System

Abstract

A system is provided.SOLUTION: A system including means for managing profile data of a user, means for acquiring input data of the user and transmitting the input data to a server, means for the server to generate an appropriate response on the basis of the profile data and the input data of the user, means for providing the generated response to the user, means for acquiring health condition and activity information of the user by using a sensor and transmitting the acquired health condition and activity information to the server, means for the server to analyze the acquired health condition and activity information and detect an abnormality, and means for notifying the user and an emergency contact when the abnormality is detected.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In "elderly care," where elderly people provide care to each other, there is a risk of both falling and getting injured, or collapsing at the same time. Furthermore, as they become devoted to caring for each other, it becomes difficult for them to go out, leading to social isolation. This increases the mental burden and reduces the quality of life. Furthermore, if an emergency occurs, they may not be able to respond quickly, which could lead to serious consequences. Therefore, there is a need for a system that can reduce the sense of isolation and quickly respond to emergency situations so that elderly people can live safely and with peace of mind. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including: means for managing user profile data; means for acquiring and transmitting user input data to a server; means for the server to generate an appropriate response based on the user profile data and input data; means for providing the generated response to the user; means for acquiring and transmitting health and activity information of the user using sensors to the server; means for the server to analyze the acquired health and activity information and detect abnormalities; means for notifying the user and emergency contacts when an abnormality is detected; means for generating and providing activity guidance based on the user's interests; and means for analyzing data acquired from the sensors on the cloud. This system reduces the sense of isolation felt by elderly people and enables rapid response to abnormal situations.

[0006] "User profile data" refers to information about an individual user, including attributes and status information such as age, gender, health status, hobbies, and activity history.

[0007] "Input Data" means information entered by a user through the system, including communications, questions, requests, etc., including text and voice.

[0008] A "server" is a part of a computer system that stores, processes, and manages data over a network, and is responsible for providing the necessary information in response to requests from clients.

[0009] A "means for generating a response" refers to an algorithm or process that analyzes received input data and automatically generates an appropriate reply, instruction, information, etc.

[0010] A "sensor" is a device that detects the user's physical condition and information about the surrounding environment in real time and acquires it as data, and includes heart rate monitors, pedometers, thermometers, etc.

[0011] "Anomaly detection methods" refers to the process of identifying and identifying abnormal patterns or emergency situations through data analysis algorithms and comparison with defined normal ranges.

[0012] "Means of notification" refers to the means of communication used to inform users and emergency contacts that an abnormality has occurred, and includes methods such as telephone, SMS, and email.

[0013] "Activity Guide" refers to information such as events, activities, and online courses suggested to you based on your interests and hobbies, and which promotes your social participation and interaction.

[0014] "Means of analyzing on the cloud" refers to the process of sending data to a remote server provided via the Internet and performing data analysis there using advanced computing resources. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

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

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

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

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

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

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

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

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] This invention is an "anti-isolation AI" system that manages user profile data and input data and supports the safety and communication of elderly people. The system provides a series of functions, including data acquisition using sensors, dialogue support by AI agents, anomaly detection and notification, and activity guidance.

[0037] System configuration

[0038] 1. User profile data management (server)

[0039] The server manages profile data such as basic user information (age, gender, hobbies, health status) and past activity history.

[0040] 2. Data entry and transmission (terminal, user)

[0041] The user inputs text or voice through the device, which then sends it to the server. For example, if the user inputs "What's the weather like today?", this message is sent to the server.

[0042] 3. Generating and Providing Responses (Server, Terminal)

[0043] The server analyzes the received input data and generates an appropriate response to the user's question. The generated response is provided to the user through the terminal. For example, the server generates a response such as "Today's weather is sunny," and the terminal displays it to the user.

[0044] 4. Data acquisition by sensors (terminal)

[0045] The device uses built-in sensors to obtain real-time information about the user's health status (heart rate, steps, body temperature), and periodically transmits this data to a server.

[0046] 5. Anomaly detection and notification (server)

[0047] The server analyzes the health data sent and detects any abnormalities. For example, if the heart rate is outside the normal range, the server determines this to be an abnormality and sends a notification to the user and emergency contacts.

[0048] 6. Providing activity information (server, terminal)

[0049] The server suggests appropriate activities and events based on the user's profile data and interests, thereby facilitating social participation and interaction.

[0050] A natural language description of the program's operation

[0051] 1. Managing User Data

[0052] The server manages the user's profile data and records any updates made to it, for example, if a user takes up a new hobby, "gardening," the server records this.

[0053] 2. Sending input data and generating a response

[0054] The device sends the data entered by the user to the server, which analyzes it and generates a response. For example, if the user asks, "What's the weather like today?", the server responds, "It's sunny today," and sends it to the device.

[0055] 3. Sensor data acquisition and anomaly detection

[0056] The device monitors the user's health status and sends it to a server. The server analyzes the received data and notifies the user if an abnormality is detected. For example, if the user's heart rate is abnormally high, the server notifies an emergency contact.

[0057] 4. Providing information about activities

[0058] The server generates activity recommendations based on the user's interests and profile, for example, telling the user, "There's a gardening workshop being held at a nearby park."

[0059] The system of the present invention reduces the sense of isolation felt by elderly people and enables them to respond quickly to abnormal situations, allowing them to live with peace of mind.

[0060] The processing flow will be explained below.

[0061] Step 1:

[0062] The device starts up and displays a screen for the user to log in. The user enters their username and password on the login screen and taps the login button.

[0063] Step 2:

[0064] The device sends the login information to the server. The server verifies the received login information, and if authentication is successful, it sends the home screen data. The device then displays the home screen.

[0065] Step 3:

[0066] The user selects the "Chat" icon on the home screen to begin a conversation with the AI ​​agent, and then types "What's the weather like today?" into the input field.

[0067] Step 4:

[0068] The device receives the text data entered by the user and sends it to the server. The server analyzes the received input data and generates a response such as "Today's weather is sunny." The server then sends the generated response data to the device.

[0069] Step 5:

[0070] The device displays the received response data to the user, who sees the message "Today's weather is sunny."

[0071] Step 6:

[0072] The device uses built-in sensors to collect real-time data on the user's health, including heart rate, steps taken, and body temperature, and this data is periodically sent to a server.

[0073] Step 7:

[0074] The server analyzes the received health data and detects abnormal patterns or emergencies. For example, if the heart rate is outside the normal range, the server will detect an abnormality.

[0075] Step 8:

[0076] If the server detects an abnormality, it will notify the user and designated emergency contacts, who will be informed via email and SMS.

[0077] Step 9:

[0078] The user selects the "Activity Guide" icon and receives suggestions for categories and events that interest them. The server references the user's profile data and generates appropriate activity guides.

[0079] Step 10:

[0080] The server sends the generated activity guide to the terminal, which then displays the received activity guide to the user, encouraging them to participate in specific events or online courses.

[0081] Example 1

[0082] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0083] Communication support and health monitoring in daily life are important for reducing feelings of isolation and improving safety for the elderly. However, existing systems lack sufficient activity guidance based on the user's interests or prompt notification when an abnormality is detected, and an improved user experience is required. In addition, there is a lack of technology to generate more appropriate responses through voice input text conversion and natural language processing using generative AI models. A new system that solves these issues is needed.

[0084] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0085] In this invention, the server includes: means for managing user profile data; means for acquiring and transmitting user input data to the server; means for the server to generate an appropriate response based on the user profile data and input data; means for providing the generated response to the user; means for acquiring the user's health status and activity information using a sensor and transmitting it to the server; means for the server to analyze the acquired health status and activity information and detect abnormalities; means for notifying the user and emergency contacts when an abnormality is detected; means for a generative AI model with natural language processing capabilities to generate the generated response; and means for converting the user's input data from voice to text. This improves the safety and communication of elderly people. It also enables activity guidance based on the user's interests and rapid response when an abnormality is detected.

[0086] "User profile data" refers to data that includes basic information about the user (age, gender, hobbies, health status) and past activity history.

[0087] "Input data" refers to text and voice data that a user inputs through a terminal.

[0088] A "server" is a computer system that analyzes user profile data and input data and generates an appropriate response.

[0089] A "generative AI model" refers to an algorithm or machine learning model that has natural language processing capabilities and generates appropriate responses based on input data.

[0090] A "sensor" is a device that acquires a user's health status (heart rate, body temperature, number of steps, etc.) and activity information in real time.

[0091] "Abnormality detection" refers to the server analyzing acquired health status and activity information and determining abnormal conditions that exceed the normal range.

[0092] "Notification" refers to the act of sending an alert to the user and emergency contacts when an abnormality is detected.

[0093] "Activity Guides" are suggested activities and events based on a user's profile data and interests.

[0094] "Speech to text conversion" refers to the process of converting voice input data into text data.

[0095] "Natural language processing" refers to the technology that enables computers to understand and generate human language.

[0096] MODE FOR CARRYING OUT THE INVENTION

[0097] This invention is an "anti-isolation AI" system that supports the safety and communication of elderly people. The system manages user profile data and input data, and provides a series of functions such as health monitoring using sensors, dialogue support using generative AI models, anomaly detection and notification, and activity guidance.

[0098] The system configuration uses the following hardware and software:

[0099] User data management (server)

[0100] The server manages profile data such as basic user information (age, gender, hobbies, health status) and past activity history. This data is stored and managed appropriately using a database management system (DBMS), and any updates are recorded as appropriate.

[0101] Specific examples

[0102] If a user becomes interested in "gardening" as a new hobby, the server records this information in the database.

[0103] Data entry and transmission (terminal, user)

[0104] The user inputs a message through the device using text or voice. The input data is sent from the device to the server. If voice input is performed, the device converts this voice into text.

[0105] Specific examples

[0106] When a user asks "What's the weather like today?", the device converts this into text and sends it to the server.

[0107] Prompt Sentence Examples

[0108] Parse the text asking about today's weather and generate an appropriate response.

[0109] Response generation and delivery (server, terminal)

[0110] The server analyzes the data received from the user using the generative AI model and generates an appropriate response, which is then provided to the user via their device.

[0111] Specific examples

[0112] When a user asks, "What's the weather like today?", the generative AI model is used to analyze the question and generate a response such as "The weather is sunny today," which the device then notifies the user.

[0113] Sensor data acquisition (terminal)

[0114] The device uses built-in sensors to obtain real-time information about the user's health status (heart rate, body temperature, number of steps) and periodically transmits this data to a server.

[0115] Specific examples

[0116] The device measures the number of heartbeats per minute and sends this data to a server.

[0117] Anomaly detection and notification (server)

[0118] The server analyzes the health data and detects any abnormalities. If an abnormality is detected, a notification is sent to the user and their emergency contacts.

[0119] Specific examples

[0120] The server detects an abnormal heart rate and sends a notification to the user and emergency contacts saying, "Your heart rate is too high."

[0121] Providing activity information (server, terminal)

[0122] The server suggests appropriate activities and events based on the user's profile data and interests, thereby facilitating social participation and interaction.

[0123] Specific examples

[0124] Based on the user's profile data, the server recommends, "There's a gardening workshop being held in a nearby park."

[0125] The system of the present invention reduces the sense of isolation felt by the elderly, providing them with peace of mind and companionship in their daily lives. It also provides a safe environment by enabling rapid response to emergency situations.

[0126] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0127] Program processing flow

[0128] Step 1: Managing User Profile Data (Server)

[0129] The server stores profile data such as basic user information (age, gender, hobbies, health status) and past activity history in a database. When a user registers or updates their profile data, it manages this data and records the changes.

[0130] input

[0131] User basic information (age, gender, hobbies, health condition)

[0132] process

[0133] The server uses a database management system (DBMS) to properly store and manage user information.

[0134] output

[0135] A database with updated user profile data

[0136] Specific actions

[0137] The server receives the new user's registration information and stores it in a database.

[0138] When a user adds a new hobby (e.g. gardening), the server records this change in the database.

[0139] Step 2: Data entry and transmission (terminal, user)

[0140] The user inputs text or voice through the device, which processes the input data and sends it to the server. If voice input is used, the device converts the voice into text.

[0141] input

[0142] User voice or text input

[0143] process

[0144] The device converts the voice input into text and sends this data to the server.

[0145] output

[0146] Textual input data sent to the server

[0147] Specific actions

[0148] The user speaks, "What's the weather like today?"

[0149] The device converts the voice into text and sends the text data "What's the weather like today?" to the server.

[0150] Step 3: Generate and serve a response (server, terminal)

[0151] The server analyzes the data received from the user using the generative AI model and generates an appropriate response, which is then provided to the user via their device.

[0152] input

[0153] Text input data sent by the user

[0154] process

[0155] The server uses a generative AI model to analyze the input data and generate an appropriate response.

[0156] output

[0157] Generated response text

[0158] Specific actions

[0159] The server parses the question "What's the weather today?" and generates the response "The weather is sunny today."

[0160] The device displays or plays this response to the user.

[0161] Step 4: Acquiring sensor data (device)

[0162] The device uses built-in sensors to obtain the user's health status (heart rate, body temperature, number of steps) in real time and periodically transmits this data to a server.

[0163] input

[0164] Health status data acquisition using sensors

[0165] process

[0166] The health data collected by the device is periodically sent to a server.

[0167] output

[0168] Health status data sent to the server

[0169] Specific actions

[0170] The device measures the user's heart rate every minute and sends this data to a server.

[0171] Step 5: Anomaly detection and notification (server)

[0172] The server analyzes the health data and detects any abnormalities. If an abnormality is detected, a notification is sent to the user and their emergency contacts.

[0173] input

[0174] Health data sent from the device

[0175] process

[0176] The server analyzes health data and detects abnormalities that exceed the normal range.

[0177] output

[0178] Anomaly detection notification message

[0179] Specific actions

[0180] The server detects abnormal heart rate and sends a notification to the user and emergency contacts saying, "Your heart rate is too high."

[0181] Step 6: Providing activity information (server, terminal)

[0182] The server suggests appropriate activities and events based on the user's profile data and interests, thereby facilitating social participation and interaction.

[0183] input

[0184] User profile data and interest data stored on the server

[0185] process

[0186] The server searches for and generates appropriate activities and events based on the user's interests.

[0187] output

[0188] Proposed activities and event information

[0189] Specific actions

[0190] Based on the user's interest data, the server recommends, "There's a gardening workshop being held in a nearby park."

[0191] The device will notify the user of this information.

[0192] Through the above processing steps, the system of the present invention improves safety and communication for the elderly. It also enables activity guidance based on the user's interests and quick response when an abnormality is detected.

[0193] (Application example 1)

[0194] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0195] The problems of elderly isolation and lack of health monitoring are serious issues. Elderly operators working in factories and other facilities require real-time monitoring of their health status while ensuring work safety and efficiency, but current systems are unable to adequately address this. Therefore, a system is needed that effectively supports the safety and communication of elderly operators and enables rapid response in the event of an emergency.

[0196] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0197] In this invention, the server includes: means for managing user profile data; means for acquiring and transmitting user input data to the server; means for the server to generate an appropriate response based on the user profile data and input data; means for providing the generated response to the user; means for acquiring the user's health condition and activity information using a sensor and transmitting it to the server; means for the server to analyze the acquired health condition and activity information and detect abnormalities; means for notifying the user and emergency contacts when an abnormality is detected; and dialogue support means using an industrial robot equipped with an AI agent to support elderly operators in factories. This enables real-time monitoring of the health condition of elderly operators and rapid response to abnormalities while ensuring their safety and work efficiency.

[0198] "User profile data" refers to the user's basic information (age, gender, hobbies, health status) and past activity history.

[0199] "Input Data" refers to information such as messages or questions entered by the user via text or voice.

[0200] "Server" refers to a computer system for processing user profile data and input data and generating an appropriate response.

[0201] "Generated response" refers to an answer or guidance generated by the server based on user input data.

[0202] "Sensor" refers to a device that acquires a user's health status (heart rate, body temperature, number of steps, etc.) and activity information in real time.

[0203] "Analysis" refers to the process of analyzing information based on acquired data and detecting anomalies and patterns.

[0204] "Anomaly detection" refers to detecting values ​​or trends that exceed the normal range through analysis results.

[0205] "Emergency contacts" refers to contact information for the user's family, medical institutions, etc. who will be notified when an abnormality is detected.

[0206] An "AI agent" refers to software that uses artificial intelligence to interact with users and provide appropriate responses and guidance.

[0207] An "industrial robot" refers to an automated mechanical device used in production sites such as factories.

[0208] "Dialogue support" refers to supporting communication between elderly operators and industrial robots.

[0209] "Activity Guide" refers to suggested activities and events based on a user's interests and profile.

[0210] "Cloud" refers to computing resources provided over the Internet.

[0211] "Real-time" refers to the immediacy and processing and provision of information with almost no delay.

[0212] The present invention relates to an "elderly operator support system" that ensures the safety and work efficiency of elderly operators while enabling real-time monitoring of their health status and prompt response in the event of an abnormality. Specific embodiments are described below.

[0213] System configuration

[0214] 1. User profile data management (server)

[0215] The server manages profile data such as basic information (age, gender, hobbies, health status) of the elderly operator users and their past work history. For example, if a new task or skill is added, the server updates and records it.

[0216] 2. Data entry and transmission (terminal, user)

[0217] The user inputs different types of data (text and voice) through a tablet or voice input device and sends this to the server, for example, asking "What do I do next?"

[0218] 3. Generating and Providing Responses (Server, Terminal)

[0219] The server analyzes the received input data and generates an appropriate response to the user's question. The generated response is provided to the user via a tablet or voice device. For example, the server generates a response such as "Next, we will inspect the part" and displays it on the terminal.

[0220] 4. Data acquisition by sensors (terminal)

[0221] The terminal uses sensors built into the wearable device to obtain real-time information on the elderly operator's health, such as heart rate, body temperature, and number of steps taken, and this data is periodically sent to a server.

[0222] 5. Anomaly detection and notification (server)

[0223] The server analyzes the health data and detects any abnormalities. For example, if the heart rate exceeds the normal range, the server determines this to be an abnormality and sends a notification to the factory manager and emergency contact.

[0224] 6. Providing activity information (server, terminal)

[0225] The server suggests the next task and efficient work methods based on the elderly operator's profile data and past work history, thereby improving the user's work efficiency.

[0226] A natural language description of the program's operation

[0227] 1. Managing User Data

[0228] The server manages basic information and past work history of elderly operators and records any updates. For example, if a new skill is added, the server adds it to the profile data.

[0229] 2. Sending input data and generating a response

[0230] The terminal sends the data entered by the user to the server, which analyzes it and generates an appropriate response. For example, if the user asks, "What's next?", the server generates the response, "Next is to inspect the part," and sends it to the terminal.

[0231] 3. Sensor data acquisition and anomaly detection

[0232] The device monitors the health status of the elderly operator and sends the information to a server. The server analyzes the received data and notifies the factory manager and emergency contacts if an abnormality is detected. For example, if the user's heart rate is abnormally high, the server notifies the factory manager and emergency contacts.

[0233] 4. Providing information about activities

[0234] The server generates activity guides based on the interests and profile of the elderly operator, for example, providing the user with a guide such as, "Next is a parts inspection, followed by machine maintenance."

[0235] Specific Examples

[0236] Examples:

[0237] If an elderly operator working at a precision manufacturing factory experiences an abnormally high temperature while inspecting a product, the factory manager and emergency contacts will be automatically notified. The operator can also ask the AI ​​assistant, "What should I do next?" to confirm the next steps.

[0238] Example prompts to input to a generative AI model:

[0239] "If an elderly operator working in a manufacturing plant feels unwell during the night shift, write a program on how an AI assistant can assist in this situation and notify the manager."

[0240] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0241] Step 1:

[0242] A user inputs profile data into a terminal. For example, basic information such as age, gender, hobbies, and health status is input. This input data is stored in a database and sent to a server. The input data is processed to generate profile data, which is then registered on the server.

[0243] Step 2:

[0244] The user enters a question or command through the device, for example, "What do I do next?" using text or voice input. The device sends this to the server, which processes the input data, analysing the text or voice data and converting it into an appropriate format.

[0245] Step 3:

[0246] The server analyzes the received input data and generates an appropriate response. This analysis is performed using a generative AI model that includes natural language processing. For example, in response to the input query "What task will be performed next?", a response such as "Next is the inspection of the parts" is generated. Data analysis organizes the information and generates response data.

[0247] Step 4:

[0248] The generated response data is sent from the server to the terminal and provided to the user. For example, a text response is displayed on the tablet screen or read aloud. An output based on the server's response data is generated and displayed on the terminal.

[0249] Step 5:

[0250] The terminal uses sensors built into the wearable device to acquire the user's health data (heart rate, body temperature, number of steps, etc.) in real time. The acquired data is periodically sent to a server. The real-time health data is generated and transmitted based on the data acquired by the sensors.

[0251] Step 6:

[0252] The server analyzes the acquired health data and detects any abnormalities. For example, if the heart rate is outside the normal range, the server determines this as an abnormality. Anomaly detection based on data analysis determines whether or not there is an abnormality.

[0253] Step 7:

[0254] If an abnormality is detected, the server sends a notification to the user and emergency contacts. For example, if the heart rate is abnormally high, the server notifies the factory manager and emergency contacts. The notification function enables a prompt response when an abnormality is detected.

[0255] Step 8:

[0256] The server suggests the next task and the most efficient way to work based on the user's profile data and past work history. For example, it provides the user with guidance such as, "Next is the parts inspection, followed by machine maintenance." Data analysis and suggestion functions aim to improve work efficiency.

[0257] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0258] This invention combines an emotion engine with an "anti-isolation AI" system that supports the safety and communication of elderly people. The system provides functions such as data acquisition using sensors, dialogue support by an AI agent, anomaly detection and notification, activity guidance, and an emotion engine that recognizes user emotions.

[0259] System configuration

[0260] 1. User profile data management (server)

[0261] The server manages profile data such as basic user information (age, gender, hobbies, health status) and past activity history.

[0262] 2. Data entry and transmission (terminal, user)

[0263] The user inputs text or voice through the device, which then sends it to the server. For example, if the user inputs "What's the weather like today?", this message is sent to the server.

[0264] 3. Generating and Providing Responses (Server, Terminal)

[0265] The server analyzes the received input data and generates an appropriate response to the user's question. The generated response is provided to the user through the terminal. For example, the server generates a response such as "Today's weather is sunny," and the terminal displays it to the user.

