing a relaxing environment" refers to a function that adjusts the environment and provides content to help users relax based on their current state.

[0167] A "means of delivery" refers to a system for presenting users with useful information or entertainment.

[0168] "Communication methods" refer to technologies used to exchange information between a user and their family or other communication partners.

[0169] This invention is a system designed to improve the quality of life by monitoring a user's health and emotional state in real time. The system is primarily realized through the collaboration of a server, a terminal, and the user.

[0170] The device is equipped with sensors to collect the user's vital and emotional data. This data, including heart rate, body temperature, voice tone, and facial expression changes, is acquired in real time. Specific sensor devices include biosensors, cameras, and microphones.

[0171] The collected data is sent from the device to the server. The server uses a generative AI model to analyze this data. Through this analysis, the server assesses the user's health and emotional state and generates recommendations to provide a relaxing environment as needed. For example, if the server determines that the user is stressed, it will suggest relaxing music or meditation content.

[0172] The recommendations and entertainment content generated by the server are then delivered to the user through the device. This delivery is either automatic or adjusted based on the user's choices. For example, if the user is feeling down during the day, uplifting music and videos will be prioritized.

[0173] Furthermore, the system optimizes communication with family members based on the user's emotional state. For example, when the user is relaxed, the server can send notifications at times that facilitate communication with family members.

[0174] A concrete example of a prompt message could be: "If an elderly user is feeling down during the day, generate suggestions for uplifting music or videos." This allows the system to provide content tailored to the user's needs.

[0175] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0176] Step 1:

[0177] The device collects the user's vital data and emotional data. Specifically, it uses heart rate and body temperature sensors to acquire the user's biometric data. It also records facial expressions and voice tone using a camera and microphone. This collected data becomes the input to the collection stage. The output is the detected vital data and emotional data.

[0178] Step 2:

[0179] The terminal performs the operation of sending the collected vital data and emotional data to the server. Specifically, it encrypts the data and sends it to the server via a secure communication protocol. The input for this step is the data obtained in step 1. The output is data that the server can use for analysis.

[0180] Step 3:

[0181] The server performs data analysis using a generated AI model based on the received data. Specifically, it analyzes emotional data with an emotion engine to identify the user's current emotional state. It also performs a health assessment of the user based on health indicators. The input for this step is vital data and emotional data transmitted from the terminal. The output is an assessment result regarding the user's health and emotional state.

[0182] Step 4:

[0183] The server uses the evaluation results to generate recommendations for the user. Specifically, it selects music and content to improve the environment for relaxation. Here, emotional state is the direct input data. The output is recommendations for the user.

[0184] Step 5:

[0185] The terminal provides the user with recommendations received from the server. Its primary actions include playing relaxing music on a music playback device or displaying visual content on a screen. The input for this step is the recommendations from the server. The output is the provision of visual or auditory stimuli to the user.

[0186] Step 6:

[0187] Users input their reactions and status regarding the provided content as feedback into their devices. Specifically, they input feedback through a dedicated application on their smartphone or tablet. This feedback is then used in subsequent data analysis. The input consists of the user's impressions and opinions, and the output is feedback data sent to the server.

[0188] (Application Example 2)

[0189] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0190] In modern society, improving the physical and mental health and quality of life of the elderly has become a social challenge. Consequently, there is a growing need for technologies that support stress management and smooth communication with family members. However, current technologies make it difficult to provide individualized, comprehensive support to the elderly. Furthermore, there is a lack of means to provide appropriate support based on their emotional state.

[0191] 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.

[0192] In this invention, the server includes a sensor device for collecting the user's biometric data, an emotion recognition device for recognizing emotional states from facial and vocal data, and an adjustment device for providing information to family members at the optimal timing according to the emotional state. This enables appropriate support and optimized communication based on the emotional state of elderly individuals.

[0193] "Biometric data" refers to physical data that indicates a user's health status, including information such as heart rate and body temperature.

[0194] A "sensor device" is a device used to detect and measure a user's biometric data, and includes wearable devices and cameras.

[0195] An "analysis device" is a processing device that analyzes collected biological data to determine health status and emotional state.

[0196] A "notification device" is a means of communicating analysis results and suggestions to the user or their family, and includes smartphones and other communication devices.

[0197] A "providing device" is a system or software that generates and provides entertainment content based on the user's preferences and circumstances.

[0198] A "communication device" is a means that enables voice calls and the sending and receiving of messages between a user and their family.

[0199] An "emotion recognition device" is software or hardware that has the function of analyzing a user's face and voice to determine their emotional state.

[0200] A "regulating device" is a means of adjusting the timing and content of information provided to family members based on the user's emotional state.

[0201] This invention is a system that comprehensively supports the user's health and emotional state. The system consists of a sensor device, an analysis device, a notification device, a provision device, a communication device, an emotion recognition device, and an adjustment device.

[0202] The sensor device plays a role in collecting the user's biometric data, measuring heart rate and body temperature using wearable devices, etc. This enables real-time collection of health data.

[0203] The server analyzes data collected using an analysis device with machine learning algorithms (e.g., TensorFlow or PyTorch). This allows it to determine the user's health and emotional state, and if an abnormality is detected, it generates appropriate content to help alleviate stress.

[0204] The notification device provides information to the user or their family based on the analysis results. For example, it may send notifications about health status and recommended actions via a smartphone app.

[0205] The device generates and delivers personalized entertainment based on the user's preferences and emotional state. It can play music using the Spotify API and select video content.

[0206] Furthermore, the communication device supports communication with family members based on the emotional state analyzed by the emotion recognition device. For example, if the user is feeling stressed, the family will be notified and prompted to make a call at an appropriate time.

[0207] For example, if a user's heart rate is detected as higher than normal, the server will suggest and notify them of relaxing music. This type of processing can be made possible by utilizing generative AI models to provide optimal solutions for each individual user.

[0208] An example of a prompt to a generative AI model is: "The user's heart rate is higher than normal. Please recommend relaxing music and a breathing instruction video."

[0209] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0210] Step 1:

[0211] Users collect biometric data (heart rate, body temperature, etc.) using sensors on smartwatches or smartphones. The input is biometric data, and the output is sent to the cloud.

[0212] Step 2:

[0213] The server processes biometric data received from the cloud using an analysis device. The input is biometric data acquired from the cloud, which is processed using machine learning algorithms to evaluate the user's health status. In this process, libraries such as TensorFlow are used to identify anomalies, and the evaluation results are output.

[0214] Step 3:

[0215] The emotion recognition device analyzes the user's face and voice using the device's camera and microphone. The input consists of camera images and audio data, which are processed by an emotion analysis algorithm. This determines the user's emotional state and outputs the result.

[0216] Step 4:

[0217] The server integrates analyzed health and emotional states to generate entertainment content tailored to the specific situation. The input consists of health and emotional state assessment results; a generative AI model is used to select and output appropriate music and video content.

[0218] Step 5:

[0219] The terminal uses a notification device to present recommended entertainment content to the user. The input is content information from a server, which is output to the user through the terminal screen and speaker.

[0220] Step 6:

[0221] The server uses a control device to manage the provision of information to family members based on their emotional state. The input is the user's emotional assessment result, and it sends notifications to family members in real time and outputs information in a way that facilitates calls as needed.

[0222] Step 7:

[0223] The generative AI model processes the prompt text and proposes the next action plan. The input is the prompt text, "The user's heart rate is higher than normal. Please recommend relaxing music and a breathing instruction video." Based on this, it generates and outputs the most suitable content suggestions.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] [Second Embodiment]

[0228] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0229] 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.

[0230] 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).

[0231] 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.

[0232] 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.

[0233] 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).

[0234] 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.

[0235] 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.

[0236] 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.

[0237] 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.

[0238] 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.

[0239] 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".

[0240] This invention is a generative AI agent system that comprehensively supports the lives of the elderly. This system has a series of functions that support user health management, entertainment provision, and communication with family members in remote locations.

[0241] health care

[0242] The terminal collects vital data from the wearable device worn by the user. The collected data, such as heart rate and blood pressure, is used to understand the user's daily health status. The server receives this data and analyzes it using AI algorithms. For example, if an abnormal blood pressure fluctuation is detected, the server sends that information to the terminal and notifies the user. This notification serves as a trigger for the user to take appropriate medical action.

[0243] Providing entertainment

[0244] The device learns the user's past preferences and behavioral patterns and generates entertainment content based on them. This includes music, reading, games, and more. The server analyzes the collected data and determines the content best suited to the user. For example, a user seeking relaxation might be offered a playlist of calming music.

[0245] communication

[0246] The server manages the scheduling of video calls with family members. The device automatically starts video calls at the designated time, providing an environment where users and family members can communicate smoothly. This makes it possible to maintain emotional connections that transcend physical distance.

[0247] This system allows seniors to enjoy a richer life tailored to their individual preferences, going beyond mere health monitoring. Furthermore, the use of AI technology enables efficient and personalized life support, supporting a safe and stable life.

[0248] The following describes the processing flow.

[0249] Step 1:

[0250] The terminal collects vital data from wearable devices worn by the user. This method uses Bluetooth or Wi-Fi connectivity to acquire data in real time.

[0251] Step 2:

[0252] The device transmits the collected vital data to the server via the internet. The data is encrypted and sent through a secure protocol.

[0253] Step 3:

[0254] The server analyzes the received vital data using an AI algorithm. It compares this data with past data and medical standards to detect abnormalities.

[0255] Step 4:

[0256] The server quickly generates an alert if an anomaly is detected based on the analysis results. This alert includes the type of anomaly and recommended actions.

[0257] Step 5:

[0258] The device receives alert notifications from the server. These notifications are communicated directly to the user via pop-up messages or audio alerts.

[0259] Step 6:

[0260] The device receives entertainment content from the server based on the user's preferences. Personalized content is delivered by utilizing the user's past action logs.

[0261] Step 7:

[0262] The server holds call data for automatically scheduling video calls with family members. A connection is established between the user's and family members' devices.

[0263] Step 8:

[0264] Users consume entertainment content on their devices as needed and communicate with family through video calls. This enriches their daily lives.

[0265] (Example 1)

[0266] 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."

