System

Abstract

A system is provided.SOLUTION: A health monitoring system for monitoring an elderly person or a child, comprising: sensor means for measuring a heart rate, a blood pressure, a body temperature, position information, and activity information; transmission means for transmitting the information measured by said sensor means to a server; AI analysis means for receiving and analyzing the information transmitted by said transmission means; and notifying means for issuing an alert when an abnormality is detected by said AI analysis means.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] As our society ages, real-time health monitoring of the elderly and children is an important social issue. However, existing health monitoring devices, such as current smartwatches, have problems such as complicated operation and charging for elderly users. Furthermore, these devices are in the way when bathing or sleeping, resulting in low wear rates. Furthermore, their notification function in the event of an abnormality is insufficient, making early detection of abnormalities difficult. The present invention aims to solve these problems by providing a health monitoring system that can be easily worn by elderly people and children and that can detect and notify abnormalities in real time. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides a system with the following features. Specifically, this is a health monitoring system for watching over elderly people and children. It includes sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information, thereby monitoring the health status of elderly people and children in detail. Data measured by the sensor means is sent to a server and analyzed by AI analysis means. The AI ​​analysis means detects abnormalities based on the received data and is equipped with notification means that issues an alert when an abnormality occurs, thereby detecting abnormalities in real time and notifying relatives and caregivers. In addition, an SOS button means that can be operated by the user in an emergency can be provided, allowing for rapid notification of an emergency. This system employs a wristband or necklace-type sensor means, reducing the hassle of wearing it and making it easy for elderly people and children to use on a daily basis.

[0006] A "sensor" is a device for measuring heart rate, blood pressure, body temperature, location information, and activity information.

[0007] "Transmission means" is a mechanism with a communication function for transmitting data measured by the sensor to a server.

[0008] "AI analysis means" is a system that analyzes received data using artificial intelligence algorithms to detect abnormal values ​​and behavior.

[0009] "Notification means" refers to a means that has the function of conveying information to close relatives or caregivers when an abnormality is detected by the AI ​​analysis means.

[0010] "SOS button means" refers to a mechanism that includes a button that a user can operate in an emergency to immediately notify the user of an emergency.

[0011] A "wristband" is a sensor device that is worn on the user's arm.

[0012] A "necklace" is a sensor device that is worn around the user's neck. [Brief explanation of the drawings]

[0013] [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

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] 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).

[0017] 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.

[0018] 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.

[0019] 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.

[0020] 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."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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."

[0034] This invention is a system that monitors the health status and location information of elderly people and children in real time and promptly notifies users when an abnormality is detected. This system consists of three main components: a wristband or necklace-type sensor device, a server that analyzes the data, and the user who receives the notification.

[0035] 1. Sensor device (terminal)

[0036] The sensor device is equipped with various sensors necessary to measure heart rate, blood pressure, body temperature, location information, and activity information. This sensor device is provided in simple formats such as a wristband or necklace, so that elderly people and children can wear it on a daily basis without difficulty. The sensor device also has a communication module that transmits the measured data to a server.

[0037] The sensor device measures heart rate, blood pressure, and body temperature, for example, every 60 seconds, and temporarily stores the data in a buffer. This data is then sent to a server at regular intervals (for example, every 5 minutes). In the event of an emergency, the user can press the SOS button, and the data will be sent to the server immediately.

[0038] 2. Server (Central Management System)

[0039] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by an AI analysis means. The AI ​​analysis means compares the data with normal ranges and executes an algorithm to detect abnormal values ​​and abnormal behavior.

[0040] For example, if the heart rate is abnormal, the server will analyze the received heart rate data in detail and if it detects consecutive values ​​outside the normal range, it will determine that there is an abnormality. If such an abnormality is detected, the server will promptly send an alert to close relatives or caregivers via a notification means.