[0266] 4. Data acquisition by sensors (terminal)

[0267] The device uses built-in sensors to collect real-time data on the user's health, including heart rate, steps taken, and body temperature, and this data is periodically sent to a server.

[0268] 5. Anomaly detection and notification (server)

[0269] The server analyzes the health data and detects abnormal patterns or emergencies. For example, if the heart rate is outside the normal range, the server will detect the abnormality. When the server detects an abnormality, it will send a notification to the user and their designated emergency contacts.

[0270] 6. Emotion Recognition by Emotion Engine (Server)

[0271] The server uses an emotion engine to recognize the user's emotions based on the user's input data and data acquired from the sensors. For example, the emotion engine analyzes the user's voice and text and detects "stress."

[0272] 7. Emotion-based response modification (server, terminal)

[0273] The server then modifies the response it generates based on the user's emotions as recognized by the emotion engine. For example, if the server detects that the user is under stress, it generates a response such as, "Why don't you try listening to some relaxing music?"

[0274] 8. Use in Emotion Data Analysis (Server)

[0275] The server also uses the emotion data recognized by the emotion engine as part of its analysis of health status and activity information. This data is also reflected in the anomaly detection process, enabling more accurate anomaly detection.

[0276] 9. Emotion-based activity guidance (server, terminal)

[0277] The server generates appropriate activity recommendations for the user based on the user's emotional data recognized by the emotion engine. For example, if the user is recognized as "depressed," the server will suggest that the user participate in relaxation activities or hobbies.

[0278] A natural language description of the program's operation

[0279] 1. Managing User Data

[0280] The server manages the user's profile data and records any updates made to it, for example, if a user takes up a new hobby, "gardening," the server records this.

[0281] 2. Sending input data and generating a response

[0282] The device sends the data entered by the user to the server, which analyzes it and generates a response. For example, if the user asks, "What's the weather like today?", the server responds, "It's sunny today," and sends it to the device.

[0283] 3. Sensor data acquisition and anomaly detection

[0284] The device monitors the user's health status and sends it to a server. The server analyzes the received data and notifies the user if an abnormality is detected. For example, if the user's heart rate is abnormally high, the server notifies an emergency contact.

[0285] 4. Emotional Data Recognition and Response Modification

[0286] The server analyzes the user's input data and sensor data using an emotion engine to recognize the user's emotions. For example, if the user is under stress, the server will modify the response and provide it via the device, suggesting, "Why not try listening to some relaxing music?"

[0287] 5. Use in Emotion Data Analysis

[0288] The server uses the emotional data recognized by the emotion engine to analyze the user's health status and reflects this in the anomaly detection process. For example, if a user is depressed over a long period of time, it can take action such as suggesting early consultation with a doctor or counselor.

[0289] 6. Emotion-based activity guidance

[0290] The server generates appropriate activity recommendations based on the user's emotional state. For example, a "depressed" user might be provided with relaxation activities to encourage social interaction.

[0291] By incorporating an emotion engine, the system of the present invention can flexibly respond to the user's emotional state, reduce the elderly's sense of isolation, and provide support for them to live with peace of mind.

[0292] The processing flow will be explained below.

[0293] Step 1:

[0294] The device starts up and displays a screen for the user to log in. The user enters their username and password on the login screen and taps the login button.

[0295] Step 2:

[0296] The device sends the login information to the server. The server verifies the received login information, and if authentication is successful, it sends the home screen data. The device then displays the home screen.

[0297] Step 3:

[0298] The user selects the "Chat" icon on the home screen to begin a conversation with the AI ​​agent, and then types "What's the weather like today?" into the input field.

[0299] Step 4:

[0300] The device receives the text data entered by the user and sends it to the server. The server analyzes the received input data and generates a response such as "Today's weather is sunny." The server then sends the generated response data to the device.

[0301] Step 5:

[0302] The device displays the received response data to the user, who sees the message "Today's weather is sunny."

[0303] Step 6:

[0304] The device uses built-in sensors to collect real-time data on the user's health, including heart rate, steps taken, and body temperature, and this data is periodically sent to a server.

[0305] Step 7:

[0306] The server analyzes the received health data and detects abnormal patterns or emergencies. For example, if the heart rate is outside the normal range, the server will detect an abnormality.

[0307] Step 8:

[0308] If the server detects an abnormality, it will notify the user and designated emergency contacts, who will be informed via email and SMS.

[0309] Step 9:

[0310] The server uses an emotion engine to analyze user input data and sensor data to recognize the user's emotions. For example, it can detect "anxiety" from the text and voice input of the user.

[0311] Step 10:

[0312] The server then modifies the response appropriately based on the user's emotions as determined by the emotion engine. For example, if the server determines that the user is feeling anxious, it generates a response suggesting, "Why not try listening to some relaxing music?"

[0313] Step 11:

[0314] The device displays the modified response to the user, who sees the message, "Why not try listening to some relaxing music?"

[0315] Step 12:

[0316] The server also uses the emotional data recognized by the emotion engine to analyze health status and activity information. For example, if a user has been feeling depressed for a long period of time, that data will be reflected in the analysis.

[0317] Step 13:

[0318] The server generates appropriate activity guides based on the emotion data recognized by the emotion engine, suggesting activities, events, relaxation methods, etc. according to the user's emotional state.

[0319] Step 14:

[0320] The device displays the generated activity guide to the user. For example, if the user is feeling "down," the device provides a guide such as "Why don't you join a gardening event at a nearby park?"

[0321] Example 2

[0322] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0323] There is a need to reduce the sense of isolation felt by the elderly and provide an environment where they can live safely while maintaining social connections. In particular, there is a lack of systems that can monitor their health and emotional state in real time and provide appropriate responses accordingly. Furthermore, there is a challenge in providing more accurate anomaly detection and activity guidance that takes emotional state into account.

[0324] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for managing user profile data, means for acquiring and analyzing user input data and generating an appropriate response, means for acquiring the user's health condition and activity information and detecting abnormalities, means for recognizing emotions based on the user input data and data acquired from the sensor, means for modifying responses based on the recognized emotions, means for analyzing the emotion data and reflecting it in the anomaly detection process, and means for generating appropriate activity guidance based on the emotion data and providing it to the user. This makes it possible to comprehensively monitor the health condition and emotional state and provide appropriate responses and guidance, allowing elderly people to live with peace of mind and reducing their sense of isolation.

[0325] "User Profile Data" refers to basic information such as age, gender, hobbies, health status, and past activity history.

[0326] "Server" refers to a computer system that processes data received from users, manages profile data, generates responses, detects anomalies, etc.

[0327] "Terminal" refers to a device that allows a user to manipulate input data and obtain health and activity information through sensors.

[0328] "Input data" refers to text and voice data provided by the user through the terminal.

[0329] "Generated response" refers to a reply or suggestion to the user that the server generates by analyzing the input data.

[0330] "Sensors" refer to devices that measure a user's health status, such as heart rate, steps, and body temperature, in real time.

[0331] "Health status and activity information" refers to data on the user's physical condition and behavior obtained through sensors.

[0332] "Anomaly detection" refers to the process by which the server analyzes health and activity information to discover unusual patterns or emergencies.

[0333] "Emotion engine" refers to an algorithm or program that analyzes user input data and sensor data to recognize emotions.

[0334] "Emotional Data" refers to information about a user's emotional state as recognized by the Emotion Engine.

[0335] "Activity guidance" refers to information about suggested activities based on a user's interests and emotional state.

[0336] "Emergency Contact" means a person or entity designated to receive notification when an anomaly is detected.

[0337] MODE FOR CARRYING OUT THE INVENTION

[0338] This invention is a system for supporting the safety and communication of the elderly, and it manages and analyzes user profile data, health data, and emotion data in an integrated manner. This system includes a server, terminals, sensors, emotion engine, etc., which work together to support the lives of the elderly.

[0339] System configuration

[0340] The system includes the following main components:

[0341] 1. Server

[0342] Profile data management: Store user basic information (age, gender, hobbies, health status, and past activity history) in a database and update it as needed.

[0343] Response generation: Based on the input data received from the user, a generative AI model is used to generate an appropriate response.

[0344] Anomaly detection: Analyzes health status and activity information sent from sensors to detect abnormalities.

[0345] Emotion Recognition: Recognize emotions from user input data and sensor data using an emotion engine.

[0346] Response Modification: Modify the response based on the recognized emotion data and provide it to the user.

[0347] 2. Terminal

[0348] Data Entry: Allows users to enter text or voice data, which is then sent to the server.

[0349] Sensor data acquisition: The built-in sensors are used to acquire the user's health data, such as heart rate, steps, and body temperature, in real time and send it to the server.

[0350] 3. Sensors

[0351] Health monitoring: Measures the user's heart rate, steps, temperature, etc.

[0352] 4. Emotion Engine

[0353] Sentiment analysis: Recognizing user emotions based on their voice, text, and health data.

[0354] System operation example

[0355] A concrete example of the system in action is as follows:

[0356] 1. Entering and submitting user data

[0357] User: For example, type "What's the weather like today?" into the device.

[0358] Terminal: Sends the entered data to the server.

[0359] 2. Generating and Displaying the Response

[0360] Server: Analyzes the input data using a generative AI model and generates a response such as "Today's weather is sunny."

[0361] Terminal: Displays the generated response to the user.

[0362] 3. Health data acquisition and anomaly detection

[0363] Sensor: Monitors the user's heart rate and sends the data to the server via the device.

[0364] Server: Analyzes the transmitted data and sends a notification to emergency contacts if the heart rate is abnormally high.

[0365] 4. Emotional Data Recognition and Response Modification

[0366] Server: Using the emotion engine, recognize emotions from user input data and sensor data. For example, if the input text is "tired," it detects "stress."

[0367] Server: Based on the recognized emotion, the server modifies the response to "Why not try listening to some relaxing music?" and provides it through the device.

[0368] Prompt Sentence Examples

[0369] Here are some example prompts to input to the generative AI model:

[0370] Answering questions

[0371] Prompt text: "The user types 'What's the weather today?' How should the server respond?"

[0372] Example response generated: "The weather is sunny today."

[0373] Emotion Recognition and Response Modification

[0374] Prompt: "By analyzing the user's text or voice data, how can the server recognize the user's emotions and generate a response based on them?"

[0375] Example generated response: "We've detected stress in your voice. Would you like to try listening to some relaxing music?"

[0376] This system can comprehensively monitor the user's health and emotional state, and generate appropriate responses and activity guidance based on that information, thereby providing support that allows elderly people to live with peace of mind.

[0377] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0378] Step 1:

[0379] Managing your profile data

[0380] Input: Basic information entered by the user when registering (age, gender, hobbies, health status, and past activity history)

[0381] What it does: The server receives input data from the user, stores it in a database, and updates existing data when the user provides new information.

[0382] Data Processing: The server merges the new information with the existing profile data to maintain consistency.

[0383] Output: Updated profile data is saved to the database.

[0384] Step 2:

[0385] Entering and Submitting Data

[0386] Input: The user uses the device to input text or voice data.

[0387] What happens: The user types a question, such as "What's the weather like today?"

[0388] Data processing: The device converts the text or voice data into a digital format and sends it to the server.

[0389] Output: The transformed input data is sent to the server.

[0390] Step 3:

[0391] Generating and serving the response

[0392] Input: User input data received by the server

[0393] Specific operation: The server uses a generative AI model to analyze the input data.

[0394] Data processing: Analyzes input data and generates appropriate responses.

[0395] Output: The generated response is sent to the terminal and displayed to the user. Example: "The weather is sunny today."

[0396] Step 4:

[0397] Acquiring Sensor Data

[0398] Input: Real-time data such as user heart rate, steps, and body temperature

[0399] How it works: Sensors built into the device measure these data.

[0400] Data processing: The acquired data is periodically sent to the server.

[0401] Output: The data acquired by the sensor is sent to the server.

[0402] Step 5:

[0403] Anomaly detection and notification

[0404] Input: Sensor data received by the server

[0405] Specific operation: The server analyzes the sensor data and detects abnormalities, such as when the heart rate exceeds the normal range.

[0406] Data processing: Analyze the data using anomaly detection algorithms.

[0407] Output: If an anomaly is detected, a notification is sent to the user and emergency contacts.

[0408] Step 6:

[0409] Emotion recognition by emotion engine

[0410] Input: User input and sensor data

[0411] Specific operation: The server uses an emotion engine to analyze this data and recognize the user's emotions.

[0412] Data processing: The emotion engine identifies the user's emotional state as a result of the analysis.

[0413] Output: Recognized emotion data is generated. Example: "I feel stressed."

[0414] Step 7:

[0415] Emotion-Based Response Modification

[0416] Input: Emotion data generated by the emotion engine

[0417] Specific behavior: The server modifies the generated response based on the emotion data.

[0418] Data processing: Regenerate the response content and modify it to correspond to the emotion.

[0419] Output: The modified response is sent to the terminal and provided to the user. Example: "Why not try listening to some relaxing music?"

[0420] Step 8:

[0421] Use in analyzing emotion data

[0422] Input: Emotion data recognized by the emotion engine

[0423] Specific operation: The server also reflects the emotion data in the anomaly detection process.

[0424] Data processing: Integrating emotion data into health analysis parameters.

[0425] Output: Consolidated analytical data is generated.

[0426] Step 9:

[0427] Emotion-based activity guidance

[0428] Input: Emotion data recognized by the emotion engine

[0429] Specific operation: The server generates appropriate activity guidance for the user based on the emotion data.

[0430] Data processing: Generate activities that match the emotional state.

[0431] Output: The generated activity guide is sent to the terminal and provided to the user. Example: "Try participating in a relaxation activity."

[0432] Through these processing steps, the system monitors the health and emotional state of elderly people in real time, and provides appropriate responses and activity guidance based on that information, thereby supporting an environment in which they can live with peace of mind.

[0433] (Application example 2)

[0434] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0435] While safety and health management for elderly people and factory workers is important, existing systems do not adequately monitor their health and emotional states in real time. Furthermore, there is a lack of systems that can quickly detect abnormalities and take appropriate action. Therefore, there is a need for a system that can respond promptly when an abnormality occurs.

[0436] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for managing user profile data; means for acquiring and transmitting user input data to the server; means for the server to generate an appropriate response based on the user profile data and input data; means for providing the generated response to the user; means for acquiring and transmitting user health and activity information using a sensor; means for the server to analyze the acquired health and activity information and detect abnormalities; means for notifying the user and emergency contacts when an abnormality is detected; means for recognizing the user's emotional state using an emotion engine; means for appropriately modifying the generated response based on the emotional state; means for generating and providing activity guidance based on the emotional state; means for monitoring the health and emotional states of factory workers in real time; and means for notifying workers and managers when an abnormality is detected. This makes it possible to monitor the health and emotional states of elderly people and factory workers in real time, quickly detect abnormalities, and take appropriate action.

[0437] "User profile data" refers to information such as the user's age, gender, hobbies, health status, and past activity history.

[0438] "Input Data" means information entered by a User through text or voice that is transmitted to the Server.

[0439] "Server" means a central computer that analyzes user input and profile data and generates and provides appropriate responses.

[0440] A "sensor" is a device that acquires a user's health status (heart rate, body temperature, etc.) and activity information (number of steps, etc.) in real time.

[0441] An "anomaly detection method" is a system that has the ability to analyze acquired health and activity information and recognize unusual patterns or emergency situations.

[0442] The "emotion engine" is an algorithm that analyzes the user's voice and text input, as well as sensor data, to recognize the user's emotional state.

[0443] The "means for appropriately modifying a response" is a system that has the function of adjusting the generated response based on the user's emotional state recognized by the emotion engine.

[0444] "Activity Guide" refers to suggested activities and events based on a user's interests and emotional state.

[0445] "Real-time monitoring means" refers to a system for monitoring and collecting data on a user's health and emotional state in real time.

[0446] "Means for notification" means a function for promptly notifying the user and emergency contacts of detected abnormalities.

[0447] This invention combines an "anti-isolation AI" system with an emotion engine to realize safety and health management for the elderly and factory workers. This system uses sensors to monitor health conditions, an AI agent to conduct dialogue, and the emotion engine recognizes emotions and generates appropriate responses.

[0448] System configuration

[0449] 1. User profile data management (server)

[0450] The server manages profile data including the user's age, gender, hobbies, health status, past activity history, etc. This data is used to respond to the user's individual needs.

[0451] 2. Data entry and transmission (terminal, user)

[0452] The user inputs text or voice through the device, which then sends it to the server. For example, if the user inputs "What's the weather like today?", this message is sent to the server.

[0453] 3. Generating and Providing Responses (Server, Terminal)

[0454] The server analyzes the received input data and generates an appropriate response to the user's question. The generated response is provided to the user through the terminal. For example, the server generates a response such as "Today's weather is sunny," and the terminal displays it to the user.

[0455] 4. Data acquisition by sensors (terminal)

[0456] The device uses built-in sensors to collect real-time data on the user's health, including heart rate, steps taken, and body temperature, and this data is periodically sent to a server.

[0457] 5. Anomaly detection and notification (server)

[0458] The server analyzes the health data and detects abnormal patterns or emergencies. For example, if the heart rate is outside the normal range, the server will detect the abnormality. When the server detects an abnormality, it will send a notification to the user and their designated emergency contacts.

[0459] 6. Emotion Recognition by Emotion Engine (Server)

[0460] The server uses an emotion engine to recognize the user's emotions based on the user's input data and data acquired from the sensors. For example, the emotion engine analyzes the user's voice and text and detects "stress."

[0461] 7. Emotion-based response modification (server, terminal)

[0462] The server then modifies the response it generates based on the user's emotions as recognized by the emotion engine. For example, if the server detects that the user is under stress, it generates a response such as, "Why don't you try listening to some relaxing music?"

[0463] 8. Use in Emotion Data Analysis (Server)

[0464] The server also uses the emotion data recognized by the emotion engine as part of its analysis of health status and activity information. This data is also reflected in the anomaly detection process, enabling more accurate anomaly detection.

[0465] 9. Emotion-based activity guidance (server, terminal)

[0466] The server generates appropriate activity recommendations for the user based on the user's emotional data recognized by the emotion engine. For example, if the user is recognized as "depressed," the server will suggest that the user participate in relaxation activities or hobbies.

[0467] 10. Health management and mental support for factory workers (servers, terminals)

[0468] The system monitors the health and emotional state of factory workers in real time and notifies the workers and their managers if an abnormality is detected. For example, if a worker's heart rate is abnormally high, the server will notify the manager and suggest that the worker take a break.

[0469] Examples of concrete examples and prompts

[0470] As a concrete example, the following is an example of a prompt sentence to be input to a generative AI model:

[0471] prompt:

[0472] "To teach the emotion analysis engine the difference between stress and relaxation, consider the following situations:"

[0473] Situation 1:

[0474] "If the user's heart rate exceeds 90:"

[0475] Response 1:

[0476] "Stress detected. We'll give you some relaxation suggestions."

[0477] Situation 2:

[0478] If the user's heart rate is within the normal range:

[0479] Response 2:

[0480] "Users are relaxed. Keep it up."

[0481] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0482] Step 1:

[0483] The server collects profile data such as the user's age, gender, hobbies, health status, and past activity history through a means for managing user profile data and stores it in a database, which is then ready to generate appropriate responses based on the individual user profile.

[0484] Input: User profile data (age, gender, hobbies, health status, activity history, etc.)

[0485] Output: User profile data stored in a database

[0486] Specific operation: The server receives the profile information provided by the user via the input form or voice and performs the process of recording it in the database.

[0487] Step 2:

[0488] The user provides input data through the terminal by text or voice, which the terminal transmits to the server, for example, by inputting a question such as "What's the weather like today?"

[0489] Input: User input data (text or voice)

[0490] Output: User input data sent to the server

[0491] Specific operation: The terminal converts the text and voice data entered by the user into an appropriate format and sends it to the server via the network.

[0492] Step 3:

[0493] The server analyzes the received input data, compares it with the user profile data, and generates an appropriate response. For example, if the user asks, "What's the weather like today?", the server generates the response, "The weather is sunny today."

[0494] Input: User input data sent to the server, user profile data

[0495] Output: The generated response (e.g., "The weather is sunny today")

[0496] How it works: The server uses natural language processing algorithms to analyze the user's input data and uses generative AI models to create appropriate responses.

[0497] Step 4:

[0498] The terminal receives the response sent from the server and provides it to the user, so that the user can get an answer to their question.

[0499] Input: Response data sent from the server

[0500] Output: The response data that is provided to the user

[0501] Specific operation: The terminal displays or outputs the received response data in a format that is easy for the user to understand.

[0502] Step 5:

[0503] The device uses built-in sensors to collect real-time health data such as the user's heart rate, number of steps, and body temperature, and periodically transmits this data to a server.

[0504] Input: Health status data obtained from sensors (heart rate, steps, temperature, etc.)

[0505] Output: Health status data sent to the server

[0506] Specific operation: The terminal periodically collects data obtained from the sensors and transmits it to the server via the network.

[0507] Step 6:

[0508] The server analyzes the captured health data to detect abnormal patterns or emergencies, such as when a heart rate exceeds the normal range.

[0509] Input: Health status data sent from the device

[0510] Output: Anomaly detection flag, details of abnormality settings

[0511] Specific operation: The server analyzes the collected health data and executes an algorithm to determine abnormal conditions. If an abnormality is detected, it sets the necessary flag.

[0512] Step 7:

[0513] When the server detects an abnormality, it will send a notification to the user and designated emergency contacts to ensure the user's safety.

[0514] Input: Anomaly detection flag, details of abnormality settings

[0515] Output: Notification message (user and emergency contact)

[0516] Specific operation: When an anomaly is detected, the server sends a notification message to pre-registered contacts.

[0517] Step 8:

[0518] The server uses an emotion engine to recognize the user's emotions based on the user's input data and data obtained from sensors, for example, detecting stress from voice and text.

[0519] Input: User input data, health status data obtained from sensors

[0520] Output: Emotional state (e.g. "Stressed")

[0521] Specific operation: The server uses the emotion engine to analyze the user's input and sensor data to determine the emotional state.

[0522] Step 9:

[0523] The server then modifies the response it generates based on the emotion it recognizes. For example, if the server recognizes that the user is under stress, it will modify the response to something like, "Why don't you try listening to some relaxing music?"