[0267] There is a need for a system that provides integrated support for the health management of the elderly, the provision of individually optimized entertainment, and the smooth communication with family and friends who live far away. Existing technologies often provide these elements separately, making it difficult for the elderly and their families to have a consistent experience that allows them to live their daily lives with peace of mind.

[0268] 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.

[0269] In this invention, the server includes recording means for collecting biometric data, diagnostic means, communication means for issuing warnings, distribution means for providing preference information, and connection means for communicating with individuals. This enables real-time management of health status, provision of personalized entertainment, and easy communication.

[0270] "Biometric data" refers to numerical physical information such as heart rate, blood pressure, and body temperature used to evaluate a user's health status.

[0271] "Recording means" is a general term for devices and systems used to collect and store biometric data.

[0272] "Diagnostic methods" refer to techniques and technologies used to analyze collected biological data and detect abnormalities in health conditions.

[0273] "Communication methods" refer to communication functions and mechanisms for notifying users of analysis results and warning information.

[0274] "Means of providing preference information" refers to the technologies and processes for creating and delivering content based on users' past behavior and preferences.

[0275] "Means of connection for communicating with people" refers to methods or devices that enable the exchange of information with people in remote locations using communication networks such as the internet.

[0276] This invention is a comprehensive life support system for the elderly, integrating health management, entertainment provision, and communication promotion. Specific embodiments for implementing this invention are described below.

[0277] health care

[0278] The device collects the user's biometric data using a smartwatch or other wearable device. This allows for real-time acquisition of data such as heart rate, blood pressure, and body temperature, which is then aggregated on the connected device via Bluetooth.

[0279] The server receives this biometric data and analyzes it using an AI algorithm. This analysis allows the system to detect abnormalities in the collected data and send immediate warnings to the user.

[0280] For example, if a user's blood pressure rises suddenly, the server sends a notification to the terminal, providing the user with a message such as, "Your blood pressure is high. Please consult a doctor."

[0281] Providing entertainment

[0282] The terminal accumulates the user's past music playback history and game play history, and transmits that data to the server.

[0283] The server uses a generative AI model to learn the user's preferences and deliver optimal entertainment content. This includes music playlists unique to the user and reading content that is engaging.

[0284] As a specific example, if it is determined that the user is seeking relaxation, the server proposes a playlist of soothing music through the terminal.

[0285] Communication

[0286] The server schedules video calls between the user and family members in a remote location. Based on the call times set in advance by the user, the terminal automatically initiates a video call.

[0287] The terminal establishes the connection of the user and family members at the start of the video call and provides an environment that supports smooth communication.

[0288] As a specific example, if a video call with family members is scheduled for 3 pm every Saturday, the terminal automatically initiates a video call at that time so that the user can easily enjoy the conversation.

[0289] Example of a prompt sentence: "Please explain the mechanism of an AI system that monitors the health status of the elderly and issues alerts in case of abnormalities."

[0290] In this way, the present invention utilizes a generative AI model to provide life support corresponding to individual needs, and serves as a help for the elderly to lead a safe and fulfilling life.

[0291] The flow of the specific process in Example 1 will be described using FIG. 11.

[0292] Step 1:

[0293] The terminal collects the user's biometric data (heart rate, blood pressure, body temperature) in real time from the wearable device. This data is sent to the terminal and aggregated on a smartphone via Bluetooth. The input is biometric information from the wearable device, and the output is vital data stored on the terminal.

[0294] Step 2:

[0295] The device transmits aggregated biometric data to a server via the internet. The server receives this data and begins analysis processing using an AI algorithm. The input is the biometric data transferred from the device, and the output is a diagnostic result indicating whether or not there are abnormalities. The data is compared to health standards to detect abnormalities in heart rate and blood pressure.

[0296] Step 3:

[0297] Based on the analysis results, the server sends a warning notification to the terminal if necessary. This can be an audio notification or displayed as a message on the screen. The input is the diagnostic result, and the output is the warning notification conveyed to the user.

[0298] Step 4:

[0299] The device collects the user's music playback history and behavioral patterns and sends this data to the server. The input is past preference data, and the output is data to be sent to the server.

[0300] Step 5:

[0301] The server analyzes the received preference data using a generating AI model to determine the most suitable entertainment content for the user. The input is preference data, and the output is recommended entertainment content. The server generates lists of music, reading materials, and other similar content.

[0302] Step 6:

[0303] The server transmits appropriate entertainment content to the terminal. The terminal presents the content to the user and makes it easily accessible. The input is the content information from the server, and the output is the content list on the user screen.

[0304] Step 7:

[0305] The server manages the schedule of video calls between the user and family members, and instructs the terminal to automatically start the call at the set time. The input is the schedule information, and the output is the instruction to start the video call.

[0306] Step 8:

[0307] The terminal launches the video call application at the time specified by the user and automatically establishes a connection with the family members. The input is the call start instruction from the server, and the output is the communication connection due to the start of the call.

[0308] Through this series of processing steps, the user can receive comprehensive support from health management to entertainment and communication assistance.

[0309] (Application Example 1)

[0310] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0311] There is a lack of an integrated support system to meet the needs of health management, entertainment, and communication in the lives of the elderly. As a result, the support for the elderly to live a safe and comfortable life is insufficient.

[0312] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0313] In this invention, the server includes means for collecting physiological data, means for identifying abnormalities based on criteria, and means for providing optimized digital information. This enables real-time monitoring of the health status of the elderly, provision of entertainment tailored to individual preferences, and efficient communication with people in remote locations.

[0314] "Physiological data" refers to information about the user's body, including vital signs such as heart rate and blood pressure.

[0315] "Sensing means" refers to devices and methods for collecting physiological data, such as wearable devices.

[0316] "Analysis means" refers to algorithms and devices used to analyze collected data and identify anomalies and trends.

[0317] "Communication methods" refer to methods or devices for conveying information to users or stakeholders based on analysis results, and include sending notification messages.

[0318] "Means of delivery" refers to systems and methods for supplying information and services tailored to user preferences, such as recommendations for entertainment content.

[0319] "Communication means" refers to methods or devices that enable the exchange of information with a person in a remote location, and video call functions are an example of this.

[0320] "Real-time monitoring" refers to the process of instantly understanding and continuously observing the user's health status.

[0321] "Optimized digital information" refers to information that is structured in a personalized manner based on the user's past preferences and behavior.

[0322] This invention incorporates the following elements to realize a system that comprehensively supports the lives of the elderly. The server collects information via sensor means to acquire physiological data from wearable devices worn by the user. Specific examples of devices include health management devices that monitor heart rate and blood pressure. The data collected by the sensor means is transmitted to a server in the cloud, where anomalies are identified by AI-based analysis means.

[0323] When the analysis system processes the data, if an anomaly is detected, the user and relevant caregivers are notified in real time through a notification system. This allows for the rapid implementation of appropriate medical measures. The hardware consists of a standard communication device for internet connectivity, while the software side utilizes machine learning libraries such as TensorFlow and Scikit-learn to handle AI analysis.

[0324] Simultaneously, optimized digital information, i.e., entertainment content, is delivered to users based on their past preferences using various delivery methods. This involves APIs from music streaming services and movie viewing platforms, for example, providing users with personalized content through Spotify or Netflix.

[0325] Furthermore, depending on the communication method, the server can schedule video calls with family and friends and notify the user in advance that the call will connect. This helps maintain emotional connections with family members who are in remote locations. For example, by utilizing the Google Calendar API to automatically connect video calls at predetermined times, smooth communication can be achieved.

[0326] An example of a prompt message would be: "Build an app that monitors Fitbit data in real time, sends notifications to care staff if an anomaly is detected, and provides recommended entertainment activities."

[0327] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0328] Step 1:

[0329] The terminal acquires physiological data from the wearable device worn by the user. This data includes heart rate and blood pressure. The acquired data is transmitted to the terminal using communication methods such as Bluetooth and stored in a format prepared for subsequent processing. The input is physiological data, and the output is the formatted data stored on the terminal.

[0330] Step 2:

[0331] The server receives physiological data transmitted from the terminal. This data is stored in a database and then analyzed using an AI algorithm. Specifically, a machine learning model is used to analyze the data to evaluate whether anomalies exist. The input is physiological data, and the output is the anomaly detection result.

[0332] Step 3:

[0333] If the analysis results are abnormal, the server will send a notification to the terminal using a notification system. The notification will include the detected abnormality and recommended actions. This action will enable users and caregivers to take prompt action. The input is the abnormality detection result, and the output is the notification information.

[0334] Step 4:

[0335] The device uses a delivery method to reference the user's past preference data and suggests optimized digital information, i.e., entertainment content, to the user. For example, via a music streaming service API, calming music is provided to a user who wants to relax. The input is the user's preference data, and the output is the suggested entertainment content.

[0336] Step 5:

[0337] The server uses communication methods to schedule video calls with family and friends and configures the system to automatically connect at the specified time. The terminal sends a notification to the user informing them of the time the call will begin. The input is the call schedule information, and the output is the preparation for starting the video call.

[0338] 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.

[0339] This invention relates to a generative AI agent system equipped with an emotion engine that analyzes the user's vital data and emotional state to comprehensively support the lives of the elderly. This system includes a variety of functions for user health management, personalized entertainment provision, and enhancing communication with family.

[0340] Emotional Recognition and Health Management

[0341] The device uses an emotion engine to analyze the user's facial expressions and voice along with their vital data to recognize their emotions. This data is collected from multiple sensors and sent to a server. The server analyzes this information using an AI algorithm to comprehensively evaluate the user's health and emotional state. For example, if the server determines that the user is experiencing stress, it will suggest a relaxing environment to help reduce stress.

[0342] Optimizing entertainment

[0343] The server generates and provides entertainment content based on the user's emotional state, as recognized by the emotion engine. The terminal delivers the received content to the user and supports their selection as needed. For example, if the server determines that the user is feeling down, uplifting music or video content will be suggested preferentially.

[0344] Emotion-based communication support

[0345] Communication with family members is further optimized based on the results of emotion recognition. The server considers the user's emotional state and suggests contacting family members at the appropriate time. Furthermore, it can analyze changes in emotions in real time during a call and use the results to help deepen the conversation. For example, before a call begins, it can determine if the user is relaxed and use that information to provide advice on how to tailor the conversation.