[0041] 3. Notification and Emergency Response (User)

[0042] Users (close relatives or caregivers) who receive alerts via notification methods can check the notifications in real time through a smartphone or tablet application. The alerts include the time when the abnormality occurred, detailed data, and current location information. Based on this information, users can take prompt action.

[0043] For example, if an elderly person's heart rate shows an abnormal value, the user will receive a push notification and can view the details in the app, after which they can contact the person directly or arrange for medical assistance if necessary.

[0044] Specific examples

[0045] Example 1: Detecting abnormal heart rates

[0046] 1. Device: The heart rate sensor measures the heart rate and sends the data to the server.

[0047] 2. Server: The server analyzes the received heart rate data and determines that an abnormality has occurred if a value outside the normal range is detected consecutively. If an abnormality is detected, an alert is issued.

[0048] 3. User: Next of kin receives an alert in the application, checks the details, assesses the situation, and if necessary, contacts the person directly to arrange medical services.

[0049] Example 2: Fall detection and notification

[0050] 1. Device: The accelerometer monitors the user's movements and detects abnormal acceleration (e.g., sudden acceleration or deceleration). If abnormal movement is detected, the data is sent to the server.

[0051] 2. Server: The server analyzes the received data and determines the possibility of a fall. It generates alert information for the fall detection and issues the alert via the notification means.

[0052] 3. User: Next of kin receive an alert in the application, check the detailed data, and if they determine that emergency response is required, they will contact them directly and respond promptly.

[0053] In this way, the system of the present invention can protect the health and safety of users by combining sensor devices that can be easily used by the elderly and children, a server that analyzes data in real time, and a notification means for rapid response.

[0054] The processing flow will be explained below.

[0055] Abnormal Heart Rate Detection Process

[0056] Step 1:

[0057] The device measures the heart rate using the heart rate sensor and temporarily stores the measurement data in a buffer.

[0058] Step 2:

[0059] The device sends the buffered heart rate data to the server at regular intervals (for example, every 5 minutes).

[0060] Step 3:

[0061] The server receives the heart rate data sent from the device and stores it in a database.

[0062] Step 4:

[0063] The heart rate data received by the server is analyzed using AI analysis tools, and abnormal values ​​are detected by comparing them with the normal range.

[0064] Step 5:

[0065] If the server detects an abnormal value, it generates alert information and issues an alert to close relatives or caregivers via a notification means.

[0066] Step 6:

[0067] Users receive alerts via an application on their smartphone or tablet, where they can view detailed data on abnormal heart rates.

[0068] Step 7:

[0069] The user assesses the situation and contacts the user or arranges for medical services if necessary.

[0070] Fall detection and notification process

[0071] Step 1:

[0072] The device uses an acceleration sensor to monitor the user's movements in real time and detect abnormal acceleration.

[0073] Step 2:

[0074] If the device detects abnormal acceleration, it immediately sends the data to the server.

[0075] Step 3:

[0076] The server receives the abnormal operation data sent from the device and stores the received data in a database.

[0077] Step 4:

[0078] The server analyzes the received data using AI analysis methods and determines that there is a high possibility of a fall.

[0079] Step 5:

[0080] The server generates alert information for the fall detection and notifies the next of kin or caregiver via the notification means.

[0081] Step 6:

[0082] Users can receive alerts via smartphone or tablet applications and check detailed data on fall detection.

[0083] Step 7:

[0084] If the user determines that an emergency response is required, the user will be contacted directly and help will be called for and responded to promptly.

[0085] Emergency Call Process

[0086] Step 1:

[0087] The device detects when the SOS button is pressed by the user and immediately sends emergency data to the server.

[0088] Step 2:

[0089] The server receives the emergency data sent from the device and stores the received data in a database.

[0090] Step 3:

[0091] The server generates emergency call alert information and immediately notifies the next of kin or caregiver via the notification means.

[0092] Step 4:

[0093] Users receive emergency alerts via smartphone or tablet applications and can view detailed emergency data.

[0094] Step 5:

[0095] The user assesses the situation and takes immediate action, arranging for medical services or emergency response if necessary.