[0524] Input: Emotional state

[0525] Output: Modified response data

[0526] Specific operation: The server uses the generative AI model to modify the response corresponding to the emotion and prepare it as a response to be provided to the user.

[0527] Step 10:

[0528] The server uses the emotion data recognized by the emotion engine as part of its analysis of health status and activity information and reflects this in the anomaly detection process, enabling more accurate anomaly detection.

[0529] Input: Emotion data, health status data

[0530] Output: Highly accurate anomaly detection results

[0531] Specific operation: The server adds emotion data to the anomaly detection algorithm and uses it to improve the accuracy of anomaly detection.

[0532] Step 11:

[0533] The server generates and provides appropriate activity guidance to the user based on the user's emotional state recognized by the emotion engine. For example, if the server recognizes that the user is depressed, it suggests relaxation activities.

[0534] Input: Emotional state

[0535] Output: Activity guide data

[0536] Specific operation: Based on the results of the emotion engine, the server generates activity guides and event suggestions for the user and sends them to the terminal.

[0537] Step 12:

[0538] The terminal displays the activity guide provided by the server to the user and prompts them to carry out the suggested activities. This step is important for improving the quality of the user's life and work.

[0539] Input: Activity guide data provided by the server

[0540] Output: Activity guide displayed to user

[0541] Specific operation: The terminal displays the activity guidance data received from the server on the user interface and provides guidance to the user by voice or text.

[0542] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0543] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0544] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0545] [Second embodiment]

[0546] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0547] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0548] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0549] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0550] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0551] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0552] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0553] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0554] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0555] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0556] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0557] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0558] This invention is an "anti-isolation AI" system that manages user profile data and input data and supports the safety and communication of elderly people. The system provides a series of functions, including data acquisition using sensors, dialogue support by AI agents, anomaly detection and notification, and activity guidance.

[0559] System configuration

[0560] 1. User profile data management (server)

[0561] The server manages profile data such as basic user information (age, gender, hobbies, health status) and past activity history.

[0562] 2. Data entry and transmission (terminal, user)

[0563] The user inputs text or voice through the device, which then sends it to the server. For example, if the user inputs "What's the weather like today?", this message is sent to the server.

[0564] 3. Generating and Providing Responses (Server, Terminal)

[0565] The server analyzes the received input data and generates an appropriate response to the user's question. The generated response is provided to the user through the terminal. For example, the server generates a response such as "Today's weather is sunny," and the terminal displays it to the user.

[0566] 4. Data acquisition by sensors (terminal)

[0567] The device uses built-in sensors to obtain real-time information about the user's health status (heart rate, steps, body temperature), and periodically transmits this data to a server.

[0568] 5. Anomaly detection and notification (server)

[0569] The server analyzes the health data sent and detects any abnormalities. For example, if the heart rate is outside the normal range, the server determines this to be an abnormality and sends a notification to the user and emergency contacts.

[0570] 6. Providing activity information (server, terminal)

[0571] The server suggests appropriate activities and events based on the user's profile data and interests, thereby facilitating social participation and interaction.

[0572] A natural language description of the program's operation

[0573] 1. Managing User Data

[0574] The server manages the user's profile data and records any updates made to it, for example, if a user takes up a new hobby, "gardening," the server records this.

[0575] 2. Sending input data and generating a response

[0576] The device sends the data entered by the user to the server, which analyzes it and generates a response. For example, if the user asks, "What's the weather like today?", the server responds, "It's sunny today," and sends it to the device.

[0577] 3. Sensor data acquisition and anomaly detection

[0578] The device monitors the user's health status and sends it to a server. The server analyzes the received data and notifies the user if an abnormality is detected. For example, if the user's heart rate is abnormally high, the server notifies an emergency contact.

[0579] 4. Providing information about activities

[0580] The server generates activity recommendations based on the user's interests and profile, for example, telling the user, "There's a gardening workshop being held at a nearby park."

[0581] The system of the present invention reduces the sense of isolation felt by elderly people and enables them to respond quickly to abnormal situations, allowing them to live with peace of mind.

[0582] The processing flow will be explained below.

[0583] Step 1:

[0584] The device starts up and displays a screen for the user to log in. The user enters their username and password on the login screen and taps the login button.

[0585] Step 2:

[0586] The device sends the login information to the server. The server verifies the received login information, and if authentication is successful, it sends the home screen data. The device then displays the home screen.

[0587] Step 3:

[0588] The user selects the "Chat" icon on the home screen to begin a conversation with the AI ​​agent, and then types "What's the weather like today?" into the input field.

[0589] Step 4:

[0590] The device receives the text data entered by the user and sends it to the server. The server analyzes the received input data and generates a response such as "Today's weather is sunny." The server then sends the generated response data to the device.

[0591] Step 5:

[0592] The device displays the received response data to the user, who sees the message "Today's weather is sunny."

[0593] Step 6:

[0594] The device uses built-in sensors to collect real-time data on the user's health, including heart rate, steps taken, and body temperature, and this data is periodically sent to a server.

[0595] Step 7:

[0596] The server analyzes the received health data and detects abnormal patterns or emergencies. For example, if the heart rate is outside the normal range, the server will detect an abnormality.

[0597] Step 8:

[0598] If the server detects an abnormality, it will notify the user and designated emergency contacts, who will be informed via email and SMS.

[0599] Step 9:

[0600] The user selects the "Activity Guide" icon and receives suggestions for categories and events that interest them. The server references the user's profile data and generates appropriate activity guides.

[0601] Step 10:

[0602] The server sends the generated activity guide to the terminal, which then displays the received activity guide to the user, encouraging them to participate in specific events or online courses.

[0603] Example 1

[0604] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0605] Communication support and health monitoring in daily life are important for reducing feelings of isolation and improving safety for the elderly. However, existing systems lack sufficient activity guidance based on the user's interests or prompt notification when an abnormality is detected, and an improved user experience is required. In addition, there is a lack of technology to generate more appropriate responses through voice input text conversion and natural language processing using generative AI models. A new system that solves these issues is needed.

[0606] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0607] In this invention, the server includes: means for managing user profile data; means for acquiring and transmitting user input data to the server; means for the server to generate an appropriate response based on the user profile data and input data; means for providing the generated response to the user; means for acquiring the user's health status and activity information using a sensor and transmitting it to the server; means for the server to analyze the acquired health status and activity information and detect abnormalities; means for notifying the user and emergency contacts when an abnormality is detected; means for a generative AI model with natural language processing capabilities to generate the generated response; and means for converting the user's input data from voice to text. This improves the safety and communication of elderly people. It also enables activity guidance based on the user's interests and rapid response when an abnormality is detected.

[0608] "User profile data" refers to data that includes basic information about the user (age, gender, hobbies, health status) and past activity history.

[0609] "Input data" refers to text and voice data that a user inputs through a terminal.

[0610] A "server" is a computer system that analyzes user profile data and input data and generates an appropriate response.

[0611] A "generative AI model" refers to an algorithm or machine learning model that has natural language processing capabilities and generates appropriate responses based on input data.

[0612] A "sensor" is a device that acquires a user's health status (heart rate, body temperature, number of steps, etc.) and activity information in real time.

[0613] "Abnormality detection" refers to the server analyzing acquired health status and activity information and determining abnormal conditions that exceed the normal range.

[0614] "Notification" refers to the act of sending an alert to the user and emergency contacts when an abnormality is detected.

[0615] "Activity Guides" are suggested activities and events based on a user's profile data and interests.

[0616] "Speech to text conversion" refers to the process of converting voice input data into text data.

[0617] "Natural language processing" refers to the technology that enables computers to understand and generate human language.

[0618] MODE FOR CARRYING OUT THE INVENTION

[0619] This invention is an "anti-isolation AI" system that supports the safety and communication of elderly people. The system manages user profile data and input data, and provides a series of functions such as health monitoring using sensors, dialogue support using generative AI models, anomaly detection and notification, and activity guidance.

[0620] The system configuration uses the following hardware and software:

[0621] User data management (server)

[0622] The server manages profile data such as basic user information (age, gender, hobbies, health status) and past activity history. This data is stored and managed appropriately using a database management system (DBMS), and any updates are recorded as appropriate.

[0623] Specific examples

[0624] If a user becomes interested in "gardening" as a new hobby, the server records this information in the database.

[0625] Data entry and transmission (terminal, user)

[0626] The user inputs a message through the device using text or voice. The input data is sent from the device to the server. If voice input is performed, the device converts this voice into text.

[0627] Specific examples

[0628] When a user asks "What's the weather like today?", the device converts this into text and sends it to the server.

[0629] Prompt Sentence Examples

[0630] Parse the text asking about today's weather and generate an appropriate response.

[0631] Response generation and delivery (server, terminal)

[0632] The server analyzes the data received from the user using the generative AI model and generates an appropriate response, which is then provided to the user via their device.

[0633] Specific examples

[0634] When a user asks, "What's the weather like today?", the generative AI model is used to analyze the question and generate a response such as "The weather is sunny today," which the device then notifies the user.

[0635] Sensor data acquisition (terminal)

[0636] The device uses built-in sensors to obtain real-time information about the user's health status (heart rate, body temperature, number of steps) and periodically transmits this data to a server.

[0637] Specific examples

[0638] The device measures the number of heartbeats per minute and sends this data to a server.

[0639] Anomaly detection and notification (server)

[0640] The server analyzes the health data and detects any abnormalities. If an abnormality is detected, a notification is sent to the user and their emergency contacts.

[0641] Specific examples

[0642] The server detects an abnormal heart rate and sends a notification to the user and emergency contacts saying, "Your heart rate is too high."

[0643] Providing activity information (server, terminal)

[0644] The server suggests appropriate activities and events based on the user's profile data and interests, thereby facilitating social participation and interaction.

[0645] Specific examples

[0646] Based on the user's profile data, the server recommends, "There's a gardening workshop being held in a nearby park."

[0647] The system of the present invention reduces the sense of isolation felt by the elderly, providing them with peace of mind and companionship in their daily lives. It also provides a safe environment by enabling rapid response to emergency situations.

[0648] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0649] Program processing flow

[0650] Step 1: Managing User Profile Data (Server)

[0651] The server stores profile data such as basic user information (age, gender, hobbies, health status) and past activity history in a database. When a user registers or updates their profile data, it manages this data and records the changes.

[0652] input

[0653] User basic information (age, gender, hobbies, health condition)

[0654] process

[0655] The server uses a database management system (DBMS) to properly store and manage user information.

[0656] output

[0657] A database with updated user profile data

[0658] Specific actions

[0659] The server receives the new user's registration information and stores it in a database.

[0660] When a user adds a new hobby (e.g. gardening), the server records this change in the database.

[0661] Step 2: Data entry and transmission (terminal, user)

[0662] The user inputs text or voice through the device, which processes the input data and sends it to the server. If voice input is used, the device converts the voice into text.

[0663] input

[0664] User voice or text input

[0665] process

[0666] The device converts the voice input into text and sends this data to the server.

[0667] output

[0668] Textual input data sent to the server

[0669] Specific actions

[0670] The user speaks, "What's the weather like today?"

[0671] The device converts the voice into text and sends the text data "What's the weather like today?" to the server.

[0672] Step 3: Generate and serve a response (server, terminal)

[0673] The server analyzes the data received from the user using the generative AI model and generates an appropriate response, which is then provided to the user via their device.

[0674] input

[0675] Text input data sent by the user

[0676] process

[0677] The server uses a generative AI model to analyze the input data and generate an appropriate response.

[0678] output

[0679] Generated response text

[0680] Specific actions

[0681] The server parses the question "What's the weather today?" and generates the response "The weather is sunny today."

[0682] The device displays or plays this response to the user.

[0683] Step 4: Acquiring sensor data (device)

[0684] The device uses built-in sensors to obtain the user's health status (heart rate, body temperature, number of steps) in real time and periodically transmits this data to a server.

[0685] input

[0686] Health status data acquisition using sensors

[0687] process

[0688] The health data collected by the device is periodically sent to a server.

[0689] output

[0690] Health status data sent to the server

[0691] Specific actions

[0692] The device measures the user's heart rate every minute and sends this data to a server.

[0693] Step 5: Anomaly detection and notification (server)

[0694] The server analyzes the health data and detects any abnormalities. If an abnormality is detected, a notification is sent to the user and their emergency contacts.

[0695] input

[0696] Health data sent from the device

[0697] process

[0698] The server analyzes health data and detects abnormalities that exceed the normal range.

[0699] output

[0700] Anomaly detection notification message

[0701] Specific actions

[0702] The server detects abnormal heart rate and sends a notification to the user and emergency contacts saying, "Your heart rate is too high."

[0703] Step 6: Providing activity information (server, terminal)

[0704] The server suggests appropriate activities and events based on the user's profile data and interests, thereby facilitating social participation and interaction.

[0705] input

[0706] User profile data and interest data stored on the server

[0707] process

[0708] The server searches for and generates appropriate activities and events based on the user's interests.

[0709] output

[0710] Proposed activities and event information

[0711] Specific actions

[0712] Based on the user's interest data, the server recommends, "There's a gardening workshop being held in a nearby park."

[0713] The device will notify the user of this information.

[0714] Through the above processing steps, the system of the present invention improves safety and communication for the elderly. It also enables activity guidance based on the user's interests and quick response when an abnormality is detected.

[0715] (Application example 1)

[0716] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0717] The problems of elderly isolation and lack of health monitoring are serious issues. Elderly operators working in factories and other facilities require real-time monitoring of their health status while ensuring work safety and efficiency, but current systems are unable to adequately address this. Therefore, a system is needed that effectively supports the safety and communication of elderly operators and enables rapid response in the event of an emergency.

[0718] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0719] In this invention, the server includes: means for managing user profile data; means for acquiring and transmitting user input data to the server; means for the server to generate an appropriate response based on the user profile data and input data; means for providing the generated response to the user; means for acquiring the user's health condition and activity information using a sensor and transmitting it to the server; means for the server to analyze the acquired health condition and activity information and detect abnormalities; means for notifying the user and emergency contacts when an abnormality is detected; and dialogue support means using an industrial robot equipped with an AI agent to support elderly operators in factories. This enables real-time monitoring of the health condition of elderly operators and rapid response to abnormalities while ensuring their safety and work efficiency.

[0720] "User profile data" refers to the user's basic information (age, gender, hobbies, health status) and past activity history.

[0721] "Input Data" refers to information such as messages or questions entered by the user via text or voice.

[0722] "Server" refers to a computer system for processing user profile data and input data and generating an appropriate response.

[0723] "Generated response" refers to an answer or guidance generated by the server based on user input data.

[0724] "Sensor" refers to a device that acquires a user's health status (heart rate, body temperature, number of steps, etc.) and activity information in real time.

[0725] "Analysis" refers to the process of analyzing information based on acquired data and detecting anomalies and patterns.

[0726] "Anomaly detection" refers to detecting values ​​or trends that exceed the normal range through analysis results.

[0727] "Emergency contacts" refers to contact information for the user's family, medical institutions, etc. who will be notified when an abnormality is detected.

[0728] An "AI agent" refers to software that uses artificial intelligence to interact with users and provide appropriate responses and guidance.

[0729] An "industrial robot" refers to an automated mechanical device used in production sites such as factories.

[0730] "Dialogue support" refers to supporting communication between elderly operators and industrial robots.

[0731] "Activity Guide" refers to suggested activities and events based on a user's interests and profile.

[0732] "Cloud" refers to computing resources provided over the Internet.

[0733] "Real-time" refers to the immediacy and processing and provision of information with almost no delay.

[0734] The present invention relates to an "elderly operator support system" that ensures the safety and work efficiency of elderly operators while enabling real-time monitoring of their health status and prompt response in the event of an abnormality. Specific embodiments are described below.

[0735] System configuration

[0736] 1. User profile data management (server)

[0737] The server manages profile data such as basic information (age, gender, hobbies, health status) of the elderly operator users and their past work history. For example, if a new task or skill is added, the server updates and records it.

[0738] 2. Data entry and transmission (terminal, user)

[0739] The user inputs different types of data (text and voice) through a tablet or voice input device and sends this to the server, for example, asking "What do I do next?"

[0740] 3. Generating and Providing Responses (Server, Terminal)

[0741] The server analyzes the received input data and generates an appropriate response to the user's question. The generated response is provided to the user via a tablet or voice device. For example, the server generates a response such as "Next, we will inspect the part" and displays it on the terminal.

[0742] 4. Data acquisition by sensors (terminal)

[0743] The terminal uses sensors built into the wearable device to obtain real-time information on the elderly operator's health, such as heart rate, body temperature, and number of steps taken, and this data is periodically sent to a server.

[0744] 5. Anomaly detection and notification (server)

[0745] The server analyzes the health data and detects any abnormalities. For example, if the heart rate exceeds the normal range, the server determines this to be an abnormality and sends a notification to the factory manager and emergency contact.

[0746] 6. Providing activity information (server, terminal)

[0747] The server suggests the next task and efficient work methods based on the elderly operator's profile data and past work history, thereby improving the user's work efficiency.

[0748] A natural language description of the program's operation

[0749] 1. Managing User Data

[0750] The server manages basic information and past work history of elderly operators and records any updates. For example, if a new skill is added, the server adds it to the profile data.

[0751] 2. Sending input data and generating a response

[0752] The terminal sends the data entered by the user to the server, which analyzes it and generates an appropriate response. For example, if the user asks, "What's next?", the server generates the response, "Next is to inspect the part," and sends it to the terminal.

[0753] 3. Sensor data acquisition and anomaly detection

[0754] The device monitors the health status of the elderly operator and sends the information to a server. The server analyzes the received data and notifies the factory manager and emergency contacts if an abnormality is detected. For example, if the user's heart rate is abnormally high, the server notifies the factory manager and emergency contacts.

[0755] 4. Providing information about activities

[0756] The server generates activity guides based on the interests and profile of the elderly operator, for example, providing the user with a guide such as, "Next is a parts inspection, followed by machine maintenance."

[0757] Specific Examples

[0758] Examples:

[0759] If an elderly operator working at a precision manufacturing factory experiences an abnormally high temperature while inspecting a product, the factory manager and emergency contacts will be automatically notified. The operator can also ask the AI ​​assistant, "What should I do next?" to confirm the next steps.

[0760] Example prompts to input to a generative AI model:

[0761] "If an elderly operator working in a manufacturing plant feels unwell during the night shift, write a program on how an AI assistant can assist in this situation and notify the manager."

[0762] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0763] Step 1:

[0764] A user inputs profile data into a terminal. For example, basic information such as age, gender, hobbies, and health status is input. This input data is stored in a database and sent to a server. The input data is processed to generate profile data, which is then registered on the server.

[0765] Step 2:

[0766] The user enters a question or command through the device, for example, "What do I do next?" using text or voice input. The device sends this to the server, which processes the input data, analysing the text or voice data and converting it into an appropriate format.

[0767] Step 3:

[0768] The server analyzes the received input data and generates an appropriate response. This analysis is performed using a generative AI model that includes natural language processing. For example, in response to the input query "What task will be performed next?", a response such as "Next is the inspection of the parts" is generated. Data analysis organizes the information and generates response data.

[0769] Step 4:

[0770] The generated response data is sent from the server to the terminal and provided to the user. For example, a text response is displayed on the tablet screen or read aloud. An output based on the server's response data is generated and displayed on the terminal.

[0771] Step 5:

[0772] The terminal uses sensors built into the wearable device to acquire the user's health data (heart rate, body temperature, number of steps, etc.) in real time. The acquired data is periodically sent to a server. The real-time health data is generated and transmitted based on the data acquired by the sensors.

[0773] Step 6:

[0774] The server analyzes the acquired health data and detects any abnormalities. For example, if the heart rate is outside the normal range, the server determines this as an abnormality. Anomaly detection based on data analysis determines whether or not there is an abnormality.

[0775] Step 7:

[0776] If an abnormality is detected, the server sends a notification to the user and emergency contacts. For example, if the heart rate is abnormally high, the server notifies the factory manager and emergency contacts. The notification function enables a prompt response when an abnormality is detected.

[0777] Step 8:

[0778] The server suggests the next task and the most efficient way to work based on the user's profile data and past work history. For example, it provides the user with guidance such as, "Next is the parts inspection, followed by machine maintenance." Data analysis and suggestion functions aim to improve work efficiency.

[0779] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0780] This invention combines an emotion engine with an "anti-isolation AI" system that supports the safety and communication of elderly people. The system provides functions such as data acquisition using sensors, dialogue support by an AI agent, anomaly detection and notification, activity guidance, and an emotion engine that recognizes user emotions.

[0781] System configuration

[0782] 1. User profile data management (server)

[0783] The server manages profile data such as basic user information (age, gender, hobbies, health status) and past activity history.

[0784] 2. Data entry and transmission (terminal, user)

[0785] The user inputs text or voice through the device, which then sends it to the server. For example, if the user inputs "What's the weather like today?", this message is sent to the server.

[0786] 3. Generating and Providing Responses (Server, Terminal)

[0787] The server analyzes the received input data and generates an appropriate response to the user's question. The generated response is provided to the user through the terminal. For example, the server generates a response such as "Today's weather is sunny," and the terminal displays it to the user.

[0788] 4. Data acquisition by sensors (terminal)

[0789] The device uses built-in sensors to collect real-time data on the user's health, including heart rate, steps taken, and body temperature, and this data is periodically sent to a server.

[0790] 5. Anomaly detection and notification (server)

[0791] The server analyzes the health data and detects abnormal patterns or emergencies. For example, if the heart rate is outside the normal range, the server will detect the abnormality. When the server detects an abnormality, it will send a notification to the user and their designated emergency contacts.

[0792] 6. Emotion Recognition by Emotion Engine (Server)

[0793] The server uses an emotion engine to recognize the user's emotions based on the user's input data and data acquired from the sensors. For example, the emotion engine analyzes the user's voice and text and detects "stress."

[0794] 7. Emotion-based response modification (server, terminal)

[0795] The server then modifies the response it generates based on the user's emotions as recognized by the emotion engine. For example, if the server detects that the user is under stress, it generates a response such as, "Why don't you try listening to some relaxing music?"

[0796] 8. Use in Emotion Data Analysis (Server)

[0797] The server also uses the emotion data recognized by the emotion engine as part of its analysis of health status and activity information. This data is also reflected in the anomaly detection process, enabling more accurate anomaly detection.