[0346] In this way, this system utilizes an emotion engine to support the user's mental and physical health in an integrated manner, providing an innovative approach to improving the quality of life for the elderly.

[0347] The following describes the processing flow.

[0348] Step 1:

[0349] The terminal collects vital data from the wearable device worn by the user. At the same time, it uses a camera and microphone to capture the user's facial expressions and voice, and passes this data to the emotion engine.

[0350] Step 2:

[0351] The device packages the collected vital and emotional data and sends it to a server via the internet. The data is encrypted to protect privacy.

[0352] Step 3:

[0353] The server uses AI to analyze received vital data and assess the user's health status. Furthermore, an emotion engine processes emotional data to identify the user's emotional state.

[0354] Step 4:

[0355] Based on the analysis results, the server comprehensively assesses the user's health and emotional state and determines the necessary response or alert. If an anomaly is detected, an alert is generated immediately.

[0356] Step 5:

[0357] The device receives alerts and status information from the server and notifies the user. Notifications are made via voice messages, visual alerts, or vibrations to attract the user's attention.

[0358] Step 6:

[0359] The server generates and sends optimized entertainment content to the device based on the user's emotional state. The content is designed to improve the user's mood.

[0360] Step 7:

[0361] The device provides the user with received entertainment content. The user can interact with and enjoy it. User feedback is logged so that it can be used to improve future services.

[0362] Step 8:

[0363] The server schedules video calls with family members, taking into account the user's emotional state. By contacting them at the appropriate time, it helps reduce feelings of isolation and supports smoother communication.

[0364] (Example 2)

[0365] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0366] In modern society, the health management and emotional support issues faced by the elderly are significant. However, conventional technologies lack the means to comprehensively analyze users' vital data and emotional data to provide immediate and appropriate health management guidance and emotional care. This lack contributes to a decline in the quality of life for the elderly.

[0367] 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.

[0368] In this invention, the server includes detection means for collecting the user's vital data and emotional data, analysis means for analyzing the vital data and emotional data and evaluating the user's health and emotional state through a generated AI model, and recommendation means for providing the user with a relaxing environment based on the analysis results. This makes it possible to grasp the user's physical and mental state in real time and provide appropriate health management and mental support.

[0369] "Vital data" refers to numerical data that indicates the basic health status of a user's body, such as heart rate, body temperature, and blood pressure.

[0370] "Emotional data" refers to data about a user's emotional state, inferred from their facial expressions, tone of voice, and other factors.

[0371] A "generative AI model" is an algorithm that uses artificial intelligence to analyze data and predict a user's emotions and health status.

[0372] "Detection means" refers to equipment or technology for collecting a user's vital data and emotional data.

[0373] An "analysis tool" is a system that analyzes collected data and objectively evaluates the user's condition.

[0374] "Recommended means of providing a relaxing environment" refers to a function that adjusts the environment and provides content to help users relax based on their current state.

[0375] A "means of delivery" refers to a system for presenting users with useful information or entertainment.

[0376] "Communication methods" refer to technologies used to exchange information between a user and their family or other communication partners.

[0377] This invention is a system designed to improve the quality of life by monitoring a user's health and emotional state in real time. The system is primarily realized through the collaboration of a server, a terminal, and the user.

[0378] The device is equipped with sensors to collect the user's vital and emotional data. This data, including heart rate, body temperature, voice tone, and facial expression changes, is acquired in real time. Specific sensor devices include biosensors, cameras, and microphones.

[0379] The collected data is sent from the device to the server. The server uses a generative AI model to analyze this data. Through this analysis, the server assesses the user's health and emotional state and generates recommendations to provide a relaxing environment as needed. For example, if the server determines that the user is stressed, it will suggest relaxing music or meditation content.

[0380] The recommendations and entertainment content generated by the server are then delivered to the user through the device. This delivery is either automatic or adjusted based on the user's choices. For example, if the user is feeling down during the day, uplifting music and videos will be prioritized.

[0381] Furthermore, the system optimizes communication with family members based on the user's emotional state. For example, when the user is relaxed, the server can send notifications at times that facilitate communication with family members.

[0382] A concrete example of a prompt message could be: "If an elderly user is feeling down during the day, generate suggestions for uplifting music or videos." This allows the system to provide content tailored to the user's needs.

[0383] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0384] Step 1:

[0385] The device collects the user's vital data and emotional data. Specifically, it uses heart rate and body temperature sensors to acquire the user's biometric data. It also records facial expressions and voice tone using a camera and microphone. This collected data becomes the input to the collection stage. The output is the detected vital data and emotional data.

[0386] Step 2:

[0387] The terminal performs the operation of sending the collected vital data and emotional data to the server. Specifically, it encrypts the data and sends it to the server via a secure communication protocol. The input for this step is the data obtained in step 1. The output is data that the server can use for analysis.

[0388] Step 3:

[0389] The server performs data analysis using a generated AI model based on the received data. Specifically, it analyzes emotional data with an emotion engine to identify the user's current emotional state. It also performs a health assessment of the user based on health indicators. The input for this step is vital data and emotional data transmitted from the terminal. The output is an assessment result regarding the user's health and emotional state.

[0390] Step 4:

[0391] The server uses the evaluation results to generate recommendations for the user. Specifically, it selects music and content to improve the environment for relaxation. Here, emotional state is the direct input data. The output is recommendations for the user.

[0392] Step 5:

[0393] The terminal provides the user with recommendations received from the server. Its primary actions include playing relaxing music on a music playback device or displaying visual content on a screen. The input for this step is the recommendations from the server. The output is the provision of visual or auditory stimuli to the user.

[0394] Step 6:

[0395] Users input their reactions and status regarding the provided content as feedback into their devices. Specifically, they input feedback through a dedicated application on their smartphone or tablet. This feedback is then used in subsequent data analysis. The input consists of the user's impressions and opinions, and the output is feedback data sent to the server.

[0396] (Application Example 2)

[0397] 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."

[0398] In modern society, improving the physical and mental health and quality of life of the elderly has become a social challenge. Consequently, there is a growing need for technologies that support stress management and smooth communication with family members. However, current technologies make it difficult to provide individualized, comprehensive support to the elderly. Furthermore, there is a lack of means to provide appropriate support based on their emotional state.

[0399] 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.

[0400] In this invention, the server includes a sensor device for collecting the user's biometric data, an emotion recognition device for recognizing emotional states from facial and vocal data, and an adjustment device for providing information to family members at the optimal timing according to the emotional state. This enables appropriate support and optimized communication based on the emotional state of elderly individuals.

[0401] "Biometric data" refers to physical data that indicates a user's health status, including information such as heart rate and body temperature.

[0402] A "sensor device" is a device used to detect and measure a user's biometric data, and includes wearable devices and cameras.

[0403] An "analysis device" is a processing device that analyzes collected biological data to determine health status and emotional state.

[0404] A "notification device" is a means of communicating analysis results and suggestions to the user or their family, and includes smartphones and other communication devices.

[0405] A "providing device" is a system or software that generates and provides entertainment content based on the user's preferences and circumstances.

[0406] A "communication device" is a means that enables voice calls and the sending and receiving of messages between a user and their family.

[0407] An "emotion recognition device" is software or hardware that has the function of analyzing a user's face and voice to determine their emotional state.

[0408] A "regulating device" is a means of adjusting the timing and content of information provided to family members based on the user's emotional state.

[0409] This invention is a system that comprehensively supports the user's health and emotional state. The system consists of a sensor device, an analysis device, a notification device, a provision device, a communication device, an emotion recognition device, and an adjustment device.

[0410] The sensor device plays a role in collecting the user's biometric data, measuring heart rate and body temperature using wearable devices, etc. This enables real-time collection of health data.

[0411] The server analyzes data collected using an analysis device with machine learning algorithms (e.g., TensorFlow or PyTorch). This allows it to determine the user's health and emotional state, and if an abnormality is detected, it generates appropriate content to help alleviate stress.

[0412] The notification device provides information to the user or their family based on the analysis results. For example, it may send notifications about health status and recommended actions via a smartphone app.

[0413] The device generates and delivers personalized entertainment based on the user's preferences and emotional state. It can play music using the Spotify API and select video content.

[0414] Furthermore, the communication device supports communication with family members based on the emotional state analyzed by the emotion recognition device. For example, if the user is feeling stressed, the family will be notified and prompted to make a call at an appropriate time.

[0415] For example, if a user's heart rate is detected as higher than normal, the server will suggest and notify them of relaxing music. This type of processing can be made possible by utilizing generative AI models to provide optimal solutions for each individual user.

[0416] An example of a prompt to a generative AI model is: "The user's heart rate is higher than normal. Please recommend relaxing music and a breathing instruction video."

[0417] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0418] Step 1:

[0419] Users collect biometric data (heart rate, body temperature, etc.) using sensors on smartwatches or smartphones. The input is biometric data, and the output is sent to the cloud.

[0420] Step 2:

[0421] The server processes biometric data received from the cloud using an analysis device. The input is biometric data acquired from the cloud, which is processed using machine learning algorithms to evaluate the user's health status. In this process, libraries such as TensorFlow are used to identify anomalies, and the evaluation results are output.

[0422] Step 3:

[0423] The emotion recognition device analyzes the user's face and voice using the device's camera and microphone. The input consists of camera images and audio data, which are processed by an emotion analysis algorithm. This determines the user's emotional state and outputs the result.

[0424] Step 4:

[0425] The server integrates analyzed health and emotional states to generate entertainment content tailored to the specific situation. The input consists of health and emotional state assessment results; a generative AI model is used to select and output appropriate music and video content.

[0426] Step 5:

[0427] The terminal uses a notification device to present recommended entertainment content to the user. The input is content information from a server, which is output to the user through the terminal screen and speaker.

[0428] Step 6:

[0429] The server uses a control device to manage the provision of information to family members based on their emotional state. The input is the user's emotional assessment result, and it sends notifications to family members in real time and outputs information in a way that facilitates calls as needed.

[0430] Step 7:

[0431] The generative AI model processes the prompt text and proposes the next action plan. The input is the prompt text, "The user's heart rate is higher than normal. Please recommend relaxing music and a breathing instruction video." Based on this, it generates and outputs the most suitable content suggestions.