[0096] Through the above processing steps, the system of the present invention can monitor the health and safety of the elderly and children in real time and respond quickly to abnormalities or emergencies.

[0097] Example 1

[0098] 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."

[0099] The goal is to monitor the health status and location information of vulnerable individuals, such as the elderly and children, in real time, and to take prompt and appropriate action when an abnormality occurs. However, existing systems make it difficult to respond quickly because the processes of data collection, communication, anomaly detection, and notification are not efficiently coordinated. In addition, many systems lack the ability to respond immediately in an emergency.

[0100] 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.

[0101] In this invention, the server includes sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information, transmission means for transmitting data measured by the sensor means to the server at regular intervals (for example, every 5 minutes), communication means for immediately transmitting data to the server when a user presses an SOS button operable by the user in an emergency, AI analysis means for receiving and analyzing the data transmitted by the transmission means and the emergency communication means, and notification means for promptly notifying close relatives or caregivers if an abnormality is detected by the AI ​​analysis means. This enables real-time health status monitoring, prompt notification in the event of an abnormality, and immediate response.

[0102] The "sensor means" refers to a device for measuring heart rate, blood pressure, body temperature, location information, activity information, and the like.

[0103] The "transmitting means" refers to a communication device for transmitting the data measured by the sensor means to a server at regular intervals.

[0104] "Communication means" refers to a device that allows a user to press an SOS button in an emergency to instantly send data to a server.

[0105] "AI analysis means" refers to an analytical device that uses artificial intelligence to analyze received data, compare it with the normal range, and detect abnormal values.

[0106] The "notification means" refers to a device that promptly notifies next of kin or caregivers when an abnormality is detected by the AI ​​analysis means.

[0107] This invention is a system that monitors the health status and location information of elderly people and children in real time and promptly notifies them when an abnormality is detected. This system consists of three main components: a wristband or necklace-type sensor device, a server that analyzes the data, and the user who receives the notification.

[0108] Sensor device (terminal)

[0109] The sensor device is equipped with various sensors to measure heart rate, blood pressure, body temperature, location information, and activity information. This sensor device is provided in simple formats such as wristbands and necklaces, and can be worn comfortably by the elderly and children on a daily basis. The sensor device also has a communication module that transmits the measured data to a server.

[0110] The device measures heart rate, blood pressure, and body temperature, for example, every 60 seconds, and temporarily stores the data in a buffer.The data is then sent to the server at regular intervals (for example, every 5 minutes).In the event of an emergency, the user can press the SOS button, and the data will be sent to the server immediately.

[0111] Server (central management system)

[0112] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by an AI analysis means. The AI ​​analysis means compares the data with normal ranges and executes an algorithm to detect abnormal values ​​and abnormal behavior.

[0113] For example, if the heart rate is abnormal, the server will analyze the received heart rate data in detail and if it detects consecutive values ​​outside the normal range, it will determine that there is an abnormality. If such an abnormality is detected, the server will promptly send an alert to close relatives or caregivers via a notification means.

[0114] Notification and Emergency Response (User)

[0115] Users (close relatives or caregivers) who receive alerts via notification methods can check the notifications in real time through a smartphone or tablet application. The alerts include the time when the abnormality occurred, detailed data, and current location information. Based on this information, users can take prompt action.

[0116] For example, if an elderly person's heart rate shows an abnormal value, the user will receive a push notification and can view the details in the app, after which they can contact the person directly or arrange for medical assistance if necessary.

[0117] Specific examples

[0118] Example 1: Detecting abnormal heart rates

[0119] 1. Device: The heart rate sensor measures the heart rate and sends the data to the server.

[0120] 2. Server: The server analyzes the received heart rate data and determines that an abnormality has occurred if a value outside the normal range is detected consecutively. If an abnormality is detected, an alert is issued.