[0798] 9. Emotion-based activity guidance (server, terminal)

[0799] The server generates appropriate activity recommendations for the user based on the user's emotional data recognized by the emotion engine. For example, if the user is recognized as "depressed," the server will suggest that the user participate in relaxation activities or hobbies.

[0800] A natural language description of the program's operation

[0801] 1. Managing User Data

[0802] The server manages the user's profile data and records any updates made to it, for example, if a user takes up a new hobby, "gardening," the server records this.

[0803] 2. Sending input data and generating a response

[0804] The device sends the data entered by the user to the server, which analyzes it and generates a response. For example, if the user asks, "What's the weather like today?", the server responds, "It's sunny today," and sends it to the device.

[0805] 3. Sensor data acquisition and anomaly detection

[0806] The device monitors the user's health status and sends it to a server. The server analyzes the received data and notifies the user if an abnormality is detected. For example, if the user's heart rate is abnormally high, the server notifies an emergency contact.

[0807] 4. Emotional Data Recognition and Response Modification

[0808] The server analyzes the user's input data and sensor data using an emotion engine to recognize the user's emotions. For example, if the user is under stress, the server will modify the response and provide it via the device, suggesting, "Why not try listening to some relaxing music?"

[0809] 5. Use in Emotion Data Analysis

[0810] The server uses the emotional data recognized by the emotion engine to analyze the user's health status and reflects this in the anomaly detection process. For example, if a user is depressed over a long period of time, it can take action such as suggesting early consultation with a doctor or counselor.

[0811] 6. Emotion-based activity guidance

[0812] The server generates appropriate activity recommendations based on the user's emotional state. For example, a "depressed" user might be provided with relaxation activities to encourage social interaction.

[0813] By incorporating an emotion engine, the system of the present invention can flexibly respond to the user's emotional state, reduce the elderly's sense of isolation, and provide support for them to live with peace of mind.

[0814] The processing flow will be explained below.

[0815] Step 1:

[0816] The device starts up and displays a screen for the user to log in. The user enters their username and password on the login screen and taps the login button.

[0817] Step 2:

[0818] The device sends the login information to the server. The server verifies the received login information, and if authentication is successful, it sends the home screen data. The device then displays the home screen.

[0819] Step 3:

[0820] The user selects the "Chat" icon on the home screen to begin a conversation with the AI ​​agent, and then types "What's the weather like today?" into the input field.

[0821] Step 4:

[0822] The device receives the text data entered by the user and sends it to the server. The server analyzes the received input data and generates a response such as "Today's weather is sunny." The server then sends the generated response data to the device.

[0823] Step 5:

[0824] The device displays the received response data to the user, who sees the message "Today's weather is sunny."

[0825] Step 6:

[0826] The device uses built-in sensors to collect real-time data on the user's health, including heart rate, steps taken, and body temperature, and this data is periodically sent to a server.

[0827] Step 7:

[0828] The server analyzes the received health data and detects abnormal patterns or emergencies. For example, if the heart rate is outside the normal range, the server will detect an abnormality.

[0829] Step 8:

[0830] If the server detects an abnormality, it will notify the user and designated emergency contacts, who will be informed via email and SMS.

[0831] Step 9:

[0832] The server uses an emotion engine to analyze user input data and sensor data to recognize the user's emotions. For example, it can detect "anxiety" from the text and voice input of the user.

[0833] Step 10:

[0834] The server then modifies the response appropriately based on the user's emotions as determined by the emotion engine. For example, if the server determines that the user is feeling anxious, it generates a response suggesting, "Why not try listening to some relaxing music?"

[0835] Step 11:

[0836] The device displays the modified response to the user, who sees the message, "Why not try listening to some relaxing music?"

[0837] Step 12:

[0838] The server also uses the emotional data recognized by the emotion engine to analyze health status and activity information. For example, if a user has been feeling depressed for a long period of time, that data will be reflected in the analysis.

[0839] Step 13:

[0840] The server generates appropriate activity guides based on the emotion data recognized by the emotion engine, suggesting activities, events, relaxation methods, etc. according to the user's emotional state.

[0841] Step 14:

[0842] The device displays the generated activity guide to the user. For example, if the user is feeling "down," the device provides a guide such as "Why don't you join a gardening event at a nearby park?"

[0843] Example 2

[0844] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0845] There is a need to reduce the sense of isolation felt by the elderly and provide an environment where they can live safely while maintaining social connections. In particular, there is a lack of systems that can monitor their health and emotional state in real time and provide appropriate responses accordingly. Furthermore, there is a challenge in providing more accurate anomaly detection and activity guidance that takes emotional state into account.

[0846] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for managing user profile data, means for acquiring and analyzing user input data and generating an appropriate response, means for acquiring the user's health condition and activity information and detecting abnormalities, means for recognizing emotions based on the user input data and data acquired from the sensor, means for modifying responses based on the recognized emotions, means for analyzing the emotion data and reflecting it in the anomaly detection process, and means for generating appropriate activity guidance based on the emotion data and providing it to the user. This makes it possible to comprehensively monitor the health condition and emotional state and provide appropriate responses and guidance, allowing elderly people to live with peace of mind and reducing their sense of isolation.

[0847] "User Profile Data" refers to basic information such as age, gender, hobbies, health status, and past activity history.

[0848] "Server" refers to a computer system that processes data received from users, manages profile data, generates responses, detects anomalies, etc.

[0849] "Terminal" refers to a device that allows a user to manipulate input data and obtain health and activity information through sensors.

[0850] "Input data" refers to text and voice data provided by the user through the terminal.

[0851] "Generated response" refers to a reply or suggestion to the user that the server generates by analyzing the input data.

[0852] "Sensors" refer to devices that measure a user's health status, such as heart rate, steps, and body temperature, in real time.

[0853] "Health status and activity information" refers to data on the user's physical condition and behavior obtained through sensors.

[0854] "Anomaly detection" refers to the process by which the server analyzes health and activity information to discover unusual patterns or emergencies.

[0855] "Emotion engine" refers to an algorithm or program that analyzes user input data and sensor data to recognize emotions.

[0856] "Emotional Data" refers to information about a user's emotional state as recognized by the Emotion Engine.

[0857] "Activity guidance" refers to information about suggested activities based on a user's interests and emotional state.

[0858] "Emergency Contact" means a person or entity designated to receive notification when an anomaly is detected.

[0859] MODE FOR CARRYING OUT THE INVENTION

[0860] This invention is a system for supporting the safety and communication of the elderly, and it manages and analyzes user profile data, health data, and emotion data in an integrated manner. This system includes a server, terminals, sensors, emotion engine, etc., which work together to support the lives of the elderly.

[0861] System configuration

[0862] The system includes the following main components:

[0863] 1. Server

[0864] Profile data management: Store user basic information (age, gender, hobbies, health status, and past activity history) in a database and update it as needed.

[0865] Response generation: Based on the input data received from the user, a generative AI model is used to generate an appropriate response.

[0866] Anomaly detection: Analyzes health status and activity information sent from sensors to detect abnormalities.

[0867] Emotion Recognition: Recognize emotions from user input data and sensor data using an emotion engine.

[0868] Response Modification: Modify the response based on the recognized emotion data and provide it to the user.

[0869] 2. Terminal

[0870] Data Entry: Allows users to enter text or voice data, which is then sent to the server.

[0871] Sensor data acquisition: The built-in sensors are used to acquire the user's health data, such as heart rate, steps, and body temperature, in real time and send it to the server.

[0872] 3. Sensors

[0873] Health monitoring: Measures the user's heart rate, steps, temperature, etc.

[0874] 4. Emotion Engine

[0875] Sentiment analysis: Recognizing user emotions based on their voice, text, and health data.

[0876] System operation example

[0877] A concrete example of the system in action is as follows:

[0878] 1. Entering and submitting user data

[0879] User: For example, type "What's the weather like today?" into the device.

[0880] Terminal: Sends the entered data to the server.

[0881] 2. Generating and Displaying the Response

[0882] Server: Analyzes the input data using a generative AI model and generates a response such as "Today's weather is sunny."

[0883] Terminal: Displays the generated response to the user.

[0884] 3. Health data acquisition and anomaly detection

[0885] Sensor: Monitors the user's heart rate and sends the data to the server via the device.

[0886] Server: Analyzes the transmitted data and sends a notification to emergency contacts if the heart rate is abnormally high.

[0887] 4. Emotional Data Recognition and Response Modification

[0888] Server: Using the emotion engine, recognize emotions from user input data and sensor data. For example, if the input text is "tired," it detects "stress."

[0889] Server: Based on the recognized emotion, the server modifies the response to "Why not try listening to some relaxing music?" and provides it through the device.

[0890] Prompt Sentence Examples

[0891] Here are some example prompts to input to the generative AI model:

[0892] Answering questions

[0893] Prompt text: "The user types 'What's the weather today?' How should the server respond?"

[0894] Example response generated: "The weather is sunny today."

[0895] Emotion Recognition and Response Modification

[0896] Prompt: "By analyzing the user's text or voice data, how can the server recognize the user's emotions and generate a response based on them?"

[0897] Example generated response: "We've detected stress in your voice. Would you like to try listening to some relaxing music?"

[0898] This system can comprehensively monitor the user's health and emotional state, and generate appropriate responses and activity guidance based on that information, thereby providing support that allows elderly people to live with peace of mind.

[0899] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0900] Step 1:

[0901] Managing your profile data

[0902] Input: Basic information entered by the user when registering (age, gender, hobbies, health status, and past activity history)

[0903] What it does: The server receives input data from the user, stores it in a database, and updates existing data when the user provides new information.

[0904] Data Processing: The server merges the new information with the existing profile data to maintain consistency.

[0905] Output: Updated profile data is saved to the database.

[0906] Step 2:

[0907] Entering and Submitting Data

[0908] Input: The user uses the device to input text or voice data.

[0909] What happens: The user types a question, such as "What's the weather like today?"

[0910] Data processing: The device converts the text or voice data into a digital format and sends it to the server.

[0911] Output: The transformed input data is sent to the server.

[0912] Step 3:

[0913] Generating and serving the response

[0914] Input: User input data received by the server

[0915] Specific operation: The server uses a generative AI model to analyze the input data.

[0916] Data processing: Analyzes input data and generates appropriate responses.

[0917] Output: The generated response is sent to the terminal and displayed to the user. Example: "The weather is sunny today."

[0918] Step 4:

[0919] Acquiring Sensor Data

[0920] Input: Real-time data such as user heart rate, steps, and body temperature

[0921] How it works: Sensors built into the device measure these data.

[0922] Data processing: The acquired data is periodically sent to the server.

[0923] Output: The data acquired by the sensor is sent to the server.

[0924] Step 5:

[0925] Anomaly detection and notification

[0926] Input: Sensor data received by the server

[0927] Specific operation: The server analyzes the sensor data and detects abnormalities, such as when the heart rate exceeds the normal range.

[0928] Data processing: Analyze the data using anomaly detection algorithms.

[0929] Output: If an anomaly is detected, a notification is sent to the user and emergency contacts.

[0930] Step 6:

[0931] Emotion recognition by emotion engine

[0932] Input: User input and sensor data

[0933] Specific operation: The server uses an emotion engine to analyze this data and recognize the user's emotions.

[0934] Data processing: The emotion engine identifies the user's emotional state as a result of the analysis.

[0935] Output: Recognized emotion data is generated. Example: "I feel stressed."

[0936] Step 7:

[0937] Emotion-Based Response Modification

[0938] Input: Emotion data generated by the emotion engine

[0939] Specific behavior: The server modifies the generated response based on the emotion data.

[0940] Data processing: Regenerate the response content and modify it to correspond to the emotion.

[0941] Output: The modified response is sent to the terminal and provided to the user. Example: "Why not try listening to some relaxing music?"

[0942] Step 8:

[0943] Use in analyzing emotion data

[0944] Input: Emotion data recognized by the emotion engine

[0945] Specific operation: The server also reflects the emotion data in the anomaly detection process.

[0946] Data processing: Integrating emotion data into health analysis parameters.

[0947] Output: Consolidated analytical data is generated.

[0948] Step 9:

[0949] Emotion-based activity guidance

[0950] Input: Emotion data recognized by the emotion engine

[0951] Specific operation: The server generates appropriate activity guidance for the user based on the emotion data.

[0952] Data processing: Generate activities that match the emotional state.

[0953] Output: The generated activity guide is sent to the terminal and provided to the user. Example: "Try participating in a relaxation activity."

[0954] Through these processing steps, the system monitors the health and emotional state of elderly people in real time, and provides appropriate responses and activity guidance based on that information, thereby supporting an environment in which they can live with peace of mind.

[0955] (Application example 2)

[0956] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0957] While safety and health management for elderly people and factory workers is important, existing systems do not adequately monitor their health and emotional states in real time. Furthermore, there is a lack of systems that can quickly detect abnormalities and take appropriate action. Therefore, there is a need for a system that can respond promptly when an abnormality occurs.

[0958] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for managing user profile data; means for acquiring and transmitting user input data to the server; means for the server to generate an appropriate response based on the user profile data and input data; means for providing the generated response to the user; means for acquiring and transmitting user health and activity information using a sensor; means for the server to analyze the acquired health and activity information and detect abnormalities; means for notifying the user and emergency contacts when an abnormality is detected; means for recognizing the user's emotional state using an emotion engine; means for appropriately modifying the generated response based on the emotional state; means for generating and providing activity guidance based on the emotional state; means for monitoring the health and emotional states of factory workers in real time; and means for notifying workers and managers when an abnormality is detected. This makes it possible to monitor the health and emotional states of elderly people and factory workers in real time, quickly detect abnormalities, and take appropriate action.

[0959] "User profile data" refers to information such as the user's age, gender, hobbies, health status, and past activity history.

[0960] "Input Data" means information entered by a User through text or voice that is transmitted to the Server.

[0961] "Server" means a central computer that analyzes user input and profile data and generates and provides appropriate responses.

[0962] A "sensor" is a device that acquires a user's health status (heart rate, body temperature, etc.) and activity information (number of steps, etc.) in real time.

[0963] An "anomaly detection method" is a system that has the ability to analyze acquired health and activity information and recognize unusual patterns or emergency situations.

[0964] The "emotion engine" is an algorithm that analyzes the user's voice and text input, as well as sensor data, to recognize the user's emotional state.

[0965] The "means for appropriately modifying a response" is a system that has the function of adjusting the generated response based on the user's emotional state recognized by the emotion engine.

[0966] "Activity Guide" refers to suggested activities and events based on a user's interests and emotional state.

[0967] "Real-time monitoring means" refers to a system for monitoring and collecting data on a user's health and emotional state in real time.

[0968] "Means for notification" means a function for promptly notifying the user and emergency contacts of detected abnormalities.

[0969] This invention combines an "anti-isolation AI" system with an emotion engine to realize safety and health management for the elderly and factory workers. This system uses sensors to monitor health conditions, an AI agent to conduct dialogue, and the emotion engine recognizes emotions and generates appropriate responses.

[0970] System configuration

[0971] 1. User profile data management (server)

[0972] The server manages profile data including the user's age, gender, hobbies, health status, past activity history, etc. This data is used to respond to the user's individual needs.

[0973] 2. Data entry and transmission (terminal, user)

[0974] The user inputs text or voice through the device, which then sends it to the server. For example, if the user inputs "What's the weather like today?", this message is sent to the server.

[0975] 3. Generating and Providing Responses (Server, Terminal)

[0976] The server analyzes the received input data and generates an appropriate response to the user's question. The generated response is provided to the user through the terminal. For example, the server generates a response such as "Today's weather is sunny," and the terminal displays it to the user.

[0977] 4. Data acquisition by sensors (terminal)

[0978] The device uses built-in sensors to collect real-time data on the user's health, including heart rate, steps taken, and body temperature, and this data is periodically sent to a server.

[0979] 5. Anomaly detection and notification (server)

[0980] The server analyzes the health data and detects abnormal patterns or emergencies. For example, if the heart rate is outside the normal range, the server will detect the abnormality. When the server detects an abnormality, it will send a notification to the user and their designated emergency contacts.

[0981] 6. Emotion Recognition by Emotion Engine (Server)

[0982] The server uses an emotion engine to recognize the user's emotions based on the user's input data and data acquired from the sensors. For example, the emotion engine analyzes the user's voice and text and detects "stress."

[0983] 7. Emotion-based response modification (server, terminal)

[0984] The server then modifies the response it generates based on the user's emotions as recognized by the emotion engine. For example, if the server detects that the user is under stress, it generates a response such as, "Why don't you try listening to some relaxing music?"

[0985] 8. Use in Emotion Data Analysis (Server)

[0986] The server also uses the emotion data recognized by the emotion engine as part of its analysis of health status and activity information. This data is also reflected in the anomaly detection process, enabling more accurate anomaly detection.

[0987] 9. Emotion-based activity guidance (server, terminal)

[0988] The server generates appropriate activity recommendations for the user based on the user's emotional data recognized by the emotion engine. For example, if the user is recognized as "depressed," the server will suggest that the user participate in relaxation activities or hobbies.

[0989] 10. Health management and mental support for factory workers (servers, terminals)

[0990] The system monitors the health and emotional state of factory workers in real time and notifies the workers and their managers if an abnormality is detected. For example, if a worker's heart rate is abnormally high, the server will notify the manager and suggest that the worker take a break.

[0991] Examples of concrete examples and prompts

[0992] As a concrete example, the following is an example of a prompt sentence to be input to a generative AI model:

[0993] prompt:

[0994] "To teach the emotion analysis engine the difference between stress and relaxation, consider the following situations:"

[0995] Situation 1:

[0996] "If the user's heart rate exceeds 90:"

[0997] Response 1:

[0998] "Stress detected. We'll give you some relaxation suggestions."

[0999] Situation 2:

[1000] If the user's heart rate is within the normal range:

[1001] Response 2:

[1002] "Users are relaxed. Keep it up."

[1003] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1004] Step 1:

[1005] The server collects profile data such as the user's age, gender, hobbies, health status, and past activity history through a means for managing user profile data and stores it in a database, which is then ready to generate appropriate responses based on the individual user profile.

[1006] Input: User profile data (age, gender, hobbies, health status, activity history, etc.)

[1007] Output: User profile data stored in a database

[1008] Specific operation: The server receives the profile information provided by the user via the input form or voice and performs the process of recording it in the database.

[1009] Step 2:

[1010] The user provides input data through the terminal by text or voice, which the terminal transmits to the server, for example, by inputting a question such as "What's the weather like today?"

[1011] Input: User input data (text or voice)

[1012] Output: User input data sent to the server

[1013] Specific operation: The terminal converts the text and voice data entered by the user into an appropriate format and sends it to the server via the network.

[1014] Step 3:

[1015] The server analyzes the received input data, compares it with the user profile data, and generates an appropriate response. For example, if the user asks, "What's the weather like today?", the server generates the response, "The weather is sunny today."

[1016] Input: User input data sent to the server, user profile data

[1017] Output: The generated response (e.g., "The weather is sunny today")

[1018] How it works: The server uses natural language processing algorithms to analyze the user's input data and uses generative AI models to create appropriate responses.

[1019] Step 4:

[1020] The terminal receives the response sent from the server and provides it to the user, so that the user can get an answer to their question.

[1021] Input: Response data sent from the server

[1022] Output: The response data that is provided to the user

[1023] Specific operation: The terminal displays or outputs the received response data in a format that is easy for the user to understand.

[1024] Step 5:

[1025] The device uses built-in sensors to collect real-time health data such as the user's heart rate, number of steps, and body temperature, and periodically transmits this data to a server.

[1026] Input: Health status data obtained from sensors (heart rate, steps, temperature, etc.)

[1027] Output: Health status data sent to the server

[1028] Specific operation: The terminal periodically collects data obtained from the sensors and transmits it to the server via the network.

[1029] Step 6:

[1030] The server analyzes the captured health data to detect abnormal patterns or emergencies, such as when a heart rate exceeds the normal range.

[1031] Input: Health status data sent from the device

[1032] Output: Anomaly detection flag, details of abnormality settings

[1033] Specific operation: The server analyzes the collected health data and executes an algorithm to determine abnormal conditions. If an abnormality is detected, it sets the necessary flag.

[1034] Step 7:

[1035] When the server detects an abnormality, it will send a notification to the user and designated emergency contacts to ensure the user's safety.

[1036] Input: Anomaly detection flag, details of abnormality settings

[1037] Output: Notification message (user and emergency contact)

[1038] Specific operation: When an anomaly is detected, the server sends a notification message to pre-registered contacts.

[1039] Step 8:

[1040] The server uses an emotion engine to recognize the user's emotions based on the user's input data and data obtained from sensors, for example, detecting stress from voice and text.

[1041] Input: User input data, health status data obtained from sensors

[1042] Output: Emotional state (e.g. "Stressed")

[1043] Specific operation: The server uses the emotion engine to analyze the user's input and sensor data to determine the emotional state.

[1044] Step 9:

[1045] The server then modifies the response it generates based on the emotion it recognizes. For example, if the server recognizes that the user is under stress, it will modify the response to something like, "Why don't you try listening to some relaxing music?"

[1046] Input: Emotional state

[1047] Output: Modified response data

[1048] Specific operation: The server uses the generative AI model to modify the response corresponding to the emotion and prepare it as a response to be provided to the user.

[1049] Step 10:

[1050] The server uses the emotion data recognized by the emotion engine as part of its analysis of health status and activity information and reflects this in the anomaly detection process, enabling more accurate anomaly detection.

[1051] Input: Emotion data, health status data

[1052] Output: Highly accurate anomaly detection results

[1053] Specific operation: The server adds emotion data to the anomaly detection algorithm and uses it to improve the accuracy of anomaly detection.

[1054] Step 11:

[1055] The server generates and provides appropriate activity guidance to the user based on the user's emotional state recognized by the emotion engine. For example, if the server recognizes that the user is depressed, it suggests relaxation activities.

[1056] Input: Emotional state

[1057] Output: Activity guide data

[1058] Specific operation: Based on the results of the emotion engine, the server generates activity guides and event suggestions for the user and sends them to the terminal.

[1059] Step 12:

[1060] The terminal displays the activity guide provided by the server to the user and prompts them to carry out the suggested activities. This step is important for improving the quality of the user's life and work.

[1061] Input: Activity guide data provided by the server

[1062] Output: Activity guide displayed to user

[1063] Specific operation: The terminal displays the activity guidance data received from the server on the user interface and provides guidance to the user by voice or text.