[0432] 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.

[0433] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0434] 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.

[0435] [Third Embodiment]

[0436] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0437] 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.

[0438] 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).

[0439] 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.

[0440] 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.

[0441] 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).

[0442] 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.

[0443] 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.

[0444] 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.

[0445] 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.

[0446] 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.

[0447] 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".

[0448] This invention is a generative AI agent system that comprehensively supports the lives of the elderly. This system has a series of functions that support user health management, entertainment provision, and communication with family members in remote locations.

[0449] health care

[0450] The terminal collects vital data from the wearable device worn by the user. The collected data, such as heart rate and blood pressure, is used to understand the user's daily health status. The server receives this data and analyzes it using AI algorithms. For example, if an abnormal blood pressure fluctuation is detected, the server sends that information to the terminal and notifies the user. This notification serves as a trigger for the user to take appropriate medical action.

[0451] Providing entertainment

[0452] The device learns the user's past preferences and behavioral patterns and generates entertainment content based on them. This includes music, reading, games, and more. The server analyzes the collected data and determines the content best suited to the user. For example, a user seeking relaxation might be offered a playlist of calming music.

[0453] communication

[0454] The server manages the scheduling of video calls with family members. The device automatically starts video calls at the designated time, providing an environment where users and family members can communicate smoothly. This makes it possible to maintain emotional connections that transcend physical distance.

[0455] This system allows seniors to enjoy a richer life tailored to their individual preferences, going beyond mere health monitoring. Furthermore, the use of AI technology enables efficient and personalized life support, supporting a safe and stable life.

[0456] The following describes the processing flow.

[0457] Step 1:

[0458] The terminal collects vital data from wearable devices worn by the user. This method uses Bluetooth or Wi-Fi connectivity to acquire data in real time.

[0459] Step 2:

[0460] The device transmits the collected vital data to the server via the internet. The data is encrypted and sent through a secure protocol.

[0461] Step 3:

[0462] The server analyzes the received vital data using an AI algorithm. It compares this data with past data and medical standards to detect abnormalities.

[0463] Step 4:

[0464] The server quickly generates an alert if an anomaly is detected based on the analysis results. This alert includes the type of anomaly and recommended actions.

[0465] Step 5:

[0466] The device receives alert notifications from the server. These notifications are communicated directly to the user via pop-up messages or audio alerts.

[0467] Step 6:

[0468] The device receives entertainment content from the server based on the user's preferences. Personalized content is delivered by utilizing the user's past action logs.

[0469] Step 7:

[0470] The server holds call data for automatically scheduling video calls with family members. A connection is established between the user's and family members' devices.

[0471] Step 8:

[0472] Users consume entertainment content on their devices as needed and communicate with family through video calls. This enriches their daily lives.

[0473] (Example 1)

[0474] 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."

[0475] There is a need for a system that provides integrated support for the health management of the elderly, the provision of individually optimized entertainment, and the smooth communication with family and friends who live far away. Existing technologies often provide these elements separately, making it difficult for the elderly and their families to have a consistent experience that allows them to live their daily lives with peace of mind.

[0476] 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.

[0477] In this invention, the server includes recording means for collecting biometric data, diagnostic means, communication means for issuing warnings, distribution means for providing preference information, and connection means for communicating with individuals. This enables real-time management of health status, provision of personalized entertainment, and easy communication.

[0478] "Biometric data" refers to numerical physical information such as heart rate, blood pressure, and body temperature used to evaluate a user's health status.

[0479] "Recording means" is a general term for devices and systems used to collect and store biometric data.

[0480] "Diagnostic methods" refer to techniques and technologies used to analyze collected biological data and detect abnormalities in health conditions.

[0481] "Communication methods" refer to communication functions and mechanisms for notifying users of analysis results and warning information.

[0482] "Means of providing preference information" refers to the technologies and processes for creating and delivering content based on users' past behavior and preferences.

[0483] "Means of connection for communicating with people" refers to methods or devices that enable the exchange of information with people in remote locations using communication networks such as the internet.

[0484] This invention is a comprehensive life support system for the elderly, integrating health management, entertainment provision, and communication promotion. Specific embodiments for implementing this invention are described below.

[0485] health care

[0486] The device collects the user's biometric data using a smartwatch or other wearable device. This allows for real-time acquisition of data such as heart rate, blood pressure, and body temperature, which is then aggregated on the connected device via Bluetooth.

[0487] The server receives this biometric data and analyzes it using an AI algorithm. This analysis allows the system to detect abnormalities in the collected data and send immediate warnings to the user.

[0488] For example, if a user's blood pressure rises suddenly, the server sends a notification to the terminal, providing the user with a message such as, "Your blood pressure is high. Please consult a doctor."

[0489] Providing entertainment

[0490] The device stores the user's past music playback and game play history and sends that data to the server.

[0491] The server uses a generative AI model to learn user preferences and deliver optimal entertainment content. This includes user-specific music playlists and interesting reading material.

[0492] For example, if the server determines that the user is seeking relaxation, it will suggest a playlist of calming music through the device.

[0493] communication

[0494] The server schedules and manages video calls between the user and family members in remote locations. Based on the call time set by the user, the device automatically starts the video call.

[0495] The device establishes a connection between the user and their family when a video call is initiated, providing an environment that supports smooth communication.

[0496] For example, if a video call with family is scheduled for 3 PM every Saturday, the device will automatically start the video call at that time, allowing the user to easily enjoy the conversation.

[0497] Example prompt: "Please explain the mechanism of an AI system that monitors the health status of elderly people and issues alerts in case of abnormalities."

[0498] Thus, this invention utilizes a generative AI model to provide lifestyle support tailored to individual needs, thereby helping elderly people live safe and fulfilling lives.

[0499] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0500] Step 1:

[0501] The terminal collects the user's biometric data (heart rate, blood pressure, body temperature) in real time from the wearable device. This data is sent to the terminal and aggregated on a smartphone via Bluetooth. The input is biometric information from the wearable device, and the output is vital data stored on the terminal.

[0502] Step 2:

[0503] The device transmits aggregated biometric data to a server via the internet. The server receives this data and begins analysis processing using an AI algorithm. The input is the biometric data transferred from the device, and the output is a diagnostic result indicating whether or not there are abnormalities. The data is compared to health standards to detect abnormalities in heart rate and blood pressure.

[0504] Step 3:

[0505] Based on the analysis results, the server sends a warning notification to the terminal if necessary. This can be an audio notification or displayed as a message on the screen. The input is the diagnostic result, and the output is the warning notification conveyed to the user.

[0506] Step 4:

[0507] The device collects the user's music playback history and behavioral patterns and sends this data to the server. The input is past preference data, and the output is data to be sent to the server.

[0508] Step 5:

[0509] The server analyzes the received preference data using a generating AI model to determine the most suitable entertainment content for the user. The input is preference data, and the output is recommended entertainment content. The server generates lists of music, reading materials, and other similar content.

[0510] Step 6:

[0511] The server sends appropriate entertainment content to the device. The device presents the content to the user, making it easily accessible. The input is content information from the server, and the output is a list of content on the user's screen.

[0512] Step 7:

[0513] The server manages the scheduling of video calls between the user and their family and instructs the device to automatically start the call at the scheduled time. The input is the schedule information, and the output is the instruction to start the video call.

[0514] Step 8:

[0515] The device launches the video call app at the time specified by the user and automatically establishes a connection with family members. The input is the call initiation command from the server, and the output is the communication connection established by the call initiation.

[0516] Through this series of processing steps, users can receive comprehensive support ranging from health management to entertainment and communication assistance.

[0517] (Application Example 1)

[0518] 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."

[0519] There is a lack of integrated support systems that meet the health management, entertainment, and communication needs of older adults. This results in insufficient support for older adults to live safe and comfortable lives.

[0520] 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.

[0521] In this invention, the server includes means for collecting physiological data, means for identifying abnormalities based on criteria, and means for providing optimized digital information. This enables real-time monitoring of the health status of the elderly, provision of entertainment tailored to individual preferences, and efficient communication with people in remote locations.

[0522] "Physiological data" refers to information about the user's body, including vital signs such as heart rate and blood pressure.

[0523] "Sensing means" refers to devices and methods for collecting physiological data, such as wearable devices.

[0524] "Analysis means" refers to algorithms and devices used to analyze collected data and identify anomalies and trends.

[0525] "Communication methods" refer to methods or devices for conveying information to users or stakeholders based on analysis results, and include sending notification messages.

[0526] "Means of delivery" refers to systems and methods for supplying information and services tailored to user preferences, such as recommendations for entertainment content.

[0527] "Communication means" refers to methods or devices that enable the exchange of information with a person in a remote location, and video call functions are an example of this.

[0528] "Real-time monitoring" refers to the process of instantly understanding and continuously observing the user's health status.

[0529] "Optimized digital information" refers to information that is structured in a personalized manner based on the user's past preferences and behavior.

[0530] This invention incorporates the following elements to realize a system that comprehensively supports the lives of the elderly. The server collects information via sensor means to acquire physiological data from wearable devices worn by the user. Specific examples of devices include health management devices that monitor heart rate and blood pressure. The data collected by the sensor means is transmitted to a server in the cloud, where anomalies are identified by AI-based analysis means.

[0531] When the analysis system processes the data, if an anomaly is detected, the user and relevant caregivers are notified in real time through a notification system. This allows for the rapid implementation of appropriate medical measures. The hardware consists of a standard communication device for internet connectivity, while the software side utilizes machine learning libraries such as TensorFlow and Scikit-learn to handle AI analysis.

[0532] Simultaneously, optimized digital information, i.e., entertainment content, is delivered to users based on their past preferences using various delivery methods. This involves APIs from music streaming services and movie viewing platforms, for example, providing users with personalized content through Spotify or Netflix.

[0533] Furthermore, depending on the communication method, the server can schedule video calls with family and friends and notify the user in advance that the call will connect. This helps maintain emotional connections with family members who are in remote locations. For example, by utilizing the Google Calendar API to automatically connect video calls at predetermined times, smooth communication can be achieved.