[1064] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1065] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1066] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1067] [Third embodiment]

[1068] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1069] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1070] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1071] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1072] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1073] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1074] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1075] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1076] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1077] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1078] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1079] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1080] This invention is an "anti-isolation AI" system that manages user profile data and input data and supports the safety and communication of elderly people. The system provides a series of functions, including data acquisition using sensors, dialogue support by AI agents, anomaly detection and notification, and activity guidance.

[1081] System configuration

[1082] 1. User profile data management (server)

[1083] The server manages profile data such as basic user information (age, gender, hobbies, health status) and past activity history.

[1084] 2. Data entry and transmission (terminal, user)

[1085] The user inputs text or voice through the device, which then sends it to the server. For example, if the user inputs "What's the weather like today?", this message is sent to the server.

[1086] 3. Generating and Providing Responses (Server, Terminal)

[1087] The server analyzes the received input data and generates an appropriate response to the user's question. The generated response is provided to the user through the terminal. For example, the server generates a response such as "Today's weather is sunny," and the terminal displays it to the user.

[1088] 4. Data acquisition by sensors (terminal)

[1089] The device uses built-in sensors to obtain real-time information about the user's health status (heart rate, steps, body temperature), and periodically transmits this data to a server.

[1090] 5. Anomaly detection and notification (server)

[1091] The server analyzes the health data sent and detects any abnormalities. For example, if the heart rate is outside the normal range, the server determines this to be an abnormality and sends a notification to the user and emergency contacts.

[1092] 6. Providing activity information (server, terminal)

[1093] The server suggests appropriate activities and events based on the user's profile data and interests, thereby facilitating social participation and interaction.

[1094] A natural language description of the program's operation

[1095] 1. Managing User Data

[1096] The server manages the user's profile data and records any updates made to it, for example, if a user takes up a new hobby, "gardening," the server records this.

[1097] 2. Sending input data and generating a response

[1098] The device sends the data entered by the user to the server, which analyzes it and generates a response. For example, if the user asks, "What's the weather like today?", the server responds, "It's sunny today," and sends it to the device.

[1099] 3. Sensor data acquisition and anomaly detection

[1100] The device monitors the user's health status and sends it to a server. The server analyzes the received data and notifies the user if an abnormality is detected. For example, if the user's heart rate is abnormally high, the server notifies an emergency contact.

[1101] 4. Providing information about activities

[1102] The server generates activity recommendations based on the user's interests and profile, for example, telling the user, "There's a gardening workshop being held at a nearby park."

[1103] The system of the present invention reduces the sense of isolation felt by elderly people and enables them to respond quickly to abnormal situations, allowing them to live with peace of mind.

[1104] The processing flow will be explained below.

[1105] Step 1:

[1106] The device starts up and displays a screen for the user to log in. The user enters their username and password on the login screen and taps the login button.

[1107] Step 2:

[1108] The device sends the login information to the server. The server verifies the received login information, and if authentication is successful, it sends the home screen data. The device then displays the home screen.

[1109] Step 3:

[1110] The user selects the "Chat" icon on the home screen to begin a conversation with the AI ​​agent, and then types "What's the weather like today?" into the input field.

[1111] Step 4:

[1112] The device receives the text data entered by the user and sends it to the server. The server analyzes the received input data and generates a response such as "Today's weather is sunny." The server then sends the generated response data to the device.

[1113] Step 5:

[1114] The device displays the received response data to the user, who sees the message "Today's weather is sunny."

[1115] Step 6:

[1116] The device uses built-in sensors to collect real-time data on the user's health, including heart rate, steps taken, and body temperature, and this data is periodically sent to a server.

[1117] Step 7:

[1118] The server analyzes the received health data and detects abnormal patterns or emergencies. For example, if the heart rate is outside the normal range, the server will detect an abnormality.

[1119] Step 8:

[1120] If the server detects an abnormality, it will notify the user and designated emergency contacts, who will be informed via email and SMS.

[1121] Step 9:

[1122] The user selects the "Activity Guide" icon and receives suggestions for categories and events that interest them. The server references the user's profile data and generates appropriate activity guides.

[1123] Step 10:

[1124] The server sends the generated activity guide to the terminal, which then displays the received activity guide to the user, encouraging them to participate in specific events or online courses.

[1125] Example 1

[1126] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1127] Communication support and health monitoring in daily life are important for reducing feelings of isolation and improving safety for the elderly. However, existing systems lack sufficient activity guidance based on the user's interests or prompt notification when an abnormality is detected, and an improved user experience is required. In addition, there is a lack of technology to generate more appropriate responses through voice input text conversion and natural language processing using generative AI models. A new system that solves these issues is needed.

[1128] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1129] In this invention, the server includes: means for managing user profile data; means for acquiring and transmitting user input data to the server; means for the server to generate an appropriate response based on the user profile data and input data; means for providing the generated response to the user; means for acquiring the user's health status and activity information using a sensor and transmitting it to the server; means for the server to analyze the acquired health status and activity information and detect abnormalities; means for notifying the user and emergency contacts when an abnormality is detected; means for a generative AI model with natural language processing capabilities to generate the generated response; and means for converting the user's input data from voice to text. This improves the safety and communication of elderly people. It also enables activity guidance based on the user's interests and rapid response when an abnormality is detected.

[1130] "User profile data" refers to data that includes basic information about the user (age, gender, hobbies, health status) and past activity history.

[1131] "Input data" refers to text and voice data that a user inputs through a terminal.

[1132] A "server" is a computer system that analyzes user profile data and input data and generates an appropriate response.

[1133] A "generative AI model" refers to an algorithm or machine learning model that has natural language processing capabilities and generates appropriate responses based on input data.

[1134] A "sensor" is a device that acquires a user's health status (heart rate, body temperature, number of steps, etc.) and activity information in real time.

[1135] "Abnormality detection" refers to the server analyzing acquired health status and activity information and determining abnormal conditions that exceed the normal range.

[1136] "Notification" refers to the act of sending an alert to the user and emergency contacts when an abnormality is detected.

[1137] "Activity Guides" are suggested activities and events based on a user's profile data and interests.

[1138] "Speech to text conversion" refers to the process of converting voice input data into text data.

[1139] "Natural language processing" refers to the technology that enables computers to understand and generate human language.

[1140] MODE FOR CARRYING OUT THE INVENTION

[1141] This invention is an "anti-isolation AI" system that supports the safety and communication of elderly people. The system manages user profile data and input data, and provides a series of functions such as health monitoring using sensors, dialogue support using generative AI models, anomaly detection and notification, and activity guidance.

[1142] The system configuration uses the following hardware and software:

[1143] User data management (server)

[1144] The server manages profile data such as basic user information (age, gender, hobbies, health status) and past activity history. This data is stored and managed appropriately using a database management system (DBMS), and any updates are recorded as appropriate.

[1145] Specific examples

[1146] If a user becomes interested in "gardening" as a new hobby, the server records this information in the database.

[1147] Data entry and transmission (terminal, user)

[1148] The user inputs a message through the device using text or voice. The input data is sent from the device to the server. If voice input is performed, the device converts this voice into text.

[1149] Specific examples

[1150] When a user asks "What's the weather like today?", the device converts this into text and sends it to the server.

[1151] Prompt Sentence Examples

[1152] Parse the text asking about today's weather and generate an appropriate response.

[1153] Response generation and delivery (server, terminal)

[1154] The server analyzes the data received from the user using the generative AI model and generates an appropriate response, which is then provided to the user via their device.

[1155] Specific examples

[1156] When a user asks, "What's the weather like today?", the generative AI model is used to analyze the question and generate a response such as "The weather is sunny today," which the device then notifies the user.

[1157] Sensor data acquisition (terminal)

[1158] The device uses built-in sensors to obtain real-time information about the user's health status (heart rate, body temperature, number of steps) and periodically transmits this data to a server.

[1159] Specific examples

[1160] The device measures the number of heartbeats per minute and sends this data to a server.

[1161] Anomaly detection and notification (server)

[1162] The server analyzes the health data and detects any abnormalities. If an abnormality is detected, a notification is sent to the user and their emergency contacts.

[1163] Specific examples

[1164] The server detects an abnormal heart rate and sends a notification to the user and emergency contacts saying, "Your heart rate is too high."

[1165] Providing activity information (server, terminal)

[1166] The server suggests appropriate activities and events based on the user's profile data and interests, thereby facilitating social participation and interaction.

[1167] Specific examples

[1168] Based on the user's profile data, the server recommends, "There's a gardening workshop being held in a nearby park."

[1169] The system of the present invention reduces the sense of isolation felt by the elderly, providing them with peace of mind and companionship in their daily lives. It also provides a safe environment by enabling rapid response to emergency situations.

[1170] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1171] Program processing flow

[1172] Step 1: Managing User Profile Data (Server)

[1173] The server stores profile data such as basic user information (age, gender, hobbies, health status) and past activity history in a database. When a user registers or updates their profile data, it manages this data and records the changes.

[1174] input

[1175] User basic information (age, gender, hobbies, health condition)

[1176] process

[1177] The server uses a database management system (DBMS) to properly store and manage user information.

[1178] output

[1179] A database with updated user profile data

[1180] Specific actions

[1181] The server receives the new user's registration information and stores it in a database.

[1182] When a user adds a new hobby (e.g. gardening), the server records this change in the database.

[1183] Step 2: Data entry and transmission (terminal, user)

[1184] The user inputs text or voice through the device, which processes the input data and sends it to the server. If voice input is used, the device converts the voice into text.

[1185] input

[1186] User voice or text input

[1187] process

[1188] The device converts the voice input into text and sends this data to the server.

[1189] output

[1190] Textual input data sent to the server

[1191] Specific actions

[1192] The user speaks, "What's the weather like today?"

[1193] The device converts the voice into text and sends the text data "What's the weather like today?" to the server.

[1194] Step 3: Generate and serve a response (server, terminal)

[1195] The server analyzes the data received from the user using the generative AI model and generates an appropriate response, which is then provided to the user via their device.

[1196] input

[1197] Text input data sent by the user

[1198] process

[1199] The server uses a generative AI model to analyze the input data and generate an appropriate response.

[1200] output

[1201] Generated response text

[1202] Specific actions

[1203] The server parses the question "What's the weather today?" and generates the response "The weather is sunny today."

[1204] The device displays or plays this response to the user.

[1205] Step 4: Acquiring sensor data (device)

[1206] The device uses built-in sensors to obtain the user's health status (heart rate, body temperature, number of steps) in real time and periodically transmits this data to a server.

[1207] input

[1208] Health status data acquisition using sensors

[1209] process

[1210] The health data collected by the device is periodically sent to a server.

[1211] output

[1212] Health status data sent to the server

[1213] Specific actions

[1214] The device measures the user's heart rate every minute and sends this data to a server.

[1215] Step 5: Anomaly detection and notification (server)

[1216] The server analyzes the health data and detects any abnormalities. If an abnormality is detected, a notification is sent to the user and their emergency contacts.

[1217] input

[1218] Health data sent from the device

[1219] process

[1220] The server analyzes health data and detects abnormalities that exceed the normal range.

[1221] output

[1222] Anomaly detection notification message

[1223] Specific actions

[1224] The server detects abnormal heart rate and sends a notification to the user and emergency contacts saying, "Your heart rate is too high."

[1225] Step 6: Providing activity information (server, terminal)

[1226] The server suggests appropriate activities and events based on the user's profile data and interests, thereby facilitating social participation and interaction.

[1227] input

[1228] User profile data and interest data stored on the server

[1229] process

[1230] The server searches for and generates appropriate activities and events based on the user's interests.

[1231] output

[1232] Proposed activities and event information

[1233] Specific actions

[1234] Based on the user's interest data, the server recommends, "There's a gardening workshop being held in a nearby park."

[1235] The device will notify the user of this information.

[1236] Through the above processing steps, the system of the present invention improves safety and communication for the elderly. It also enables activity guidance based on the user's interests and quick response when an abnormality is detected.

[1237] (Application example 1)

[1238] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1239] The problems of elderly isolation and lack of health monitoring are serious issues. Elderly operators working in factories and other facilities require real-time monitoring of their health status while ensuring work safety and efficiency, but current systems are unable to adequately address this. Therefore, a system is needed that effectively supports the safety and communication of elderly operators and enables rapid response in the event of an emergency.

[1240] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1241] In this invention, the server includes: means for managing user profile data; means for acquiring and transmitting user input data to the server; means for the server to generate an appropriate response based on the user profile data and input data; means for providing the generated response to the user; means for acquiring the user's health condition and activity information using a sensor and transmitting it to the server; means for the server to analyze the acquired health condition and activity information and detect abnormalities; means for notifying the user and emergency contacts when an abnormality is detected; and dialogue support means using an industrial robot equipped with an AI agent to support elderly operators in factories. This enables real-time monitoring of the health condition of elderly operators and rapid response to abnormalities while ensuring their safety and work efficiency.

[1242] "User profile data" refers to the user's basic information (age, gender, hobbies, health status) and past activity history.

[1243] "Input Data" refers to information such as messages or questions entered by the user via text or voice.

[1244] "Server" refers to a computer system for processing user profile data and input data and generating an appropriate response.

[1245] "Generated response" refers to an answer or guidance generated by the server based on user input data.

[1246] "Sensor" refers to a device that acquires a user's health status (heart rate, body temperature, number of steps, etc.) and activity information in real time.

[1247] "Analysis" refers to the process of analyzing information based on acquired data and detecting anomalies and patterns.

[1248] "Anomaly detection" refers to detecting values ​​or trends that exceed the normal range through analysis results.

[1249] "Emergency contacts" refers to contact information for the user's family, medical institutions, etc. who will be notified when an abnormality is detected.

[1250] An "AI agent" refers to software that uses artificial intelligence to interact with users and provide appropriate responses and guidance.

[1251] An "industrial robot" refers to an automated mechanical device used in production sites such as factories.

[1252] "Dialogue support" refers to supporting communication between elderly operators and industrial robots.

[1253] "Activity Guide" refers to suggested activities and events based on a user's interests and profile.

[1254] "Cloud" refers to computing resources provided over the Internet.

[1255] "Real-time" refers to the immediacy and processing and provision of information with almost no delay.

[1256] The present invention relates to an "elderly operator support system" that ensures the safety and work efficiency of elderly operators while enabling real-time monitoring of their health status and prompt response in the event of an abnormality. Specific embodiments are described below.

[1257] System configuration

[1258] 1. User profile data management (server)

[1259] The server manages profile data such as basic information (age, gender, hobbies, health status) of the elderly operator users and their past work history. For example, if a new task or skill is added, the server updates and records it.

[1260] 2. Data entry and transmission (terminal, user)

[1261] The user inputs different types of data (text and voice) through a tablet or voice input device and sends this to the server, for example, asking "What do I do next?"

[1262] 3. Generating and Providing Responses (Server, Terminal)

[1263] The server analyzes the received input data and generates an appropriate response to the user's question. The generated response is provided to the user via a tablet or voice device. For example, the server generates a response such as "Next, we will inspect the part" and displays it on the terminal.

[1264] 4. Data acquisition by sensors (terminal)

[1265] The terminal uses sensors built into the wearable device to obtain real-time information on the elderly operator's health, such as heart rate, body temperature, and number of steps taken, and this data is periodically sent to a server.

[1266] 5. Anomaly detection and notification (server)

[1267] The server analyzes the health data and detects any abnormalities. For example, if the heart rate exceeds the normal range, the server determines this to be an abnormality and sends a notification to the factory manager and emergency contact.

[1268] 6. Providing activity information (server, terminal)

[1269] The server suggests the next task and efficient work methods based on the elderly operator's profile data and past work history, thereby improving the user's work efficiency.

[1270] A natural language description of the program's operation

[1271] 1. Managing User Data

[1272] The server manages basic information and past work history of elderly operators and records any updates. For example, if a new skill is added, the server adds it to the profile data.

[1273] 2. Sending input data and generating a response

[1274] The terminal sends the data entered by the user to the server, which analyzes it and generates an appropriate response. For example, if the user asks, "What's next?", the server generates the response, "Next is to inspect the part," and sends it to the terminal.

[1275] 3. Sensor data acquisition and anomaly detection

[1276] The device monitors the health status of the elderly operator and sends the information to a server. The server analyzes the received data and notifies the factory manager and emergency contacts if an abnormality is detected. For example, if the user's heart rate is abnormally high, the server notifies the factory manager and emergency contacts.

[1277] 4. Providing information about activities

[1278] The server generates activity guides based on the interests and profile of the elderly operator, for example, providing the user with a guide such as, "Next is a parts inspection, followed by machine maintenance."

[1279] Specific Examples

[1280] Examples:

[1281] If an elderly operator working at a precision manufacturing factory experiences an abnormally high temperature while inspecting a product, the factory manager and emergency contacts will be automatically notified. The operator can also ask the AI ​​assistant, "What should I do next?" to confirm the next steps.

[1282] Example prompts to input to a generative AI model:

[1283] "If an elderly operator working in a manufacturing plant feels unwell during the night shift, write a program on how an AI assistant can assist in this situation and notify the manager."

[1284] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1285] Step 1:

[1286] A user inputs profile data into a terminal. For example, basic information such as age, gender, hobbies, and health status is input. This input data is stored in a database and sent to a server. The input data is processed to generate profile data, which is then registered on the server.

[1287] Step 2:

[1288] The user enters a question or command through the device, for example, "What do I do next?" using text or voice input. The device sends this to the server, which processes the input data, analysing the text or voice data and converting it into an appropriate format.

[1289] Step 3:

[1290] The server analyzes the received input data and generates an appropriate response. This analysis is performed using a generative AI model that includes natural language processing. For example, in response to the input query "What task will be performed next?", a response such as "Next is the inspection of the parts" is generated. Data analysis organizes the information and generates response data.

[1291] Step 4:

[1292] The generated response data is sent from the server to the terminal and provided to the user. For example, a text response is displayed on the tablet screen or read aloud. An output based on the server's response data is generated and displayed on the terminal.

[1293] Step 5:

[1294] The terminal uses sensors built into the wearable device to acquire the user's health data (heart rate, body temperature, number of steps, etc.) in real time. The acquired data is periodically sent to a server. The real-time health data is generated and transmitted based on the data acquired by the sensors.

[1295] Step 6:

[1296] The server analyzes the acquired health data and detects any abnormalities. For example, if the heart rate is outside the normal range, the server determines this as an abnormality. Anomaly detection based on data analysis determines whether or not there is an abnormality.

[1297] Step 7:

[1298] If an abnormality is detected, the server sends a notification to the user and emergency contacts. For example, if the heart rate is abnormally high, the server notifies the factory manager and emergency contacts. The notification function enables a prompt response when an abnormality is detected.

[1299] Step 8:

[1300] The server suggests the next task and the most efficient way to work based on the user's profile data and past work history. For example, it provides the user with guidance such as, "Next is the parts inspection, followed by machine maintenance." Data analysis and suggestion functions aim to improve work efficiency.

[1301] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1302] This invention combines an emotion engine with an "anti-isolation AI" system that supports the safety and communication of elderly people. The system provides functions such as data acquisition using sensors, dialogue support by an AI agent, anomaly detection and notification, activity guidance, and an emotion engine that recognizes user emotions.

[1303] System configuration

[1304] 1. User profile data management (server)

[1305] The server manages profile data such as basic user information (age, gender, hobbies, health status) and past activity history.

[1306] 2. Data entry and transmission (terminal, user)

[1307] The user inputs text or voice through the device, which then sends it to the server. For example, if the user inputs "What's the weather like today?", this message is sent to the server.

[1308] 3. Generating and Providing Responses (Server, Terminal)

[1309] The server analyzes the received input data and generates an appropriate response to the user's question. The generated response is provided to the user through the terminal. For example, the server generates a response such as "Today's weather is sunny," and the terminal displays it to the user.

[1310] 4. Data acquisition by sensors (terminal)

[1311] The device uses built-in sensors to collect real-time data on the user's health, including heart rate, steps taken, and body temperature, and this data is periodically sent to a server.

[1312] 5. Anomaly detection and notification (server)

[1313] The server analyzes the health data and detects abnormal patterns or emergencies. For example, if the heart rate is outside the normal range, the server will detect the abnormality. When the server detects an abnormality, it will send a notification to the user and their designated emergency contacts.

[1314] 6. Emotion Recognition by Emotion Engine (Server)

[1315] The server uses an emotion engine to recognize the user's emotions based on the user's input data and data acquired from the sensors. For example, the emotion engine analyzes the user's voice and text and detects "stress."

[1316] 7. Emotion-based response modification (server, terminal)

[1317] The server then modifies the response it generates based on the user's emotions as recognized by the emotion engine. For example, if the server detects that the user is under stress, it generates a response such as, "Why don't you try listening to some relaxing music?"

[1318] 8. Use in Emotion Data Analysis (Server)

[1319] The server also uses the emotion data recognized by the emotion engine as part of its analysis of health status and activity information. This data is also reflected in the anomaly detection process, enabling more accurate anomaly detection.

[1320] 9. Emotion-based activity guidance (server, terminal)

[1321] The server generates appropriate activity recommendations for the user based on the user's emotional data recognized by the emotion engine. For example, if the user is recognized as "depressed," the server will suggest that the user participate in relaxation activities or hobbies.

[1322] A natural language description of the program's operation

[1323] 1. Managing User Data

[1324] The server manages the user's profile data and records any updates made to it, for example, if a user takes up a new hobby, "gardening," the server records this.

[1325] 2. Sending input data and generating a response

[1326] The device sends the data entered by the user to the server, which analyzes it and generates a response. For example, if the user asks, "What's the weather like today?", the server responds, "It's sunny today," and sends it to the device.

[1327] 3. Sensor data acquisition and anomaly detection

[1328] The device monitors the user's health status and sends it to a server. The server analyzes the received data and notifies the user if an abnormality is detected. For example, if the user's heart rate is abnormally high, the server notifies an emergency contact.

[1329] 4. Emotional Data Recognition and Response Modification

[1330] The server analyzes the user's input data and sensor data using an emotion engine to recognize the user's emotions. For example, if the user is under stress, the server will modify the response and provide it via the device, suggesting, "Why not try listening to some relaxing music?"

[1331] 5. Use in Emotion Data Analysis

[1332] The server uses the emotional data recognized by the emotion engine to analyze the user's health status and reflects this in the anomaly detection process. For example, if a user is depressed over a long period of time, it can take action such as suggesting early consultation with a doctor or counselor.

[1333] 6. Emotion-based activity guidance

[1334] The server generates appropriate activity recommendations based on the user's emotional state. For example, a "depressed" user might be provided with relaxation activities to encourage social interaction.

[1335] By incorporating an emotion engine, the system of the present invention can flexibly respond to the user's emotional state, reduce the elderly's sense of isolation, and provide support for them to live with peace of mind.

[1336] The processing flow will be explained below.

[1337] Step 1:

[1338] The device starts up and displays a screen for the user to log in. The user enters their username and password on the login screen and taps the login button.

[1339] Step 2:

[1340] The device sends the login information to the server. The server verifies the received login information, and if authentication is successful, it sends the home screen data. The device then displays the home screen.

[1341] Step 3:

[1342] The user selects the "Chat" icon on the home screen to begin a conversation with the AI ​​agent, and then types "What's the weather like today?" into the input field.

[1343] Step 4:

[1344] The device receives the text data entered by the user and sends it to the server. The server analyzes the received input data and generates a response such as "Today's weather is sunny." The server then sends the generated response data to the device.

[1345] Step 5:

[1346] The device displays the received response data to the user, who sees the message "Today's weather is sunny."

[1347] Step 6:

[1348] The device uses built-in sensors to collect real-time data on the user's health, including heart rate, steps taken, and body temperature, and this data is periodically sent to a server.

[1349] Step 7:

[1350] The server analyzes the received health data and detects abnormal patterns or emergencies. For example, if the heart rate is outside the normal range, the server will detect an abnormality.

[1351] Step 8:

[1352] If the server detects an abnormality, it will notify the user and designated emergency contacts, who will be informed via email and SMS.

[1353] Step 9:

[1354] The server uses an emotion engine to analyze user input data and sensor data to recognize the user's emotions. For example, it can detect "anxiety" from the text and voice input of the user.

[1355] Step 10:

[1356] The server then modifies the response appropriately based on the user's emotions as determined by the emotion engine. For example, if the server determines that the user is feeling anxious, it generates a response suggesting, "Why not try listening to some relaxing music?"

[1357] Step 11:

[1358] The device displays the modified response to the user, who sees the message, "Why not try listening to some relaxing music?"

[1359] Step 12:

[1360] The server also uses the emotional data recognized by the emotion engine to analyze health status and activity information. For example, if a user has been feeling depressed for a long period of time, that data will be reflected in the analysis.

[1361] Step 13:

[1362] The server generates appropriate activity guides based on the emotion data recognized by the emotion engine, suggesting activities, events, relaxation methods, etc. according to the user's emotional state.

[1363] Step 14:

[1364] The device displays the generated activity guide to the user. For example, if the user is feeling "down," the device provides a guide such as "Why don't you join a gardening event at a nearby park?"

[1365] Example 2

[1366] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1367] There is a need to reduce the sense of isolation felt by the elderly and provide an environment where they can live safely while maintaining social connections. In particular, there is a lack of systems that can monitor their health and emotional state in real time and provide appropriate responses accordingly. Furthermore, there is a challenge in providing more accurate anomaly detection and activity guidance that takes emotional state into account.

[1368] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for managing user profile data, means for acquiring and analyzing user input data and generating an appropriate response, means for acquiring the user's health condition and activity information and detecting abnormalities, means for recognizing emotions based on the user input data and data acquired from the sensor, means for modifying responses based on the recognized emotions, means for analyzing the emotion data and reflecting it in the anomaly detection process, and means for generating appropriate activity guidance based on the emotion data and providing it to the user. This makes it possible to comprehensively monitor the health condition and emotional state and provide appropriate responses and guidance, allowing elderly people to live with peace of mind and reducing their sense of isolation.

[1369] "User Profile Data" refers to basic information such as age, gender, hobbies, health status, and past activity history.

[1370] "Server" refers to a computer system that processes data received from users, manages profile data, generates responses, detects anomalies, etc.

[1371] "Terminal" refers to a device that allows a user to manipulate input data and obtain health and activity information through sensors.

[1372] "Input data" refers to text and voice data provided by the user through the terminal.

[1373] "Generated response" refers to a reply or suggestion to the user that the server generates by analyzing the input data.

[1374] "Sensors" refer to devices that measure a user's health status, such as heart rate, steps, and body temperature, in real time.

[1375] "Health status and activity information" refers to data on the user's physical condition and behavior obtained through sensors.

[1376] "Anomaly detection" refers to the process by which the server analyzes health and activity information to discover unusual patterns or emergencies.

[1377] "Emotion engine" refers to an algorithm or program that analyzes user input data and sensor data to recognize emotions.

[1378] "Emotional Data" refers to information about a user's emotional state as recognized by the Emotion Engine.

[1379] "Activity guidance" refers to information about suggested activities based on a user's interests and emotional state.

[1380] "Emergency Contact" means a person or entity designated to receive notification when an anomaly is detected.

[1381] MODE FOR CARRYING OUT THE INVENTION

[1382] This invention is a system for supporting the safety and communication of the elderly, and it manages and analyzes user profile data, health data, and emotion data in an integrated manner. This system includes a server, terminals, sensors, emotion engine, etc., which work together to support the lives of the elderly.

[1383] System configuration

[1384] The system includes the following main components:

[1385] 1. Server

[1386] Profile data management: Store user basic information (age, gender, hobbies, health status, and past activity history) in a database and update it as needed.

[1387] Response generation: Based on the input data received from the user, a generative AI model is used to generate an appropriate response.

[1388] Anomaly detection: Analyzes health status and activity information sent from sensors to detect abnormalities.

[1389] Emotion Recognition: Recognize emotions from user input data and sensor data using an emotion engine.

[1390] Response Modification: Modify the response based on the recognized emotion data and provide it to the user.

[1391] 2. Terminal

[1392] Data Entry: Allows users to enter text or voice data, which is then sent to the server.

[1393] Sensor data acquisition: The built-in sensors are used to acquire the user's health data, such as heart rate, steps, and body temperature, in real time and send it to the server.

[1394] 3. Sensors

[1395] Health monitoring: Measures the user's heart rate, steps, temperature, etc.

[1396] 4. Emotion Engine

[1397] Sentiment analysis: Recognizing user emotions based on their voice, text, and health data.

[1398] System operation example

[1399] A concrete example of the system in action is as follows:

[1400] 1. Entering and submitting user data

[1401] User: For example, type "What's the weather like today?" into the device.

[1402] Terminal: Sends the entered data to the server.

[1403] 2. Generating and Displaying the Response

[1404] Server: Analyzes the input data using a generative AI model and generates a response such as "Today's weather is sunny."

[1405] Terminal: Displays the generated response to the user.

[1406] 3. Health data acquisition and anomaly detection

[1407] Sensor: Monitors the user's heart rate and sends the data to the server via the device.

[1408] Server: Analyzes the transmitted data and sends a notification to emergency contacts if the heart rate is abnormally high.

[1409] 4. Emotional Data Recognition and Response Modification

[1410] Server: Using the emotion engine, recognize emotions from user input data and sensor data. For example, if the input text is "tired," it detects "stress."

[1411] Server: Based on the recognized emotion, the server modifies the response to "Why not try listening to some relaxing music?" and provides it through the device.

[1412] Prompt Sentence Examples

[1413] Here are some example prompts to input to the generative AI model:

[1414] Answering questions

[1415] Prompt text: "The user types 'What's the weather today?' How should the server respond?"

[1416] Example response generated: "The weather is sunny today."

[1417] Emotion Recognition and Response Modification

[1418] Prompt: "By analyzing the user's text or voice data, how can the server recognize the user's emotions and generate a response based on them?"

[1419] Example generated response: "We've detected stress in your voice. Would you like to try listening to some relaxing music?"

[1420] This system can comprehensively monitor the user's health and emotional state, and generate appropriate responses and activity guidance based on that information, thereby providing support that allows elderly people to live with peace of mind.

[1421] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1422] Step 1:

[1423] Managing your profile data

[1424] Input: Basic information entered by the user when registering (age, gender, hobbies, health status, and past activity history)

[1425] What it does: The server receives input data from the user, stores it in a database, and updates existing data when the user provides new information.

[1426] Data Processing: The server merges the new information with the existing profile data to maintain consistency.

[1427] Output: Updated profile data is saved to the database.

[1428] Step 2:

[1429] Entering and Submitting Data

[1430] Input: The user uses the device to input text or voice data.

[1431] What happens: The user types a question, such as "What's the weather like today?"

[1432] Data processing: The device converts the text or voice data into a digital format and sends it to the server.

[1433] Output: The transformed input data is sent to the server.

[1434] Step 3:

[1435] Generating and serving the response

[1436] Input: User input data received by the server

[1437] Specific operation: The server uses a generative AI model to analyze the input data.

[1438] Data processing: Analyzes input data and generates appropriate responses.

[1439] Output: The generated response is sent to the terminal and displayed to the user. Example: "The weather is sunny today."

[1440] Step 4:

[1441] Acquiring Sensor Data

[1442] Input: Real-time data such as user heart rate, steps, and body temperature

[1443] How it works: Sensors built into the device measure these data.

[1444] Data processing: The acquired data is periodically sent to the server.

[1445] Output: The data acquired by the sensor is sent to the server.

[1446] Step 5:

[1447] Anomaly detection and notification

[1448] Input: Sensor data received by the server

[1449] Specific operation: The server analyzes the sensor data and detects abnormalities, such as when the heart rate exceeds the normal range.

[1450] Data processing: Analyze the data using anomaly detection algorithms.

[1451] Output: If an anomaly is detected, a notification is sent to the user and emergency contacts.

[1452] Step 6:

[1453] Emotion recognition by emotion engine

[1454] Input: User input and sensor data

[1455] Specific operation: The server uses an emotion engine to analyze this data and recognize the user's emotions.

[1456] Data processing: The emotion engine identifies the user's emotional state as a result of the analysis.

[1457] Output: Recognized emotion data is generated. Example: "I feel stressed."

[1458] Step 7:

[1459] Emotion-Based Response Modification

[1460] Input: Emotion data generated by the emotion engine

[1461] Specific behavior: The server modifies the generated response based on the emotion data.

[1462] Data processing: Regenerate the response content and modify it to correspond to the emotion.

[1463] Output: The modified response is sent to the terminal and provided to the user. Example: "Why not try listening to some relaxing music?"

[1464] Step 8:

[1465] Use in analyzing emotion data

[1466] Input: Emotion data recognized by the emotion engine

[1467] Specific operation: The server also reflects the emotion data in the anomaly detection process.

[1468] Data processing: Integrating emotion data into health analysis parameters.

[1469] Output: Consolidated analytical data is generated.

[1470] Step 9:

[1471] Emotion-based activity guidance

[1472] Input: Emotion data recognized by the emotion engine

[1473] Specific operation: The server generates appropriate activity guidance for the user based on the emotion data.

[1474] Data processing: Generate activities that match the emotional state.

[1475] Output: The generated activity guide is sent to the terminal and provided to the user. Example: "Try participating in a relaxation activity."

[1476] Through these processing steps, the system monitors the health and emotional state of elderly people in real time, and provides appropriate responses and activity guidance based on that information, thereby supporting an environment in which they can live with peace of mind.

[1477] (Application example 2)

[1478] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1479] While safety and health management for elderly people and factory workers is important, existing systems do not adequately monitor their health and emotional states in real time. Furthermore, there is a lack of systems that can quickly detect abnormalities and take appropriate action. Therefore, there is a need for a system that can respond promptly when an abnormality occurs.

[1480] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for managing user profile data; means for acquiring and transmitting user input data to the server; means for the server to generate an appropriate response based on the user profile data and input data; means for providing the generated response to the user; means for acquiring and transmitting user health and activity information using a sensor; means for the server to analyze the acquired health and activity information and detect abnormalities; means for notifying the user and emergency contacts when an abnormality is detected; means for recognizing the user's emotional state using an emotion engine; means for appropriately modifying the generated response based on the emotional state; means for generating and providing activity guidance based on the emotional state; means for monitoring the health and emotional states of factory workers in real time; and means for notifying workers and managers when an abnormality is detected. This makes it possible to monitor the health and emotional states of elderly people and factory workers in real time, quickly detect abnormalities, and take appropriate action.

[1481] "User profile data" refers to information such as the user's age, gender, hobbies, health status, and past activity history.

[1482] "Input Data" means information entered by a User through text or voice that is transmitted to the Server.

[1483] "Server" means a central computer that analyzes user input and profile data and generates and provides appropriate responses.

[1484] A "sensor" is a device that acquires a user's health status (heart rate, body temperature, etc.) and activity information (number of steps, etc.) in real time.

[1485] An "anomaly detection method" is a system that has the ability to analyze acquired health and activity information and recognize unusual patterns or emergency situations.

[1486] The "emotion engine" is an algorithm that analyzes the user's voice and text input, as well as sensor data, to recognize the user's emotional state.

[1487] The "means for appropriately modifying a response" is a system that has the function of adjusting the generated response based on the user's emotional state recognized by the emotion engine.

[1488] "Activity Guide" refers to suggested activities and events based on a user's interests and emotional state.

[1489] "Real-time monitoring means" refers to a system for monitoring and collecting data on a user's health and emotional state in real time.

[1490] "Means for notification" means a function for promptly notifying the user and emergency contacts of detected abnormalities.

[1491] This invention combines an "anti-isolation AI" system with an emotion engine to realize safety and health management for the elderly and factory workers. This system uses sensors to monitor health conditions, an AI agent to conduct dialogue, and the emotion engine recognizes emotions and generates appropriate responses.

[1492] System configuration

[1493] 1. User profile data management (server)

[1494] The server manages profile data including the user's age, gender, hobbies, health status, past activity history, etc. This data is used to respond to the user's individual needs.

[1495] 2. Data entry and transmission (terminal, user)

[1496] The user inputs text or voice through the device, which then sends it to the server. For example, if the user inputs "What's the weather like today?", this message is sent to the server.

[1497] 3. Generating and Providing Responses (Server, Terminal)

[1498] The server analyzes the received input data and generates an appropriate response to the user's question. The generated response is provided to the user through the terminal. For example, the server generates a response such as "Today's weather is sunny," and the terminal displays it to the user.

[1499] 4. Data acquisition by sensors (terminal)

[1500] The device uses built-in sensors to collect real-time data on the user's health, including heart rate, steps taken, and body temperature, and this data is periodically sent to a server.

[1501] 5. Anomaly detection and notification (server)

[1502] The server analyzes the health data and detects abnormal patterns or emergencies. For example, if the heart rate is outside the normal range, the server will detect the abnormality. When the server detects an abnormality, it will send a notification to the user and their designated emergency contacts.

[1503] 6. Emotion Recognition by Emotion Engine (Server)

[1504] The server uses an emotion engine to recognize the user's emotions based on the user's input data and data acquired from the sensors. For example, the emotion engine analyzes the user's voice and text and detects "stress."

[1505] 7. Emotion-based response modification (server, terminal)

[1506] The server then modifies the response it generates based on the user's emotions as recognized by the emotion engine. For example, if the server detects that the user is under stress, it generates a response such as, "Why don't you try listening to some relaxing music?"

[1507] 8. Use in Emotion Data Analysis (Server)

[1508] The server also uses the emotion data recognized by the emotion engine as part of its analysis of health status and activity information. This data is also reflected in the anomaly detection process, enabling more accurate anomaly detection.

[1509] 9. Emotion-based activity guidance (server, terminal)

[1510] The server generates appropriate activity recommendations for the user based on the user's emotional data recognized by the emotion engine. For example, if the user is recognized as "depressed," the server will suggest that the user participate in relaxation activities or hobbies.

[1511] 10. Health management and mental support for factory workers (servers, terminals)

[1512] The system monitors the health and emotional state of factory workers in real time and notifies the workers and their managers if an abnormality is detected. For example, if a worker's heart rate is abnormally high, the server will notify the manager and suggest that the worker take a break.

[1513] Examples of concrete examples and prompts

[1514] As a concrete example, the following is an example of a prompt sentence to be input to a generative AI model:

[1515] prompt:

[1516] "To teach the emotion analysis engine the difference between stress and relaxation, consider the following situations:"

[1517] Situation 1:

[1518] "If the user's heart rate exceeds 90:"

[1519] Response 1:

[1520] "Stress detected. We'll give you some relaxation suggestions."

[1521] Situation 2:

[1522] If the user's heart rate is within the normal range:

[1523] Response 2:

[1524] "Users are relaxed. Keep it up."

[1525] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1526] Step 1:

[1527] The server collects profile data such as the user's age, gender, hobbies, health status, and past activity history through a means for managing user profile data and stores it in a database, which is then ready to generate appropriate responses based on the individual user profile.

[1528] Input: User profile data (age, gender, hobbies, health status, activity history, etc.)

[1529] Output: User profile data stored in a database

[1530] Specific operation: The server receives the profile information provided by the user via the input form or voice and performs the process of recording it in the database.

[1531] Step 2:

[1532] The user provides input data through the terminal by text or voice, which the terminal transmits to the server, for example, by inputting a question such as "What's the weather like today?"

[1533] Input: User input data (text or voice)

[1534] Output: User input data sent to the server

[1535] Specific operation: The terminal converts the text and voice data entered by the user into an appropriate format and sends it to the server via the network.

[1536] Step 3:

[1537] The server analyzes the received input data, compares it with the user profile data, and generates an appropriate response. For example, if the user asks, "What's the weather like today?", the server generates the response, "The weather is sunny today."

[1538] Input: User input data sent to the server, user profile data

[1539] Output: The generated response (e.g., "The weather is sunny today")

[1540] How it works: The server uses natural language processing algorithms to analyze the user's input data and uses generative AI models to create appropriate responses.

[1541] Step 4:

[1542] The terminal receives the response sent from the server and provides it to the user, so that the user can get an answer to their question.

[1543] Input: Response data sent from the server

[1544] Output: The response data that is provided to the user

[1545] Specific operation: The terminal displays or outputs the received response data in a format that is easy for the user to understand.

[1546] Step 5:

[1547] The device uses built-in sensors to collect real-time health data such as the user's heart rate, number of steps, and body temperature, and periodically transmits this data to a server.

[1548] Input: Health status data obtained from sensors (heart rate, steps, temperature, etc.)

[1549] Output: Health status data sent to the server

[1550] Specific operation: The terminal periodically collects data obtained from the sensors and transmits it to the server via the network.

[1551] Step 6:

[1552] The server analyzes the captured health data to detect abnormal patterns or emergencies, such as when a heart rate exceeds the normal range.

[1553] Input: Health status data sent from the device

[1554] Output: Anomaly detection flag, details of abnormality settings

[1555] Specific operation: The server analyzes the collected health data and executes an algorithm to determine abnormal conditions. If an abnormality is detected, it sets the necessary flag.

[1556] Step 7:

[1557] When the server detects an abnormality, it will send a notification to the user and designated emergency contacts to ensure the user's safety.

[1558] Input: Anomaly detection flag, details of abnormality settings

[1559] Output: Notification message (user and emergency contact)

[1560] Specific operation: When an anomaly is detected, the server sends a notification message to pre-registered contacts.

[1561] Step 8:

[1562] The server uses an emotion engine to recognize the user's emotions based on the user's input data and data obtained from sensors, for example, detecting stress from voice and text.

[1563] Input: User input data, health status data obtained from sensors

[1564] Output: Emotional state (e.g. "Stressed")

[1565] Specific operation: The server uses the emotion engine to analyze the user's input and sensor data to determine the emotional state.

[1566] Step 9:

[1567] The server then modifies the response it generates based on the emotion it recognizes. For example, if the server recognizes that the user is under stress, it will modify the response to something like, "Why don't you try listening to some relaxing music?"

[1568] Input: Emotional state

[1569] Output: Modified response data

[1570] Specific operation: The server uses the generative AI model to modify the response corresponding to the emotion and prepare it as a response to be provided to the user.

[1571] Step 10:

[1572] The server uses the emotion data recognized by the emotion engine as part of its analysis of health status and activity information and reflects this in the anomaly detection process, enabling more accurate anomaly detection.

[1573] Input: Emotion data, health status data

[1574] Output: Highly accurate anomaly detection results

[1575] Specific operation: The server adds emotion data to the anomaly detection algorithm and uses it to improve the accuracy of anomaly detection.

[1576] Step 11:

[1577] The server generates and provides appropriate activity guidance to the user based on the user's emotional state recognized by the emotion engine. For example, if the server recognizes that the user is depressed, it suggests relaxation activities.

[1578] Input: Emotional state

[1579] Output: Activity guide data

[1580] Specific operation: Based on the results of the emotion engine, the server generates activity guides and event suggestions for the user and sends them to the terminal.

[1581] Step 12:

[1582] The terminal displays the activity guide provided by the server to the user and prompts them to carry out the suggested activities. This step is important for improving the quality of the user's life and work.

[1583] Input: Activity guide data provided by the server

[1584] Output: Activity guide displayed to user

[1585] Specific operation: The terminal displays the activity guidance data received from the server on the user interface and provides guidance to the user by voice or text.

[1586] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1587] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1588] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1589] [Fourth embodiment]

[1590] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1591] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1592] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1593] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1594] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1595] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1596] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1597] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1598] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1599] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1600] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1601] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1602] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1603] This invention is an "anti-isolation AI" system that manages user profile data and input data and supports the safety and communication of elderly people. The system provides a series of functions, including data acquisition using sensors, dialogue support by AI agents, anomaly detection and notification, and activity guidance.

[1604] System configuration

[1605] 1. User profile data management (server)

[1606] The server manages profile data such as basic user information (age, gender, hobbies, health status) and past activity history.

[1607] 2. Data entry and transmission (terminal, user)

[1608] The user inputs text or voice through the device, which then sends it to the server. For example, if the user inputs "What's the weather like today?", this message is sent to the server.

[1609] 3. Generating and Providing Responses (Server, Terminal)

[1610] The server analyzes the received input data and generates an appropriate response to the user's question. The generated response is provided to the user through the terminal. For example, the server generates a response such as "Today's weather is sunny," and the terminal displays it to the user.

[1611] 4. Data acquisition by sensors (terminal)

[1612] The device uses built-in sensors to obtain real-time information about the user's health status (heart rate, steps, body temperature), and periodically transmits this data to a server.