[0534] An example of a prompt message would be: "Build an app that monitors Fitbit data in real time, sends notifications to care staff if an anomaly is detected, and provides recommended entertainment activities."

[0535] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0536] Step 1:

[0537] The terminal acquires physiological data from the wearable device worn by the user. This data includes heart rate and blood pressure. The acquired data is transmitted to the terminal using communication methods such as Bluetooth and stored in a format prepared for subsequent processing. The input is physiological data, and the output is the formatted data stored on the terminal.

[0538] Step 2:

[0539] The server receives physiological data transmitted from the terminal. This data is stored in a database and then analyzed using an AI algorithm. Specifically, a machine learning model is used to analyze the data to evaluate whether anomalies exist. The input is physiological data, and the output is the anomaly detection result.

[0540] Step 3:

[0541] If the analysis results are abnormal, the server will send a notification to the terminal using a notification system. The notification will include the detected abnormality and recommended actions. This action will enable users and caregivers to take prompt action. The input is the abnormality detection result, and the output is the notification information.

[0542] Step 4:

[0543] The device uses a delivery method to reference the user's past preference data and suggests optimized digital information, i.e., entertainment content, to the user. For example, via a music streaming service API, calming music is provided to a user who wants to relax. The input is the user's preference data, and the output is the suggested entertainment content.

[0544] Step 5:

[0545] The server uses communication methods to schedule video calls with family and friends and configures the system to automatically connect at the specified time. The terminal sends a notification to the user informing them of the time the call will begin. The input is the call schedule information, and the output is the preparation for starting the video call.

[0546] 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.

[0547] This invention relates to a generative AI agent system equipped with an emotion engine that analyzes the user's vital data and emotional state to comprehensively support the lives of the elderly. This system includes a variety of functions for user health management, personalized entertainment provision, and enhancing communication with family.

[0548] Emotional Recognition and Health Management

[0549] The device uses an emotion engine to analyze the user's facial expressions and voice along with their vital data to recognize their emotions. This data is collected from multiple sensors and sent to a server. The server analyzes this information using an AI algorithm to comprehensively evaluate the user's health and emotional state. For example, if the server determines that the user is experiencing stress, it will suggest a relaxing environment to help reduce stress.

[0550] Optimizing entertainment

[0551] The server generates and provides entertainment content based on the user's emotional state, as recognized by the emotion engine. The terminal delivers the received content to the user and supports their selection as needed. For example, if the server determines that the user is feeling down, uplifting music or video content will be suggested preferentially.

[0552] Emotion-based communication support

[0553] Communication with family members is further optimized based on the results of emotion recognition. The server considers the user's emotional state and suggests contacting family members at the appropriate time. Furthermore, it can analyze changes in emotions in real time during a call and use the results to help deepen the conversation. For example, before a call begins, it can determine if the user is relaxed and use that information to provide advice on how to tailor the conversation.

[0554] In this way, this system utilizes an emotion engine to support the user's mental and physical health in an integrated manner, providing an innovative approach to improving the quality of life for the elderly.

[0555] The following describes the processing flow.

[0556] Step 1:

[0557] The terminal collects vital data from the wearable device worn by the user. At the same time, it uses a camera and microphone to capture the user's facial expressions and voice, and passes this data to the emotion engine.

[0558] Step 2:

[0559] The device packages the collected vital and emotional data and sends it to a server via the internet. The data is encrypted to protect privacy.

[0560] Step 3:

[0561] The server uses AI to analyze received vital data and assess the user's health status. Furthermore, an emotion engine processes emotional data to identify the user's emotional state.

[0562] Step 4:

[0563] Based on the analysis results, the server comprehensively assesses the user's health and emotional state and determines the necessary response or alert. If an anomaly is detected, an alert is generated immediately.

[0564] Step 5:

[0565] The device receives alerts and status information from the server and notifies the user. Notifications are made via voice messages, visual alerts, or vibrations to attract the user's attention.

[0566] Step 6:

[0567] The server generates and sends optimized entertainment content to the device based on the user's emotional state. The content is designed to improve the user's mood.

[0568] Step 7:

[0569] The device provides the user with received entertainment content. The user can interact with and enjoy it. User feedback is logged so that it can be used to improve future services.

[0570] Step 8:

[0571] The server schedules video calls with family members, taking into account the user's emotional state. By contacting them at the appropriate time, it helps reduce feelings of isolation and supports smoother communication.

[0572] (Example 2)

[0573] 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."

[0574] In modern society, the health management and emotional support issues faced by the elderly are significant. However, conventional technologies lack the means to comprehensively analyze users' vital data and emotional data to provide immediate and appropriate health management guidance and emotional care. This lack contributes to a decline in the quality of life for the elderly.

[0575] 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.

[0576] In this invention, the server includes detection means for collecting the user's vital data and emotional data, analysis means for analyzing the vital data and emotional data and evaluating the user's health and emotional state through a generated AI model, and recommendation means for providing the user with a relaxing environment based on the analysis results. This makes it possible to grasp the user's physical and mental state in real time and provide appropriate health management and mental support.

[0577] "Vital data" refers to numerical data that indicates the basic health status of a user's body, such as heart rate, body temperature, and blood pressure.

[0578] "Emotional data" refers to data about a user's emotional state, inferred from their facial expressions, tone of voice, and other factors.

[0579] A "generative AI model" is an algorithm that uses artificial intelligence to analyze data and predict a user's emotions and health status.

[0580] "Detection means" refers to equipment or technology for collecting a user's vital data and emotional data.

[0581] An "analysis tool" is a system that analyzes collected data and objectively evaluates the user's condition.

[0582] "Recommended means of providing a relaxing environment" refers to a function that adjusts the environment and provides content to help users relax based on their current state.

[0583] A "means of delivery" refers to a system for presenting users with useful information or entertainment.

[0584] "Communication methods" refer to technologies used to exchange information between a user and their family or other communication partners.

[0585] This invention is a system designed to improve the quality of life by monitoring a user's health and emotional state in real time. The system is primarily realized through the collaboration of a server, a terminal, and the user.

[0586] The device is equipped with sensors to collect the user's vital and emotional data. This data, including heart rate, body temperature, voice tone, and facial expression changes, is acquired in real time. Specific sensor devices include biosensors, cameras, and microphones.

[0587] The collected data is sent from the device to the server. The server uses a generative AI model to analyze this data. Through this analysis, the server assesses the user's health and emotional state and generates recommendations to provide a relaxing environment as needed. For example, if the server determines that the user is stressed, it will suggest relaxing music or meditation content.

[0588] The recommendations and entertainment content generated by the server are then delivered to the user through the device. This delivery is either automatic or adjusted based on the user's choices. For example, if the user is feeling down during the day, uplifting music and videos will be prioritized.

[0589] Furthermore, the system optimizes communication with family members based on the user's emotional state. For example, when the user is relaxed, the server can send notifications at times that facilitate communication with family members.

[0590] A concrete example of a prompt message could be: "If an elderly user is feeling down during the day, generate suggestions for uplifting music or videos." This allows the system to provide content tailored to the user's needs.

[0591] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0592] Step 1:

[0593] The device collects the user's vital data and emotional data. Specifically, it uses heart rate and body temperature sensors to acquire the user's biometric data. It also records facial expressions and voice tone using a camera and microphone. This collected data becomes the input to the collection stage. The output is the detected vital data and emotional data.

[0594] Step 2:

[0595] The terminal performs the operation of sending the collected vital data and emotional data to the server. Specifically, it encrypts the data and sends it to the server via a secure communication protocol. The input for this step is the data obtained in step 1. The output is data that the server can use for analysis.

[0596] Step 3:

[0597] The server performs data analysis using a generated AI model based on the received data. Specifically, it analyzes emotional data with an emotion engine to identify the user's current emotional state. It also performs a health assessment of the user based on health indicators. The input for this step is vital data and emotional data transmitted from the terminal. The output is an assessment result regarding the user's health and emotional state.

[0598] Step 4:

[0599] The server uses the evaluation results to generate recommendations for the user. Specifically, it selects music and content to improve the environment for relaxation. Here, emotional state is the direct input data. The output is recommendations for the user.

[0600] Step 5:

[0601] The terminal provides the user with recommendations received from the server. Its primary actions include playing relaxing music on a music playback device or displaying visual content on a screen. The input for this step is the recommendations from the server. The output is the provision of visual or auditory stimuli to the user.

[0602] Step 6:

[0603] Users input their reactions and status regarding the provided content as feedback into their devices. Specifically, they input feedback through a dedicated application on their smartphone or tablet. This feedback is then used in subsequent data analysis. The input consists of the user's impressions and opinions, and the output is feedback data sent to the server.

[0604] (Application Example 2)

[0605] 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."

[0606] In modern society, improving the physical and mental health and quality of life of the elderly has become a social challenge. Consequently, there is a growing need for technologies that support stress management and smooth communication with family members. However, current technologies make it difficult to provide individualized, comprehensive support to the elderly. Furthermore, there is a lack of means to provide appropriate support based on their emotional state.

[0607] 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.

[0608] In this invention, the server includes a sensor device for collecting the user's biometric data, an emotion recognition device for recognizing emotional states from facial and vocal data, and an adjustment device for providing information to family members at the optimal timing according to the emotional state. This enables appropriate support and optimized communication based on the emotional state of elderly individuals.

[0609] "Biometric data" refers to physical data that indicates a user's health status, including information such as heart rate and body temperature.

[0610] A "sensor device" is a device used to detect and measure a user's biometric data, and includes wearable devices and cameras.

[0611] An "analysis device" is a processing device that analyzes collected biological data to determine health status and emotional state.

[0612] A "notification device" is a means of communicating analysis results and suggestions to the user or their family, and includes smartphones and other communication devices.

[0613] A "providing device" is a system or software that generates and provides entertainment content based on the user's preferences and circumstances.

[0614] A "communication device" is a means that enables voice calls and the sending and receiving of messages between a user and their family.

[0615] An "emotion recognition device" is software or hardware that has the function of analyzing a user's face and voice to determine their emotional state.

[0616] A "regulating device" is a means of adjusting the timing and content of information provided to family members based on the user's emotional state.