[1613] 5. Anomaly detection and notification (server)

[1614] The server analyzes the health data sent and detects any abnormalities. For example, if the heart rate is outside the normal range, the server determines this to be an abnormality and sends a notification to the user and emergency contacts.

[1615] 6. Providing activity information (server, terminal)

[1616] The server suggests appropriate activities and events based on the user's profile data and interests, thereby facilitating social participation and interaction.

[1617] A natural language description of the program's operation

[1618] 1. Managing User Data

[1619] The server manages the user's profile data and records any updates made to it, for example, if a user takes up a new hobby, "gardening," the server records this.

[1620] 2. Sending input data and generating a response

[1621] The device sends the data entered by the user to the server, which analyzes it and generates a response. For example, if the user asks, "What's the weather like today?", the server responds, "It's sunny today," and sends it to the device.

[1622] 3. Sensor data acquisition and anomaly detection

[1623] The device monitors the user's health status and sends it to a server. The server analyzes the received data and notifies the user if an abnormality is detected. For example, if the user's heart rate is abnormally high, the server notifies an emergency contact.

[1624] 4. Providing information about activities

[1625] The server generates activity recommendations based on the user's interests and profile, for example, telling the user, "There's a gardening workshop being held at a nearby park."

[1626] The system of the present invention reduces the sense of isolation felt by elderly people and enables them to respond quickly to abnormal situations, allowing them to live with peace of mind.

[1627] The processing flow will be explained below.

[1628] Step 1:

[1629] The device starts up and displays a screen for the user to log in. The user enters their username and password on the login screen and taps the login button.

[1630] Step 2:

[1631] The device sends the login information to the server. The server verifies the received login information, and if authentication is successful, it sends the home screen data. The device then displays the home screen.

[1632] Step 3:

[1633] The user selects the "Chat" icon on the home screen to begin a conversation with the AI ​​agent, and then types "What's the weather like today?" into the input field.

[1634] Step 4:

[1635] The device receives the text data entered by the user and sends it to the server. The server analyzes the received input data and generates a response such as "Today's weather is sunny." The server then sends the generated response data to the device.

[1636] Step 5:

[1637] The device displays the received response data to the user, who sees the message "Today's weather is sunny."

[1638] Step 6:

[1639] The device uses built-in sensors to collect real-time data on the user's health, including heart rate, steps taken, and body temperature, and this data is periodically sent to a server.

[1640] Step 7:

[1641] The server analyzes the received health data and detects abnormal patterns or emergencies. For example, if the heart rate is outside the normal range, the server will detect an abnormality.

[1642] Step 8:

[1643] If the server detects an abnormality, it will notify the user and designated emergency contacts, who will be informed via email and SMS.

[1644] Step 9:

[1645] The user selects the "Activity Guide" icon and receives suggestions for categories and events that interest them. The server references the user's profile data and generates appropriate activity guides.

[1646] Step 10:

[1647] The server sends the generated activity guide to the terminal, which then displays the received activity guide to the user, encouraging them to participate in specific events or online courses.

[1648] Example 1

[1649] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1650] Communication support and health monitoring in daily life are important for reducing feelings of isolation and improving safety for the elderly. However, existing systems lack sufficient activity guidance based on the user's interests or prompt notification when an abnormality is detected, and an improved user experience is required. In addition, there is a lack of technology to generate more appropriate responses through voice input text conversion and natural language processing using generative AI models. A new system that solves these issues is needed.

[1651] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1652] In this invention, the server includes: means for managing user profile data; means for acquiring and transmitting user input data to the server; means for the server to generate an appropriate response based on the user profile data and input data; means for providing the generated response to the user; means for acquiring the user's health status and activity information using a sensor and transmitting it to the server; means for the server to analyze the acquired health status and activity information and detect abnormalities; means for notifying the user and emergency contacts when an abnormality is detected; means for a generative AI model with natural language processing capabilities to generate the generated response; and means for converting the user's input data from voice to text. This improves the safety and communication of elderly people. It also enables activity guidance based on the user's interests and rapid response when an abnormality is detected.

[1653] "User profile data" refers to data that includes basic information about the user (age, gender, hobbies, health status) and past activity history.

[1654] "Input data" refers to text and voice data that a user inputs through a terminal.

[1655] A "server" is a computer system that analyzes user profile data and input data and generates an appropriate response.

[1656] A "generative AI model" refers to an algorithm or machine learning model that has natural language processing capabilities and generates appropriate responses based on input data.

[1657] A "sensor" is a device that acquires a user's health status (heart rate, body temperature, number of steps, etc.) and activity information in real time.

[1658] "Abnormality detection" refers to the server analyzing acquired health status and activity information and determining abnormal conditions that exceed the normal range.

[1659] "Notification" refers to the act of sending an alert to the user and emergency contacts when an abnormality is detected.

[1660] "Activity Guides" are suggested activities and events based on a user's profile data and interests.

[1661] "Speech to text conversion" refers to the process of converting voice input data into text data.

[1662] "Natural language processing" refers to the technology that enables computers to understand and generate human language.

[1663] MODE FOR CARRYING OUT THE INVENTION

[1664] This invention is an "anti-isolation AI" system that supports the safety and communication of elderly people. The system manages user profile data and input data, and provides a series of functions such as health monitoring using sensors, dialogue support using generative AI models, anomaly detection and notification, and activity guidance.

[1665] The system configuration uses the following hardware and software:

[1666] User data management (server)

[1667] The server manages profile data such as basic user information (age, gender, hobbies, health status) and past activity history. This data is stored and managed appropriately using a database management system (DBMS), and any updates are recorded as appropriate.

[1668] Specific examples

[1669] If a user becomes interested in "gardening" as a new hobby, the server records this information in the database.

[1670] Data entry and transmission (terminal, user)

[1671] The user inputs a message through the device using text or voice. The input data is sent from the device to the server. If voice input is performed, the device converts this voice into text.

[1672] Specific examples

[1673] When a user asks "What's the weather like today?", the device converts this into text and sends it to the server.

[1674] Prompt Sentence Examples

[1675] Parse the text asking about today's weather and generate an appropriate response.

[1676] Response generation and delivery (server, terminal)

[1677] The server analyzes the data received from the user using the generative AI model and generates an appropriate response, which is then provided to the user via their device.

[1678] Specific examples

[1679] When a user asks, "What's the weather like today?", the generative AI model is used to analyze the question and generate a response such as "The weather is sunny today," which the device then notifies the user.

[1680] Sensor data acquisition (terminal)

[1681] The device uses built-in sensors to obtain real-time information about the user's health status (heart rate, body temperature, number of steps) and periodically transmits this data to a server.

[1682] Specific examples

[1683] The device measures the number of heartbeats per minute and sends this data to a server.

[1684] Anomaly detection and notification (server)

[1685] The server analyzes the health data and detects any abnormalities. If an abnormality is detected, a notification is sent to the user and their emergency contacts.

[1686] Specific examples

[1687] The server detects an abnormal heart rate and sends a notification to the user and emergency contacts saying, "Your heart rate is too high."

[1688] Providing activity information (server, terminal)

[1689] The server suggests appropriate activities and events based on the user's profile data and interests, thereby facilitating social participation and interaction.

[1690] Specific examples

[1691] Based on the user's profile data, the server recommends, "There's a gardening workshop being held in a nearby park."

[1692] The system of the present invention reduces the sense of isolation felt by the elderly, providing them with peace of mind and companionship in their daily lives. It also provides a safe environment by enabling rapid response to emergency situations.

[1693] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1694] Program processing flow

[1695] Step 1: Managing User Profile Data (Server)

[1696] The server stores profile data such as basic user information (age, gender, hobbies, health status) and past activity history in a database. When a user registers or updates their profile data, it manages this data and records the changes.

[1697] input

[1698] User basic information (age, gender, hobbies, health condition)

[1699] process

[1700] The server uses a database management system (DBMS) to properly store and manage user information.

[1701] output

[1702] A database with updated user profile data

[1703] Specific actions

[1704] The server receives the new user's registration information and stores it in a database.

[1705] When a user adds a new hobby (e.g. gardening), the server records this change in the database.

[1706] Step 2: Data entry and transmission (terminal, user)

[1707] The user inputs text or voice through the device, which processes the input data and sends it to the server. If voice input is used, the device converts the voice into text.

[1708] input

[1709] User voice or text input

[1710] process

[1711] The device converts the voice input into text and sends this data to the server.

[1712] output

[1713] Textual input data sent to the server

[1714] Specific actions

[1715] The user speaks, "What's the weather like today?"

[1716] The device converts the voice into text and sends the text data "What's the weather like today?" to the server.

[1717] Step 3: Generate and serve a response (server, terminal)

[1718] The server analyzes the data received from the user using the generative AI model and generates an appropriate response, which is then provided to the user via their device.

[1719] input

[1720] Text input data sent by the user

[1721] process

[1722] The server uses a generative AI model to analyze the input data and generate an appropriate response.

[1723] output

[1724] Generated response text

[1725] Specific actions

[1726] The server parses the question "What's the weather today?" and generates the response "The weather is sunny today."

[1727] The device displays or plays this response to the user.

[1728] Step 4: Acquiring sensor data (device)

[1729] The device uses built-in sensors to obtain the user's health status (heart rate, body temperature, number of steps) in real time and periodically transmits this data to a server.

[1730] input

[1731] Health status data acquisition using sensors

[1732] process

[1733] The health data collected by the device is periodically sent to a server.

[1734] output

[1735] Health status data sent to the server

[1736] Specific actions

[1737] The device measures the user's heart rate every minute and sends this data to a server.

[1738] Step 5: Anomaly detection and notification (server)

[1739] The server analyzes the health data and detects any abnormalities. If an abnormality is detected, a notification is sent to the user and their emergency contacts.

[1740] input

[1741] Health data sent from the device

[1742] process

[1743] The server analyzes health data and detects abnormalities that exceed the normal range.

[1744] output

[1745] Anomaly detection notification message

[1746] Specific actions

[1747] The server detects abnormal heart rate and sends a notification to the user and emergency contacts saying, "Your heart rate is too high."

[1748] Step 6: Providing activity information (server, terminal)

[1749] The server suggests appropriate activities and events based on the user's profile data and interests, thereby facilitating social participation and interaction.

[1750] input

[1751] User profile data and interest data stored on the server

[1752] process

[1753] The server searches for and generates appropriate activities and events based on the user's interests.

[1754] output

[1755] Proposed activities and event information

[1756] Specific actions

[1757] Based on the user's interest data, the server recommends, "There's a gardening workshop being held in a nearby park."

[1758] The device will notify the user of this information.

[1759] Through the above processing steps, the system of the present invention improves safety and communication for the elderly. It also enables activity guidance based on the user's interests and quick response when an abnormality is detected.

[1760] (Application example 1)

[1761] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1762] The problems of elderly isolation and lack of health monitoring are serious issues. Elderly operators working in factories and other facilities require real-time monitoring of their health status while ensuring work safety and efficiency, but current systems are unable to adequately address this. Therefore, a system is needed that effectively supports the safety and communication of elderly operators and enables rapid response in the event of an emergency.

[1763] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1764] In this invention, the server includes: means for managing user profile data; means for acquiring and transmitting user input data to the server; means for the server to generate an appropriate response based on the user profile data and input data; means for providing the generated response to the user; means for acquiring the user's health condition and activity information using a sensor and transmitting it to the server; means for the server to analyze the acquired health condition and activity information and detect abnormalities; means for notifying the user and emergency contacts when an abnormality is detected; and dialogue support means using an industrial robot equipped with an AI agent to support elderly operators in factories. This enables real-time monitoring of the health condition of elderly operators and rapid response to abnormalities while ensuring their safety and work efficiency.

[1765] "User profile data" refers to the user's basic information (age, gender, hobbies, health status) and past activity history.

[1766] "Input Data" refers to information such as messages or questions entered by the user via text or voice.

[1767] "Server" refers to a computer system for processing user profile data and input data and generating an appropriate response.

[1768] "Generated response" refers to an answer or guidance generated by the server based on user input data.

[1769] "Sensor" refers to a device that acquires a user's health status (heart rate, body temperature, number of steps, etc.) and activity information in real time.

[1770] "Analysis" refers to the process of analyzing information based on acquired data and detecting anomalies and patterns.

[1771] "Anomaly detection" refers to detecting values ​​or trends that exceed the normal range through analysis results.

[1772] "Emergency contacts" refers to contact information for the user's family, medical institutions, etc. who will be notified when an abnormality is detected.

[1773] An "AI agent" refers to software that uses artificial intelligence to interact with users and provide appropriate responses and guidance.

[1774] An "industrial robot" refers to an automated mechanical device used in production sites such as factories.

[1775] "Dialogue support" refers to supporting communication between elderly operators and industrial robots.

[1776] "Activity Guide" refers to suggested activities and events based on a user's interests and profile.

[1777] "Cloud" refers to computing resources provided over the Internet.

[1778] "Real-time" refers to the immediacy and processing and provision of information with almost no delay.

[1779] The present invention relates to an "elderly operator support system" that ensures the safety and work efficiency of elderly operators while enabling real-time monitoring of their health status and prompt response in the event of an abnormality. Specific embodiments are described below.

[1780] System configuration

[1781] 1. User profile data management (server)

[1782] The server manages profile data such as basic information (age, gender, hobbies, health status) of the elderly operator users and their past work history. For example, if a new task or skill is added, the server updates and records it.

[1783] 2. Data entry and transmission (terminal, user)

[1784] The user inputs different types of data (text and voice) through a tablet or voice input device and sends this to the server, for example, asking "What do I do next?"

[1785] 3. Generating and Providing Responses (Server, Terminal)

[1786] The server analyzes the received input data and generates an appropriate response to the user's question. The generated response is provided to the user via a tablet or voice device. For example, the server generates a response such as "Next, we will inspect the part" and displays it on the terminal.

[1787] 4. Data acquisition by sensors (terminal)

[1788] The terminal uses sensors built into the wearable device to obtain real-time information on the elderly operator's health, such as heart rate, body temperature, and number of steps taken, and this data is periodically sent to a server.

[1789] 5. Anomaly detection and notification (server)

[1790] The server analyzes the health data and detects any abnormalities. For example, if the heart rate exceeds the normal range, the server determines this to be an abnormality and sends a notification to the factory manager and emergency contact.

[1791] 6. Providing activity information (server, terminal)

[1792] The server suggests the next task and efficient work methods based on the elderly operator's profile data and past work history, thereby improving the user's work efficiency.

[1793] A natural language description of the program's operation

[1794] 1. Managing User Data

[1795] The server manages basic information and past work history of elderly operators and records any updates. For example, if a new skill is added, the server adds it to the profile data.

[1796] 2. Sending input data and generating a response

[1797] The terminal sends the data entered by the user to the server, which analyzes it and generates an appropriate response. For example, if the user asks, "What's next?", the server generates the response, "Next is to inspect the part," and sends it to the terminal.

[1798] 3. Sensor data acquisition and anomaly detection

[1799] The device monitors the health status of the elderly operator and sends the information to a server. The server analyzes the received data and notifies the factory manager and emergency contacts if an abnormality is detected. For example, if the user's heart rate is abnormally high, the server notifies the factory manager and emergency contacts.

[1800] 4. Providing information about activities

[1801] The server generates activity guides based on the interests and profile of the elderly operator, for example, providing the user with a guide such as, "Next is a parts inspection, followed by machine maintenance."

[1802] Specific Examples

[1803] Examples:

[1804] If an elderly operator working at a precision manufacturing factory experiences an abnormally high temperature while inspecting a product, the factory manager and emergency contacts will be automatically notified. The operator can also ask the AI ​​assistant, "What should I do next?" to confirm the next steps.

[1805] Example prompts to input to a generative AI model:

[1806] "If an elderly operator working in a manufacturing plant feels unwell during the night shift, write a program on how an AI assistant can assist in this situation and notify the manager."

[1807] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1808] Step 1:

[1809] A user inputs profile data into a terminal. For example, basic information such as age, gender, hobbies, and health status is input. This input data is stored in a database and sent to a server. The input data is processed to generate profile data, which is then registered on the server.

[1810] Step 2:

[1811] The user enters a question or command through the device, for example, "What do I do next?" using text or voice input. The device sends this to the server, which processes the input data, analysing the text or voice data and converting it into an appropriate format.

[1812] Step 3:

[1813] The server analyzes the received input data and generates an appropriate response. This analysis is performed using a generative AI model that includes natural language processing. For example, in response to the input query "What task will be performed next?", a response such as "Next is the inspection of the parts" is generated. Data analysis organizes the information and generates response data.

[1814] Step 4:

[1815] The generated response data is sent from the server to the terminal and provided to the user. For example, a text response is displayed on the tablet screen or read aloud. An output based on the server's response data is generated and displayed on the terminal.

[1816] Step 5:

[1817] The terminal uses sensors built into the wearable device to acquire the user's health data (heart rate, body temperature, number of steps, etc.) in real time. The acquired data is periodically sent to a server. The real-time health data is generated and transmitted based on the data acquired by the sensors.

[1818] Step 6:

[1819] The server analyzes the acquired health data and detects any abnormalities. For example, if the heart rate is outside the normal range, the server determines this as an abnormality. Anomaly detection based on data analysis determines whether or not there is an abnormality.

[1820] Step 7:

[1821] If an abnormality is detected, the server sends a notification to the user and emergency contacts. For example, if the heart rate is abnormally high, the server notifies the factory manager and emergency contacts. The notification function enables a prompt response when an abnormality is detected.

[1822] Step 8:

[1823] The server suggests the next task and the most efficient way to work based on the user's profile data and past work history. For example, it provides the user with guidance such as, "Next is the parts inspection, followed by machine maintenance." Data analysis and suggestion functions aim to improve work efficiency.

[1824] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1825] This invention combines an emotion engine with an "anti-isolation AI" system that supports the safety and communication of elderly people. The system provides functions such as data acquisition using sensors, dialogue support by an AI agent, anomaly detection and notification, activity guidance, and an emotion engine that recognizes user emotions.

[1826] System configuration

[1827] 1. User profile data management (server)

[1828] The server manages profile data such as basic user information (age, gender, hobbies, health status) and past activity history.

[1829] 2. Data entry and transmission (terminal, user)

[1830] The user inputs text or voice through the device, which then sends it to the server. For example, if the user inputs "What's the weather like today?", this message is sent to the server.

[1831] 3. Generating and Providing Responses (Server, Terminal)

[1832] The server analyzes the received input data and generates an appropriate response to the user's question. The generated response is provided to the user through the terminal. For example, the server generates a response such as "Today's weather is sunny," and the terminal displays it to the user.

[1833] 4. Data acquisition by sensors (terminal)

[1834] The device uses built-in sensors to collect real-time data on the user's health, including heart rate, steps taken, and body temperature, and this data is periodically sent to a server.

[1835] 5. Anomaly detection and notification (server)

[1836] The server analyzes the health data and detects abnormal patterns or emergencies. For example, if the heart rate is outside the normal range, the server will detect the abnormality. When the server detects an abnormality, it will send a notification to the user and their designated emergency contacts.

[1837] 6. Emotion Recognition by Emotion Engine (Server)

[1838] The server uses an emotion engine to recognize the user's emotions based on the user's input data and data acquired from the sensors. For example, the emotion engine analyzes the user's voice and text and detects "stress."

[1839] 7. Emotion-based response modification (server, terminal)

[1840] The server then modifies the response it generates based on the user's emotions as recognized by the emotion engine. For example, if the server detects that the user is under stress, it generates a response such as, "Why don't you try listening to some relaxing music?"

[1841] 8. Use in Emotion Data Analysis (Server)

[1842] The server also uses the emotion data recognized by the emotion engine as part of its analysis of health status and activity information. This data is also reflected in the anomaly detection process, enabling more accurate anomaly detection.

[1843] 9. Emotion-based activity guidance (server, terminal)

[1844] The server generates appropriate activity recommendations for the user based on the user's emotional data recognized by the emotion engine. For example, if the user is recognized as "depressed," the server will suggest that the user participate in relaxation activities or hobbies.

[1845] A natural language description of the program's operation

[1846] 1. Managing User Data

[1847] The server manages the user's profile data and records any updates made to it, for example, if a user takes up a new hobby, "gardening," the server records this.

[1848] 2. Sending input data and generating a response

[1849] The device sends the data entered by the user to the server, which analyzes it and generates a response. For example, if the user asks, "What's the weather like today?", the server responds, "It's sunny today," and sends it to the device.

[1850] 3. Sensor data acquisition and anomaly detection

[1851] The device monitors the user's health status and sends it to a server. The server analyzes the received data and notifies the user if an abnormality is detected. For example, if the user's heart rate is abnormally high, the server notifies an emergency contact.

[1852] 4. Emotional Data Recognition and Response Modification

[1853] The server analyzes the user's input data and sensor data using an emotion engine to recognize the user's emotions. For example, if the user is under stress, the server will modify the response and provide it via the device, suggesting, "Why not try listening to some relaxing music?"

[1854] 5. Use in Emotion Data Analysis

[1855] The server uses the emotional data recognized by the emotion engine to analyze the user's health status and reflects this in the anomaly detection process. For example, if a user is depressed over a long period of time, it can take action such as suggesting early consultation with a doctor or counselor.

[1856] 6. Emotion-based activity guidance

[1857] The server generates appropriate activity recommendations based on the user's emotional state. For example, a "depressed" user might be provided with relaxation activities to encourage social interaction.

[1858] By incorporating an emotion engine, the system of the present invention can flexibly respond to the user's emotional state, reduce the elderly's sense of isolation, and provide support for them to live with peace of mind.

[1859] The processing flow will be explained below.

[1860] Step 1:

[1861] The device starts up and displays a screen for the user to log in. The user enters their username and password on the login screen and taps the login button.

[1862] Step 2:

[1863] The device sends the login information to the server. The server verifies the received login information, and if authentication is successful, it sends the home screen data. The device then displays the home screen.

[1864] Step 3:

[1865] The user selects the "Chat" icon on the home screen to begin a conversation with the AI ​​agent, and then types "What's the weather like today?" into the input field.

[1866] Step 4:

[1867] The device receives the text data entered by the user and sends it to the server. The server analyzes the received input data and generates a response such as "Today's weather is sunny." The server then sends the generated response data to the device.

[1868] Step 5:

[1869] The device displays the received response data to the user, who sees the message "Today's weather is sunny."