[0617] This invention is a system that comprehensively supports the user's health and emotional state. The system consists of a sensor device, an analysis device, a notification device, a provision device, a communication device, an emotion recognition device, and an adjustment device.

[0618] The sensor device plays a role in collecting the user's biometric data, measuring heart rate and body temperature using wearable devices, etc. This enables real-time collection of health data.

[0619] The server analyzes data collected using an analysis device with machine learning algorithms (e.g., TensorFlow or PyTorch). This allows it to determine the user's health and emotional state, and if an abnormality is detected, it generates appropriate content to help alleviate stress.

[0620] The notification device provides information to the user or their family based on the analysis results. For example, it may send notifications about health status and recommended actions via a smartphone app.

[0621] The device generates and delivers personalized entertainment based on the user's preferences and emotional state. It can play music using the Spotify API and select video content.

[0622] Furthermore, the communication device supports communication with family members based on the emotional state analyzed by the emotion recognition device. For example, if the user is feeling stressed, the family will be notified and prompted to make a call at an appropriate time.

[0623] For example, if a user's heart rate is detected as higher than normal, the server will suggest and notify them of relaxing music. This type of processing can be made possible by utilizing generative AI models to provide optimal solutions for each individual user.

[0624] An example of a prompt to a generative AI model is: "The user's heart rate is higher than normal. Please recommend relaxing music and a breathing instruction video."

[0625] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0626] Step 1:

[0627] Users collect biometric data (heart rate, body temperature, etc.) using sensors on smartwatches or smartphones. The input is biometric data, and the output is sent to the cloud.

[0628] Step 2:

[0629] The server processes biometric data received from the cloud using an analysis device. The input is biometric data acquired from the cloud, which is processed using machine learning algorithms to evaluate the user's health status. In this process, libraries such as TensorFlow are used to identify anomalies, and the evaluation results are output.

[0630] Step 3:

[0631] The emotion recognition device analyzes the user's face and voice using the device's camera and microphone. The input consists of camera images and audio data, which are processed by an emotion analysis algorithm. This determines the user's emotional state and outputs the result.

[0632] Step 4:

[0633] The server integrates analyzed health and emotional states to generate entertainment content tailored to the specific situation. The input consists of health and emotional state assessment results; a generative AI model is used to select and output appropriate music and video content.

[0634] Step 5:

[0635] The terminal uses a notification device to present recommended entertainment content to the user. The input is content information from a server, which is output to the user through the terminal screen and speaker.

[0636] Step 6:

[0637] The server uses a control device to manage the provision of information to family members based on their emotional state. The input is the user's emotional assessment result, and it sends notifications to family members in real time and outputs information in a way that facilitates calls as needed.

[0638] Step 7:

[0639] The generative AI model processes the prompt text and proposes the next action plan. The input is the prompt text, "The user's heart rate is higher than normal. Please recommend relaxing music and a breathing instruction video." Based on this, it generates and outputs the most suitable content suggestions.

[0640] 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.

[0641] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0642] 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.

[0643] [Fourth Embodiment]

[0644] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0645] 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.

[0646] 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).

[0647] 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.

[0648] 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.

[0649] 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).

[0650] 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.

[0651] 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.

[0652] 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.

[0653] 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.

[0654] 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.

[0655] 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.

[0656] 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".

[0657] This invention is a generative AI agent system that comprehensively supports the lives of the elderly. This system has a series of functions that support user health management, entertainment provision, and communication with family members in remote locations.

[0658] health care

[0659] The terminal collects vital data from the wearable device worn by the user. The collected data, such as heart rate and blood pressure, is used to understand the user's daily health status. The server receives this data and analyzes it using AI algorithms. For example, if an abnormal blood pressure fluctuation is detected, the server sends that information to the terminal and notifies the user. This notification serves as a trigger for the user to take appropriate medical action.

[0660] Providing entertainment

[0661] The device learns the user's past preferences and behavioral patterns and generates entertainment content based on them. This includes music, reading, games, and more. The server analyzes the collected data and determines the content best suited to the user. For example, a user seeking relaxation might be offered a playlist of calming music.

[0662] communication

[0663] The server manages the scheduling of video calls with family members. The device automatically starts video calls at the designated time, providing an environment where users and family members can communicate smoothly. This makes it possible to maintain emotional connections that transcend physical distance.

[0664] This system allows seniors to enjoy a richer life tailored to their individual preferences, going beyond mere health monitoring. Furthermore, the use of AI technology enables efficient and personalized life support, supporting a safe and stable life.

[0665] The following describes the processing flow.

[0666] Step 1:

[0667] The terminal collects vital data from wearable devices worn by the user. This method uses Bluetooth or Wi-Fi connectivity to acquire data in real time.

[0668] Step 2:

[0669] The device transmits the collected vital data to the server via the internet. The data is encrypted and sent through a secure protocol.

[0670] Step 3:

[0671] The server analyzes the received vital data using an AI algorithm. It compares this data with past data and medical standards to detect abnormalities.

[0672] Step 4:

[0673] The server quickly generates an alert if an anomaly is detected based on the analysis results. This alert includes the type of anomaly and recommended actions.

[0674] Step 5:

[0675] The device receives alert notifications from the server. These notifications are communicated directly to the user via pop-up messages or audio alerts.

[0676] Step 6:

[0677] The device receives entertainment content from the server based on the user's preferences. Personalized content is delivered by utilizing the user's past action logs.

[0678] Step 7:

[0679] The server holds call data for automatically scheduling video calls with family members. A connection is established between the user's and family members' devices.

[0680] Step 8:

[0681] Users consume entertainment content on their devices as needed and communicate with family through video calls. This enriches their daily lives.

[0682] (Example 1)

[0683] 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".

[0684] There is a need for a system that provides integrated support for the health management of the elderly, the provision of individually optimized entertainment, and the smooth communication with family and friends who live far away. Existing technologies often provide these elements separately, making it difficult for the elderly and their families to have a consistent experience that allows them to live their daily lives with peace of mind.

[0685] 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.

[0686] In this invention, the server includes recording means for collecting biometric data, diagnostic means, communication means for issuing warnings, distribution means for providing preference information, and connection means for communicating with individuals. This enables real-time management of health status, provision of personalized entertainment, and easy communication.

[0687] "Biometric data" refers to numerical physical information such as heart rate, blood pressure, and body temperature used to evaluate a user's health status.

[0688] "Recording means" is a general term for devices and systems used to collect and store biometric data.

[0689] "Diagnostic methods" refer to techniques and technologies used to analyze collected biological data and detect abnormalities in health conditions.

[0690] "Communication methods" refer to communication functions and mechanisms for notifying users of analysis results and warning information.

[0691] "Means of providing preference information" refers to the technologies and processes for creating and delivering content based on users' past behavior and preferences.

[0692] "Means of connection for communicating with people" refers to methods or devices that enable the exchange of information with people in remote locations using communication networks such as the internet.

[0693] This invention is a comprehensive life support system for the elderly, integrating health management, entertainment provision, and communication promotion. Specific embodiments for implementing this invention are described below.

[0694] health care

[0695] The device collects the user's biometric data using a smartwatch or other wearable device. This allows for real-time acquisition of data such as heart rate, blood pressure, and body temperature, which is then aggregated on the connected device via Bluetooth.

[0696] The server receives this biometric data and analyzes it using an AI algorithm. This analysis allows the system to detect abnormalities in the collected data and send immediate warnings to the user.

[0697] For example, if a user's blood pressure rises suddenly, the server sends a notification to the terminal, providing the user with a message such as, "Your blood pressure is high. Please consult a doctor."

[0698] Providing entertainment

[0699] The device stores the user's past music playback and game play history and sends that data to the server.

[0700] The server uses a generative AI model to learn user preferences and deliver optimal entertainment content. This includes user-specific music playlists and interesting reading material.

[0701] For example, if the server determines that the user is seeking relaxation, it will suggest a playlist of calming music through the device.

[0702] communication

[0703] The server schedules and manages video calls between the user and family members in remote locations. Based on the call time set by the user, the device automatically starts the video call.

[0704] The device establishes a connection between the user and their family when a video call is initiated, providing an environment that supports smooth communication.

[0705] For example, if a video call with family is scheduled for 3 PM every Saturday, the device will automatically start the video call at that time, allowing the user to easily enjoy the conversation.

[0706] Example prompt: "Please explain the mechanism of an AI system that monitors the health status of elderly people and issues alerts in case of abnormalities."

[0707] Thus, this invention utilizes a generative AI model to provide lifestyle support tailored to individual needs, thereby helping elderly people live safe and fulfilling lives.

[0708] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0709] Step 1:

[0710] The terminal collects the user's biometric data (heart rate, blood pressure, body temperature) in real time from the wearable device. This data is sent to the terminal and aggregated on a smartphone via Bluetooth. The input is biometric information from the wearable device, and the output is vital data stored on the terminal.

[0711] Step 2:

[0712] The device transmits aggregated biometric data to a server via the internet. The server receives this data and begins analysis processing using an AI algorithm. The input is the biometric data transferred from the device, and the output is a diagnostic result indicating whether or not there are abnormalities. The data is compared to health standards to detect abnormalities in heart rate and blood pressure.

[0713] Step 3:

[0714] Based on the analysis results, the server sends a warning notification to the terminal if necessary. This can be an audio notification or displayed as a message on the screen. The input is the diagnostic result, and the output is the warning notification conveyed to the user.

[0715] Step 4:

[0716] The device collects the user's music playback history and behavioral patterns and sends this data to the server. The input is past preference data, and the output is data to be sent to the server.

[0717] Step 5:

[0718] The server analyzes the received preference data using a generating AI model to determine the most suitable entertainment content for the user. The input is preference data, and the output is recommended entertainment content. The server generates lists of music, reading materials, and other similar content.

[0719] Step 6:

[0720] The server sends appropriate entertainment content to the device. The device presents the content to the user, making it easily accessible. The input is content information from the server, and the output is a list of content on the user's screen.

[0721] Step 7:

[0722] The server manages the scheduling of video calls between the user and their family and instructs the device to automatically start the call at the scheduled time. The input is the schedule information, and the output is the instruction to start the video call.

[0723] Step 8:

[0724] The device launches the video call app at the time specified by the user and automatically establishes a connection with family members. The input is the call initiation command from the server, and the output is the communication connection established by the call initiation.

[0725] Through this series of processing steps, users can receive comprehensive support ranging from health management to entertainment and communication assistance.

[0726] (Application Example 1)

[0727] 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".

[0728] There is a lack of integrated support systems that meet the health management, entertainment, and communication needs of older adults. This results in insufficient support for older adults to live safe and comfortable lives.

[0729] 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.

[0730] In this invention, the server includes means for collecting physiological data, means for identifying abnormalities based on criteria, and means for providing optimized digital information. This enables real-time monitoring of the health status of the elderly, provision of entertainment tailored to individual preferences, and efficient communication with people in remote locations.

[0731] "Physiological data" refers to information about the user's body, including vital signs such as heart rate and blood pressure.

[0732] "Sensing means" refers to devices and methods for collecting physiological data, such as wearable devices.

[0733] "Analysis means" refers to algorithms and devices used to analyze collected data and identify anomalies and trends.

[0734] "Communication methods" refer to methods or devices for conveying information to users or stakeholders based on analysis results, and include sending notification messages.

[0735] "Means of delivery" refers to systems and methods for supplying information and services tailored to user preferences, such as recommendations for entertainment content.

[0736] "Communication means" refers to methods or devices that enable the exchange of information with a person in a remote location, and video call functions are an example of this.

[0737] "Real-time monitoring" refers to the process of instantly understanding and continuously observing the user's health status.

[0738] "Optimized digital information" refers to information that is structured in a personalized manner based on the user's past preferences and behavior.

[0739] This invention incorporates the following elements to realize a system that comprehensively supports the lives of the elderly. The server collects information via sensor means to acquire physiological data from wearable devices worn by the user. Specific examples of devices include health management devices that monitor heart rate and blood pressure. The data collected by the sensor means is transmitted to a server in the cloud, where anomalies are identified by AI-based analysis means.

[0740] When the analysis system processes the data, if an anomaly is detected, the user and relevant caregivers are notified in real time through a notification system. This allows for the rapid implementation of appropriate medical measures. The hardware consists of a standard communication device for internet connectivity, while the software side utilizes machine learning libraries such as TensorFlow and Scikit-learn to handle AI analysis.

[0741] Simultaneously, optimized digital information, i.e., entertainment content, is delivered to users based on their past preferences using various delivery methods. This involves APIs from music streaming services and movie viewing platforms, for example, providing users with personalized content through Spotify or Netflix.

[0742] Furthermore, depending on the communication method, the server can schedule video calls with family and friends and notify the user in advance that the call will connect. This helps maintain emotional connections with family members who are in remote locations. For example, by utilizing the Google Calendar API to automatically connect video calls at predetermined times, smooth communication can be achieved.

[0743] An example of a prompt message would be: "Build an app that monitors Fitbit data in real time, sends notifications to care staff if an anomaly is detected, and provides recommended entertainment activities."

[0744] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0745] Step 1:

[0746] The terminal acquires physiological data from the wearable device worn by the user. This data includes heart rate and blood pressure. The acquired data is transmitted to the terminal using communication methods such as Bluetooth and stored in a format prepared for subsequent processing. The input is physiological data, and the output is the formatted data stored on the terminal.

[0747] Step 2:

[0748] The server receives physiological data transmitted from the terminal. This data is stored in a database and then analyzed using an AI algorithm. Specifically, a machine learning model is used to analyze the data to evaluate whether anomalies exist. The input is physiological data, and the output is the anomaly detection result.

[0749] Step 3:

[0750] If the analysis results are abnormal, the server will send a notification to the terminal using a notification system. The notification will include the detected abnormality and recommended actions. This action will enable users and caregivers to take prompt action. The input is the abnormality detection result, and the output is the notification information.

[0751] Step 4:

[0752] The device uses a delivery method to reference the user's past preference data and suggests optimized digital information, i.e., entertainment content, to the user. For example, via a music streaming service API, calming music is provided to a user who wants to relax. The input is the user's preference data, and the output is the suggested entertainment content.

[0753] Step 5:

[0754] The server uses communication methods to schedule video calls with family and friends and configures the system to automatically connect at the specified time. The terminal sends a notification to the user informing them of the time the call will begin. The input is the call schedule information, and the output is the preparation for starting the video call.

[0755] 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.

[0756] This invention relates to a generative AI agent system equipped with an emotion engine that analyzes the user's vital data and emotional state to comprehensively support the lives of the elderly. This system includes a variety of functions for user health management, personalized entertainment provision, and enhancing communication with family.

[0757] Emotional Recognition and Health Management

[0758] The device uses an emotion engine to analyze the user's facial expressions and voice along with their vital data to recognize their emotions. This data is collected from multiple sensors and sent to a server. The server analyzes this information using an AI algorithm to comprehensively evaluate the user's health and emotional state. For example, if the server determines that the user is experiencing stress, it will suggest a relaxing environment to help reduce stress.

[0759] Optimizing entertainment

[0760] The server generates and provides entertainment content based on the user's emotional state, as recognized by the emotion engine. The terminal delivers the received content to the user and supports their selection as needed. For example, if the server determines that the user is feeling down, uplifting music or video content will be suggested preferentially.

[0761] Emotion-based communication support

[0762] Communication with family members is further optimized based on the results of emotion recognition. The server considers the user's emotional state and suggests contacting family members at the appropriate time. Furthermore, it can analyze changes in emotions in real time during a call and use the results to help deepen the conversation. For example, before a call begins, it can determine if the user is relaxed and use that information to provide advice on how to tailor the conversation.

[0763] In this way, this system utilizes an emotion engine to support the user's mental and physical health in an integrated manner, providing an innovative approach to improving the quality of life for the elderly.

[0764] The following describes the processing flow.

[0765] Step 1:

[0766] The terminal collects vital data from the wearable device worn by the user. At the same time, it uses a camera and microphone to capture the user's facial expressions and voice, and passes this data to the emotion engine.

[0767] Step 2:

[0768] The device packages the collected vital and emotional data and sends it to a server via the internet. The data is encrypted to protect privacy.

[0769] Step 3:

[0770] The server uses AI to analyze received vital data and assess the user's health status. Furthermore, an emotion engine processes emotional data to identify the user's emotional state.

[0771] Step 4:

[0772] Based on the analysis results, the server comprehensively assesses the user's health and emotional state and determines the necessary response or alert. If an anomaly is detected, an alert is generated immediately.

[0773] Step 5:

[0774] The device receives alerts and status information from the server and notifies the user. Notifications are made via voice messages, visual alerts, or vibrations to attract the user's attention.

[0775] Step 6:

[0776] The server generates and sends optimized entertainment content to the device based on the user's emotional state. The content is designed to improve the user's mood.

[0777] Step 7:

[0778] The device provides the user with received entertainment content. The user can interact with and enjoy it. User feedback is logged so that it can be used to improve future services.

[0779] Step 8:

[0780] The server schedules video calls with family members, taking into account the user's emotional state. By contacting them at the appropriate time, it helps reduce feelings of isolation and supports smoother communication.

[0781] (Example 2)

[0782] 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".

[0783] In modern society, the health management and emotional support issues faced by the elderly are significant. However, conventional technologies lack the means to comprehensively analyze users' vital data and emotional data to provide immediate and appropriate health management guidance and emotional care. This lack contributes to a decline in the quality of life for the elderly.

[0784] 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.

[0785] In this invention, the server includes detection means for collecting the user's vital data and emotional data, analysis means for analyzing the vital data and emotional data and evaluating the user's health and emotional state through a generated AI model, and recommendation means for providing the user with a relaxing environment based on the analysis results. This makes it possible to grasp the user's physical and mental state in real time and provide appropriate health management and mental support.

[0786] "Vital data" refers to numerical data that indicates the basic health status of a user's body, such as heart rate, body temperature, and blood pressure.

[0787] "Emotional data" refers to data about a user's emotional state, inferred from their facial expressions, tone of voice, and other factors.

[0788] A "generative AI model" is an algorithm that uses artificial intelligence to analyze data and predict a user's emotions and health status.

[0789] "Detection means" refers to equipment or technology for collecting a user's vital data and emotional data.

[0790] An "analysis tool" is a system that analyzes collected data and objectively evaluates the user's condition.

[0791] "Recommended means of providing a relaxing environment" refers to a function that adjusts the environment and provides content to help users relax based on their current state.

[0792] A "means of delivery" refers to a system for presenting users with useful information or entertainment.

[0793] "Communication methods" refer to technologies used to exchange information between a user and their family or other communication partners.

[0794] This invention is a system designed to improve the quality of life by monitoring a user's health and emotional state in real time. The system is primarily realized through the collaboration of a server, a terminal, and the user.

[0795] The device is equipped with sensors to collect the user's vital and emotional data. This data, including heart rate, body temperature, voice tone, and facial expression changes, is acquired in real time. Specific sensor devices include biosensors, cameras, and microphones.

[0796] The collected data is sent from the device to the server. The server uses a generative AI model to analyze this data. Through this analysis, the server assesses the user's health and emotional state and generates recommendations to provide a relaxing environment as needed. For example, if the server determines that the user is stressed, it will suggest relaxing music or meditation content.

[0797] The recommendations and entertainment content generated by the server are then delivered to the user through the device. This delivery is either automatic or adjusted based on the user's choices. For example, if the user is feeling down during the day, uplifting music and videos will be prioritized.

[0798] Furthermore, the system optimizes communication with family members based on the user's emotional state. For example, when the user is relaxed, the server can send notifications at times that facilitate communication with family members.

[0799] A concrete example of a prompt message could be: "If an elderly user is feeling down during the day, generate suggestions for uplifting music or videos." This allows the system to provide content tailored to the user's needs.

[0800] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0801] Step 1:

[0802] The device collects the user's vital data and emotional data. Specifically, it uses heart rate and body temperature sensors to acquire the user's biometric data. It also records facial expressions and voice tone using a camera and microphone. This collected data becomes the input to the collection stage. The output is the detected vital data and emotional data.

[0803] Step 2:

[0804] The terminal performs the operation of sending the collected vital data and emotional data to the server. Specifically, it encrypts the data and sends it to the server via a secure communication protocol. The input for this step is the data obtained in step 1. The output is data that the server can use for analysis.