[1870] Step 6:

[1871] The device uses built-in sensors to collect real-time data on the user's health, including heart rate, steps taken, and body temperature, and this data is periodically sent to a server.

[1872] Step 7:

[1873] The server analyzes the received health data and detects abnormal patterns or emergencies. For example, if the heart rate is outside the normal range, the server will detect an abnormality.

[1874] Step 8:

[1875] If the server detects an abnormality, it will notify the user and designated emergency contacts, who will be informed via email and SMS.

[1876] Step 9:

[1877] The server uses an emotion engine to analyze user input data and sensor data to recognize the user's emotions. For example, it can detect "anxiety" from the text and voice input of the user.

[1878] Step 10:

[1879] The server then modifies the response appropriately based on the user's emotions as determined by the emotion engine. For example, if the server determines that the user is feeling anxious, it generates a response suggesting, "Why not try listening to some relaxing music?"

[1880] Step 11:

[1881] The device displays the modified response to the user, who sees the message, "Why not try listening to some relaxing music?"

[1882] Step 12:

[1883] The server also uses the emotional data recognized by the emotion engine to analyze health status and activity information. For example, if a user has been feeling depressed for a long period of time, that data will be reflected in the analysis.

[1884] Step 13:

[1885] The server generates appropriate activity guides based on the emotion data recognized by the emotion engine, suggesting activities, events, relaxation methods, etc. according to the user's emotional state.

[1886] Step 14:

[1887] The device displays the generated activity guide to the user. For example, if the user is feeling "down," the device provides a guide such as "Why don't you join a gardening event at a nearby park?"

[1888] Example 2

[1889] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1890] There is a need to reduce the sense of isolation felt by the elderly and provide an environment where they can live safely while maintaining social connections. In particular, there is a lack of systems that can monitor their health and emotional state in real time and provide appropriate responses accordingly. Furthermore, there is a challenge in providing more accurate anomaly detection and activity guidance that takes emotional state into account.

[1891] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for managing user profile data, means for acquiring and analyzing user input data and generating an appropriate response, means for acquiring the user's health condition and activity information and detecting abnormalities, means for recognizing emotions based on the user input data and data acquired from the sensor, means for modifying responses based on the recognized emotions, means for analyzing the emotion data and reflecting it in the anomaly detection process, and means for generating appropriate activity guidance based on the emotion data and providing it to the user. This makes it possible to comprehensively monitor the health condition and emotional state and provide appropriate responses and guidance, allowing elderly people to live with peace of mind and reducing their sense of isolation.

[1892] "User Profile Data" refers to basic information such as age, gender, hobbies, health status, and past activity history.

[1893] "Server" refers to a computer system that processes data received from users, manages profile data, generates responses, detects anomalies, etc.

[1894] "Terminal" refers to a device that allows a user to manipulate input data and obtain health and activity information through sensors.

[1895] "Input data" refers to text and voice data provided by the user through the terminal.

[1896] "Generated response" refers to a reply or suggestion to the user that the server generates by analyzing the input data.

[1897] "Sensors" refer to devices that measure a user's health status, such as heart rate, steps, and body temperature, in real time.

[1898] "Health status and activity information" refers to data on the user's physical condition and behavior obtained through sensors.

[1899] "Anomaly detection" refers to the process by which the server analyzes health and activity information to discover unusual patterns or emergencies.

[1900] "Emotion engine" refers to an algorithm or program that analyzes user input data and sensor data to recognize emotions.

[1901] "Emotional Data" refers to information about a user's emotional state as recognized by the Emotion Engine.

[1902] "Activity guidance" refers to information about suggested activities based on a user's interests and emotional state.

[1903] "Emergency Contact" means a person or entity designated to receive notification when an anomaly is detected.

[1904] MODE FOR CARRYING OUT THE INVENTION

[1905] This invention is a system for supporting the safety and communication of the elderly, and it manages and analyzes user profile data, health data, and emotion data in an integrated manner. This system includes a server, terminals, sensors, emotion engine, etc., which work together to support the lives of the elderly.

[1906] System configuration

[1907] The system includes the following main components:

[1908] 1. Server

[1909] Profile data management: Store user basic information (age, gender, hobbies, health status, and past activity history) in a database and update it as needed.

[1910] Response generation: Based on the input data received from the user, a generative AI model is used to generate an appropriate response.

[1911] Anomaly detection: Analyzes health status and activity information sent from sensors to detect abnormalities.

[1912] Emotion Recognition: Recognize emotions from user input data and sensor data using an emotion engine.

[1913] Response Modification: Modify the response based on the recognized emotion data and provide it to the user.

[1914] 2. Terminal

[1915] Data Entry: Allows users to enter text or voice data, which is then sent to the server.

[1916] Sensor data acquisition: The built-in sensors are used to acquire the user's health data, such as heart rate, steps, and body temperature, in real time and send it to the server.

[1917] 3. Sensors

[1918] Health monitoring: Measures the user's heart rate, steps, temperature, etc.

[1919] 4. Emotion Engine

[1920] Sentiment analysis: Recognizing user emotions based on their voice, text, and health data.

[1921] System operation example

[1922] A concrete example of the system in action is as follows:

[1923] 1. Entering and submitting user data

[1924] User: For example, type "What's the weather like today?" into the device.

[1925] Terminal: Sends the entered data to the server.

[1926] 2. Generating and Displaying the Response

[1927] Server: Analyzes the input data using a generative AI model and generates a response such as "Today's weather is sunny."

[1928] Terminal: Displays the generated response to the user.

[1929] 3. Health data acquisition and anomaly detection

[1930] Sensor: Monitors the user's heart rate and sends the data to the server via the device.

[1931] Server: Analyzes the transmitted data and sends a notification to emergency contacts if the heart rate is abnormally high.

[1932] 4. Emotional Data Recognition and Response Modification

[1933] Server: Using the emotion engine, recognize emotions from user input data and sensor data. For example, if the input text is "tired," it detects "stress."

[1934] Server: Based on the recognized emotion, the server modifies the response to "Why not try listening to some relaxing music?" and provides it through the device.

[1935] Prompt Sentence Examples

[1936] Here are some example prompts to input to the generative AI model:

[1937] Answering questions

[1938] Prompt text: "The user types 'What's the weather today?' How should the server respond?"

[1939] Example response generated: "The weather is sunny today."

[1940] Emotion Recognition and Response Modification

[1941] Prompt: "By analyzing the user's text or voice data, how can the server recognize the user's emotions and generate a response based on them?"

[1942] Example generated response: "We've detected stress in your voice. Would you like to try listening to some relaxing music?"

[1943] This system can comprehensively monitor the user's health and emotional state, and generate appropriate responses and activity guidance based on that information, thereby providing support that allows elderly people to live with peace of mind.

[1944] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1945] Step 1:

[1946] Managing your profile data

[1947] Input: Basic information entered by the user when registering (age, gender, hobbies, health status, and past activity history)

[1948] What it does: The server receives input data from the user, stores it in a database, and updates existing data when the user provides new information.

[1949] Data Processing: The server merges the new information with the existing profile data to maintain consistency.

[1950] Output: Updated profile data is saved to the database.

[1951] Step 2:

[1952] Entering and Submitting Data

[1953] Input: The user uses the device to input text or voice data.

[1954] What happens: The user types a question, such as "What's the weather like today?"

[1955] Data processing: The device converts the text or voice data into a digital format and sends it to the server.

[1956] Output: The transformed input data is sent to the server.

[1957] Step 3:

[1958] Generating and serving the response

[1959] Input: User input data received by the server

[1960] Specific operation: The server uses a generative AI model to analyze the input data.

[1961] Data processing: Analyzes input data and generates appropriate responses.

[1962] Output: The generated response is sent to the terminal and displayed to the user. Example: "The weather is sunny today."

[1963] Step 4:

[1964] Acquiring Sensor Data

[1965] Input: Real-time data such as user heart rate, steps, and body temperature

[1966] How it works: Sensors built into the device measure these data.

[1967] Data processing: The acquired data is periodically sent to the server.

[1968] Output: The data acquired by the sensor is sent to the server.

[1969] Step 5:

[1970] Anomaly detection and notification

[1971] Input: Sensor data received by the server

[1972] Specific operation: The server analyzes the sensor data and detects abnormalities, such as when the heart rate exceeds the normal range.

[1973] Data processing: Analyze the data using anomaly detection algorithms.

[1974] Output: If an anomaly is detected, a notification is sent to the user and emergency contacts.

[1975] Step 6:

[1976] Emotion recognition by emotion engine

[1977] Input: User input and sensor data

[1978] Specific operation: The server uses an emotion engine to analyze this data and recognize the user's emotions.

[1979] Data processing: The emotion engine identifies the user's emotional state as a result of the analysis.

[1980] Output: Recognized emotion data is generated. Example: "I feel stressed."

[1981] Step 7:

[1982] Emotion-Based Response Modification

[1983] Input: Emotion data generated by the emotion engine

[1984] Specific behavior: The server modifies the generated response based on the emotion data.

[1985] Data processing: Regenerate the response content and modify it to correspond to the emotion.

[1986] Output: The modified response is sent to the terminal and provided to the user. Example: "Why not try listening to some relaxing music?"

[1987] Step 8:

[1988] Use in analyzing emotion data

[1989] Input: Emotion data recognized by the emotion engine

[1990] Specific operation: The server also reflects the emotion data in the anomaly detection process.

[1991] Data processing: Integrating emotion data into health analysis parameters.

[1992] Output: Consolidated analytical data is generated.

[1993] Step 9:

[1994] Emotion-based activity guidance

[1995] Input: Emotion data recognized by the emotion engine

[1996] Specific operation: The server generates appropriate activity guidance for the user based on the emotion data.

[1997] Data processing: Generate activities that match the emotional state.

[1998] Output: The generated activity guide is sent to the terminal and provided to the user. Example: "Try participating in a relaxation activity."

[1999] Through these processing steps, the system monitors the health and emotional state of elderly people in real time, and provides appropriate responses and activity guidance based on that information, thereby supporting an environment in which they can live with peace of mind.

[2000] (Application example 2)

[2001] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2002] While safety and health management for elderly people and factory workers is important, existing systems do not adequately monitor their health and emotional states in real time. Furthermore, there is a lack of systems that can quickly detect abnormalities and take appropriate action. Therefore, there is a need for a system that can respond promptly when an abnormality occurs.

[2003] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for managing user profile data; means for acquiring and transmitting user input data to the server; means for the server to generate an appropriate response based on the user profile data and input data; means for providing the generated response to the user; means for acquiring and transmitting user health and activity information using a sensor; means for the server to analyze the acquired health and activity information and detect abnormalities; means for notifying the user and emergency contacts when an abnormality is detected; means for recognizing the user's emotional state using an emotion engine; means for appropriately modifying the generated response based on the emotional state; means for generating and providing activity guidance based on the emotional state; means for monitoring the health and emotional states of factory workers in real time; and means for notifying workers and managers when an abnormality is detected. This makes it possible to monitor the health and emotional states of elderly people and factory workers in real time, quickly detect abnormalities, and take appropriate action.

[2004] "User profile data" refers to information such as the user's age, gender, hobbies, health status, and past activity history.

[2005] "Input Data" means information entered by a User through text or voice that is transmitted to the Server.

[2006] "Server" means a central computer that analyzes user input and profile data and generates and provides appropriate responses.

[2007] A "sensor" is a device that acquires a user's health status (heart rate, body temperature, etc.) and activity information (number of steps, etc.) in real time.

[2008] An "anomaly detection method" is a system that has the ability to analyze acquired health and activity information and recognize unusual patterns or emergency situations.

[2009] The "emotion engine" is an algorithm that analyzes the user's voice and text input, as well as sensor data, to recognize the user's emotional state.

[2010] The "means for appropriately modifying a response" is a system that has the function of adjusting the generated response based on the user's emotional state recognized by the emotion engine.

[2011] "Activity Guide" refers to suggested activities and events based on a user's interests and emotional state.

[2012] "Real-time monitoring means" refers to a system for monitoring and collecting data on a user's health and emotional state in real time.

[2013] "Means for notification" means a function for promptly notifying the user and emergency contacts of detected abnormalities.

[2014] This invention combines an "anti-isolation AI" system with an emotion engine to realize safety and health management for the elderly and factory workers. This system uses sensors to monitor health conditions, an AI agent to conduct dialogue, and the emotion engine recognizes emotions and generates appropriate responses.

[2015] System configuration

[2016] 1. User profile data management (server)

[2017] The server manages profile data including the user's age, gender, hobbies, health status, past activity history, etc. This data is used to respond to the user's individual needs.

[2018] 2. Data entry and transmission (terminal, user)

[2019] The user inputs text or voice through the device, which then sends it to the server. For example, if the user inputs "What's the weather like today?", this message is sent to the server.

[2020] 3. Generating and Providing Responses (Server, Terminal)

[2021] The server analyzes the received input data and generates an appropriate response to the user's question. The generated response is provided to the user through the terminal. For example, the server generates a response such as "Today's weather is sunny," and the terminal displays it to the user.

[2022] 4. Data acquisition by sensors (terminal)

[2023] The device uses built-in sensors to collect real-time data on the user's health, including heart rate, steps taken, and body temperature, and this data is periodically sent to a server.

[2024] 5. Anomaly detection and notification (server)

[2025] The server analyzes the health data and detects abnormal patterns or emergencies. For example, if the heart rate is outside the normal range, the server will detect the abnormality. When the server detects an abnormality, it will send a notification to the user and their designated emergency contacts.

[2026] 6. Emotion Recognition by Emotion Engine (Server)

[2027] The server uses an emotion engine to recognize the user's emotions based on the user's input data and data acquired from the sensors. For example, the emotion engine analyzes the user's voice and text and detects "stress."

[2028] 7. Emotion-based response modification (server, terminal)

[2029] The server then modifies the response it generates based on the user's emotions as recognized by the emotion engine. For example, if the server detects that the user is under stress, it generates a response such as, "Why don't you try listening to some relaxing music?"

[2030] 8. Use in Emotion Data Analysis (Server)

[2031] The server also uses the emotion data recognized by the emotion engine as part of its analysis of health status and activity information. This data is also reflected in the anomaly detection process, enabling more accurate anomaly detection.

[2032] 9. Emotion-based activity guidance (server, terminal)

[2033] The server generates appropriate activity recommendations for the user based on the user's emotional data recognized by the emotion engine. For example, if the user is recognized as "depressed," the server will suggest that the user participate in relaxation activities or hobbies.

[2034] 10. Health management and mental support for factory workers (servers, terminals)

[2035] The system monitors the health and emotional state of factory workers in real time and notifies the workers and their managers if an abnormality is detected. For example, if a worker's heart rate is abnormally high, the server will notify the manager and suggest that the worker take a break.

[2036] Examples of concrete examples and prompts

[2037] As a concrete example, the following is an example of a prompt sentence to be input to a generative AI model:

[2038] prompt:

[2039] "To teach the emotion analysis engine the difference between stress and relaxation, consider the following situations:"

[2040] Situation 1:

[2041] "If the user's heart rate exceeds 90:"

[2042] Response 1:

[2043] "Stress detected. We'll give you some relaxation suggestions."

[2044] Situation 2:

[2045] If the user's heart rate is within the normal range:

[2046] Response 2:

[2047] "Users are relaxed. Keep it up."

[2048] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2049] Step 1:

[2050] The server collects profile data such as the user's age, gender, hobbies, health status, and past activity history through a means for managing user profile data and stores it in a database, which is then ready to generate appropriate responses based on the individual user profile.

[2051] Input: User profile data (age, gender, hobbies, health status, activity history, etc.)

[2052] Output: User profile data stored in a database

[2053] Specific operation: The server receives the profile information provided by the user via the input form or voice and performs the process of recording it in the database.

[2054] Step 2:

[2055] The user provides input data through the terminal by text or voice, which the terminal transmits to the server, for example, by inputting a question such as "What's the weather like today?"

[2056] Input: User input data (text or voice)

[2057] Output: User input data sent to the server

[2058] Specific operation: The terminal converts the text and voice data entered by the user into an appropriate format and sends it to the server via the network.

[2059] Step 3:

[2060] The server analyzes the received input data, compares it with the user profile data, and generates an appropriate response. For example, if the user asks, "What's the weather like today?", the server generates the response, "The weather is sunny today."

[2061] Input: User input data sent to the server, user profile data

[2062] Output: The generated response (e.g., "The weather is sunny today")

[2063] How it works: The server uses natural language processing algorithms to analyze the user's input data and uses generative AI models to create appropriate responses.

[2064] Step 4:

[2065] The terminal receives the response sent from the server and provides it to the user, so that the user can get an answer to their question.

[2066] Input: Response data sent from the server

[2067] Output: The response data that is provided to the user

[2068] Specific operation: The terminal displays or outputs the received response data in a format that is easy for the user to understand.

[2069] Step 5:

[2070] The device uses built-in sensors to collect real-time health data such as the user's heart rate, number of steps, and body temperature, and periodically transmits this data to a server.

[2071] Input: Health status data obtained from sensors (heart rate, steps, temperature, etc.)

[2072] Output: Health status data sent to the server

[2073] Specific operation: The terminal periodically collects data obtained from the sensors and transmits it to the server via the network.

[2074] Step 6:

[2075] The server analyzes the captured health data to detect abnormal patterns or emergencies, such as when a heart rate exceeds the normal range.

[2076] Input: Health status data sent from the device

[2077] Output: Anomaly detection flag, details of abnormality settings

[2078] Specific operation: The server analyzes the collected health data and executes an algorithm to determine abnormal conditions. If an abnormality is detected, it sets the necessary flag.

[2079] Step 7:

[2080] When the server detects an abnormality, it will send a notification to the user and designated emergency contacts to ensure the user's safety.

[2081] Input: Anomaly detection flag, details of abnormality settings

[2082] Output: Notification message (user and emergency contact)

[2083] Specific operation: When an anomaly is detected, the server sends a notification message to pre-registered contacts.

[2084] Step 8:

[2085] The server uses an emotion engine to recognize the user's emotions based on the user's input data and data obtained from sensors, for example, detecting stress from voice and text.

[2086] Input: User input data, health status data obtained from sensors

[2087] Output: Emotional state (e.g. "Stressed")

[2088] Specific operation: The server uses the emotion engine to analyze the user's input and sensor data to determine the emotional state.

[2089] Step 9:

[2090] The server then modifies the response it generates based on the emotion it recognizes. For example, if the server recognizes that the user is under stress, it will modify the response to something like, "Why don't you try listening to some relaxing music?"

[2091] Input: Emotional state

[2092] Output: Modified response data

[2093] Specific operation: The server uses the generative AI model to modify the response corresponding to the emotion and prepare it as a response to be provided to the user.

[2094] Step 10:

[2095] The server uses the emotion data recognized by the emotion engine as part of its analysis of health status and activity information and reflects this in the anomaly detection process, enabling more accurate anomaly detection.

[2096] Input: Emotion data, health status data

[2097] Output: Highly accurate anomaly detection results

[2098] Specific operation: The server adds emotion data to the anomaly detection algorithm and uses it to improve the accuracy of anomaly detection.

[2099] Step 11:

[2100] The server generates and provides appropriate activity guidance to the user based on the user's emotional state recognized by the emotion engine. For example, if the server recognizes that the user is depressed, it suggests relaxation activities.

[2101] Input: Emotional state

[2102] Output: Activity guide data

[2103] Specific operation: Based on the results of the emotion engine, the server generates activity guides and event suggestions for the user and sends them to the terminal.

[2104] Step 12:

[2105] The terminal displays the activity guide provided by the server to the user and prompts them to carry out the suggested activities. This step is important for improving the quality of the user's life and work.

[2106] Input: Activity guide data provided by the server

[2107] Output: Activity guide displayed to user

[2108] Specific operation: The terminal displays the activity guidance data received from the server on the user interface and provides guidance to the user by voice or text.

[2109] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2110] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2111] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2112] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2113] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2114] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2115] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2116] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2117] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2118] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2119] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2120] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2121] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2122] 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.

[2123] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2124] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2125] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2126] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2127] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2128] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2129] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2130] The following is further disclosed regarding the above embodiment.

[2131] (Claim 1)

[2132] a means for managing your profile data;

[2133] A means for obtaining user input data and transmitting it to the server;

[2134] means for the server to generate an appropriate response based on the user's profile data and input data;

[2135] a means for providing the generated response to a user;

[2136] A means for acquiring user health status and activity information using sensors and transmitting the information to a server;

[2137] A means for the server to analyze the acquired health status and activity information and detect abnormalities;

[2138] A means of notifying users and emergency contacts when an anomaly is detected;

[2139] A system including:

[2140] (Claim 2)

[2141] 10. The system of claim 1, further comprising means for generating and providing activity guidance to the user based on the user's interests.

[2142] (Claim 3)

[2143] The system according to claim 1, further comprising means for analyzing data acquired from the sensor on the cloud.

[2144] "Example 1"

[2145] (Claim 1)

[2146] a means for managing your profile data;

[2147] A means for obtaining user input data and transmitting it to the server;

[2148] means for the server to generate an appropriate response based on the user's profile data and input data;

[2149] a means for providing the generated response to a user;

[2150] A means for acquiring user health status and activity information using sensors and transmitting the information to a server;

[2151] A means for the server to analyze the acquired health status and activity information and detect abnormalities;

[2152] A means of notifying users and emergency contacts when an anomaly is detected;

[2153] A means for generating responses using a generative AI model with natural language processing capabilities;

[2154] a means for converting user input data from speech to text; and

[2155] A system including:

[2156] (Claim 2)

[2157] 10. The system of claim 1, further comprising means for generating and providing activity guidance to the user based on the user's interests.

[2158] (Claim 3)

[2159] The system according to claim 1, further comprising...

Claims

1. a means for managing your profile data; A means for obtaining user input data and transmitting it to the server; means for the server to generate an appropriate response based on the user's profile data and input data; a means for providing the generated response to a user; A means for acquiring user health status and activity information using sensors and transmitting the information to a server; A means for the server to analyze the acquired health status and activity information and detect abnormalities; A means of notifying users and emergency contacts when an anomaly is detected; A system including:

2. 10. The system of claim 1, further comprising means for generating and providing to the user an activity guide based on the user's interests.

3. The system according to claim 1 , further comprising means for analyzing data acquired from the sensor on a cloud.

Images