[0805] Step 3:

[0806] The server performs data analysis using a generated AI model based on the received data. Specifically, it analyzes emotional data with an emotion engine to identify the user's current emotional state. It also performs a health assessment of the user based on health indicators. The input for this step is vital data and emotional data transmitted from the terminal. The output is an assessment result regarding the user's health and emotional state.

[0807] Step 4:

[0808] The server uses the evaluation results to generate recommendations for the user. Specifically, it selects music and content to improve the environment for relaxation. Here, emotional state is the direct input data. The output is recommendations for the user.

[0809] Step 5:

[0810] The terminal provides the user with recommendations received from the server. Its primary actions include playing relaxing music on a music playback device or displaying visual content on a screen. The input for this step is the recommendations from the server. The output is the provision of visual or auditory stimuli to the user.

[0811] Step 6:

[0812] Users input their reactions and status regarding the provided content as feedback into their devices. Specifically, they input feedback through a dedicated application on their smartphone or tablet. This feedback is then used in subsequent data analysis. The input consists of the user's impressions and opinions, and the output is feedback data sent to the server.

[0813] (Application Example 2)

[0814] 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".

[0815] In modern society, improving the physical and mental health and quality of life of the elderly has become a social challenge. Consequently, there is a growing need for technologies that support stress management and smooth communication with family members. However, current technologies make it difficult to provide individualized, comprehensive support to the elderly. Furthermore, there is a lack of means to provide appropriate support based on their emotional state.

[0816] 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.

[0817] In this invention, the server includes a sensor device for collecting the user's biometric data, an emotion recognition device for recognizing emotional states from facial and vocal data, and an adjustment device for providing information to family members at the optimal timing according to the emotional state. This enables appropriate support and optimized communication based on the emotional state of elderly individuals.

[0818] "Biometric data" refers to physical data that indicates a user's health status, including information such as heart rate and body temperature.

[0819] A "sensor device" is a device used to detect and measure a user's biometric data, and includes wearable devices and cameras.

[0820] An "analysis device" is a processing device that analyzes collected biological data to determine health status and emotional state.

[0821] A "notification device" is a means of communicating analysis results and suggestions to the user or their family, and includes smartphones and other communication devices.

[0822] A "providing device" is a system or software that generates and provides entertainment content based on the user's preferences and circumstances.

[0823] A "communication device" is a means that enables voice calls and the sending and receiving of messages between a user and their family.

[0824] An "emotion recognition device" is software or hardware that has the function of analyzing a user's face and voice to determine their emotional state.

[0825] A "regulating device" is a means of adjusting the timing and content of information provided to family members based on the user's emotional state.

[0826] This invention is a system that comprehensively supports the user's health and emotional state. The system consists of a sensor device, an analysis device, a notification device, a provision device, a communication device, an emotion recognition device, and an adjustment device.

[0827] The sensor device plays a role in collecting the user's biometric data, measuring heart rate and body temperature using wearable devices, etc. This enables real-time collection of health data.

[0828] The server analyzes data collected using an analysis device with machine learning algorithms (e.g., TensorFlow or PyTorch). This allows it to determine the user's health and emotional state, and if an abnormality is detected, it generates appropriate content to help alleviate stress.

[0829] The notification device provides information to the user or their family based on the analysis results. For example, it may send notifications about health status and recommended actions via a smartphone app.

[0830] The device generates and delivers personalized entertainment based on the user's preferences and emotional state. It can play music using the Spotify API and select video content.

[0831] Furthermore, the communication device supports communication with family members based on the emotional state analyzed by the emotion recognition device. For example, if the user is feeling stressed, the family will be notified and prompted to make a call at an appropriate time.

[0832] For example, if a user's heart rate is detected as higher than normal, the server will suggest and notify them of relaxing music. This type of processing can be made possible by utilizing generative AI models to provide optimal solutions for each individual user.

[0833] An example of a prompt to a generative AI model is: "The user's heart rate is higher than normal. Please recommend relaxing music and a breathing instruction video."

[0834] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0835] Step 1:

[0836] Users collect biometric data (heart rate, body temperature, etc.) using sensors on smartwatches or smartphones. The input is biometric data, and the output is sent to the cloud.

[0837] Step 2:

[0838] The server processes biometric data received from the cloud using an analysis device. The input is biometric data acquired from the cloud, which is processed using machine learning algorithms to evaluate the user's health status. In this process, libraries such as TensorFlow are used to identify anomalies, and the evaluation results are output.

[0839] Step 3:

[0840] The emotion recognition device analyzes the user's face and voice using the device's camera and microphone. The input consists of camera images and audio data, which are processed by an emotion analysis algorithm. This determines the user's emotional state and outputs the result.

[0841] Step 4:

[0842] The server integrates analyzed health and emotional states to generate entertainment content tailored to the specific situation. The input consists of health and emotional state assessment results; a generative AI model is used to select and output appropriate music and video content.

[0843] Step 5:

[0844] The terminal uses a notification device to present recommended entertainment content to the user. The input is content information from a server, which is output to the user through the terminal screen and speaker.

[0845] Step 6:

[0846] The server uses a control device to manage the provision of information to family members based on their emotional state. The input is the user's emotional assessment result, and it sends notifications to family members in real time and outputs information in a way that facilitates calls as needed.

[0847] Step 7:

[0848] The generative AI model processes the prompt text and proposes the next action plan. The input is the prompt text, "The user's heart rate is higher than normal. Please recommend relaxing music and a breathing instruction video." Based on this, it generates and outputs the most suitable content suggestions.

[0849] 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.

[0850] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0851] 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.

[0852] 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.

[0853] 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.

[0854] 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.

[0855] 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.

[0856] 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.

[0857] 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."

[0858] 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.

[0859] 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.

[0860] 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.

[0861] 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.

[0862] 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.

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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.

[0867] 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.

[0868] 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.

[0869] 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.

[0870] The following is further disclosed regarding the embodiments described above.

[0871] (Claim 1)

[0872] A sensor means for collecting the user's vital data,

[0873] An analysis means for analyzing the above vital data and detecting abnormalities based on predetermined criteria,

[0874] A notification means for notifying the user based on the above analysis results,

[0875] A means of providing content based on user preferences,

[0876] A means of communication for communicating with family,

[0877] A system that includes this.

[0878] (Claim 2)

[0879] The system according to claim 1, wherein the analysis means predicts the user's health status using a machine learning algorithm.

[0880] (Claim 3)

[0881] The system according to claim 1, wherein the above-mentioned means generates optimized entertainment based on the user's past actions.

[0882] "Example 1"

[0883] (Claim 1)

[0884] A recording means for collecting user biometric data,

[0885] A diagnostic means that analyzes the above biological data and detects abnormalities based on predetermined criteria,

[0886] A means of contacting the user to issue a warning based on the above analysis results,

[0887] A means of providing information based on user preferences,

[0888] A means of connection for communicating with a person in a remote location,

[0889] A system that includes this.

[0890] (Claim 2)

[0891] The system according to claim 1, wherein the diagnostic means evaluates the user's health status using machine learning techniques.

[0892] (Claim 3)

[0893] The system according to claim 1, wherein the above-mentioned distribution means creates optimized entertainment based on the user's past behavior.

[0894] "Application Example 1"

[0895] (Claim 1)

[0896] A sensor means for collecting physiological data of the user,

[0897] An analytical means for analyzing the above physiological data and identifying abnormalities based on criteria,

[0898] A means of notifying users based on the above analysis results,

[0899] A means of providing information based on user preferences,

[0900] A means of communication for communicating with a person in a remote location,

[0901] A means of monitoring the user's health status in real time via an information processing device,

[0902] A means for optimizing digital information related to remote users,

[0903] A system that includes this.

[0904] (Claim 2)

[0905] The system according to claim 1, wherein the analysis means predicts the user's health status using a machine learning algorithm and generates an alert.

[0906] (Claim 3)

[0907] The system according to claim 1, wherein the above-mentioned means of provision utilizes a digital information distribution service to provide optimized entertainment based on the user's past preferences.

[0908] "Example 2 of combining an emotion engine"

[0909] (Claim 1)

[0910] A detection means for collecting the user's vital data and emotional data,

[0911] An analytical means for analyzing the above vital data and emotional data and evaluating the user's health and emotional state through a generated AI model,

[0912] Based on the above analysis results, recommended means of providing a relaxing environment for the user,

[0913] A means of generating and providing entertainment content based on the user's emotional state,

[0914] A communication method that optimizes communication with family members based on emotion recognition,

[0915] A system that includes this.

[0916] (Claim 2)

[0917] The system according to claim 1, wherein the analysis means uses an emotion engine to identify the user's emotions in real time and predict their health status.

[0918] (Claim 3)

[0919] The system according to claim 1, wherein the above-mentioned means optimizes music and videos according to the user's emotional data.

[0920] "Application example 2 when combining with an emotional engine"

[0921] (Claim 1)

[0922] A sensor device that collects the user's biometric data,

[0923] An analysis device that analyzes the above biological data and identifies abnormalities based on established criteria,

[0924] A notification device that provides information to the user based on the above analysis results,

[0925] A device that generates and provides entertainment based on user preferences,

[0926] A communication device for communicating with family,

[0927] An emotion recognition device that recognizes emotional states from facial expressions and voice,

[0928] A device that provides information to family members at the optimal timing according to their emotional state,

[0929] A system that includes this.

[0930] (Claim 2)

[0931] The system according to claim 1, wherein the analysis device predicts the user's health status using a machine learning algorithm.

[0932] (Claim 3)

[0933] The system according to claim 1, wherein the above-mentioned device generates optimized entertainment based on the user's past behavior. [Explanation of symbols]

[0934] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A sensor means for collecting the user's vital data, An analysis means for analyzing the above vital data and detecting abnormalities based on predetermined criteria, A notification means for notifying the user based on the above analysis results, A means of providing content based on user preferences, A means of communication for communicating with family, A system that includes this.

2. The system according to claim 1, wherein the analysis means predicts the user's health status using a machine learning algorithm.

3. The system according to claim 1, wherein the above-mentioned means generates optimized entertainment based on the user's past actions.

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