[0121] 3. User: Next of kin receives an alert in the application, checks the details, assesses the situation, and if necessary, contacts the person directly to arrange medical services.

[0122] Example 2: Fall detection and notification

[0123] 1. Device: The accelerometer monitors the user's movements and detects abnormal acceleration (e.g., sudden acceleration or deceleration). If abnormal movement is detected, the data is sent to the server.

[0124] 2. Server: The server analyzes the received data and determines the possibility of a fall. It generates alert information for the fall detection and issues the alert via the notification means.

[0125] 3. User: Next of kin receive an alert in the application, check the detailed data, and if they determine that emergency response is required, they will contact them directly and respond promptly.

[0126] Prompt Sentence Examples

[0127] "If the user's heart rate is outside the normal range, activate an alert and notify next of kin."

[0128] "If the device's location information changes suddenly, send that data immediately and issue an alert if it determines there is a possibility of a fall."

[0129] In this way, the system of the present invention can protect the health and safety of the elderly and children in real time by combining sensor devices, a server that performs AI analysis, and notification means.

[0130] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0131] Step 1: Data collection (device)

[0132] The device operates various sensors to measure heart rate, blood pressure, body temperature, location information, and activity information. Specifically, the heart rate sensor measures heart rate every 60 seconds, and the blood pressure sensor measures blood pressure. These data are temporarily stored in a buffer within the device. Location information is also periodically updated using GPS and other location sensors. The input is vital information of the human body, and the output is sensor data stored in the buffer.

[0133] Step 2: Send data (terminal)

[0134] The communication module in the device sends the data stored in the buffer to the server at regular intervals (for example, every 5 minutes). In addition, in the event of an emergency, the user can press the SOS button, which immediately sends the data to the server. The input is the sensor data stored in the buffer, and the output is the transmitted data. Specifically, the communication module retrieves the data from the buffer and sends it to the server's receiving port.

[0135] Step 3: Receiving data (server)

[0136] The server receives data sent from the terminal. Specifically, the server constantly monitors the receiving port and waits for data to arrive. The input is the sensor data sent from the terminal, and the output is the received data. The received data is immediately saved in the database.

[0137] Step 4: Data analysis (server)

[0138] The AI ​​analysis algorithm in the server analyzes the received data by comparing it with normal ranges. For example, if consecutive abnormal heart rate values ​​are detected, it will flag them as an abnormality. The input is the sensor data stored in the database, and the output is the analysis result. Specifically, the AI ​​algorithm retrieves the data from the database and performs analysis.

[0139] Step 5: Alert generation (server)

[0140] If the server detects an abnormality, it will use the notification system to send an alert to relatives or caregivers. Specific operations include email, SMS, and app push notifications. The input is the result of the AI ​​analysis, and the output is the sent alert.

[0141] Step 6: Receiving and Confirming Notifications (User)

[0142] The user receives an alert notification on their smartphone or tablet. They can then check detailed data (such as the time the abnormality occurred and details of the heart rate) through the app. The input is the alert sent from the server, and the output is the detailed data displayed on the user's device. Specifically, the user opens the app and checks the alert content.

[0143] Step 7: Emergency Response (User)

[0144] After receiving an alert, the user checks the situation and takes necessary action, such as contacting the user directly or arranging for medical services. The input is the alert content and detailed data, and the output is the response action taken. Specific actions taken by the user include contacting the user by phone or messaging app.

[0145] (Application example 1)

[0146] 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."

[0147] Conventional health monitoring systems have difficulty monitoring the health status and location information of elderly people and children in real time, making it difficult to respond quickly when an abnormality occurs. Furthermore, there are cases where analysis of data sent from sensor devices and notifications are delayed, hindering emergency response. Furthermore, the system's operation is complicated, making it difficult for elderly people and children to use it on a daily basis.

[0148] 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.

[0149] In this invention, the server includes sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information, transmission means for transmitting data measured by the sensor means to the server, AI analysis means for receiving and analyzing the data transmitted by the transmission means, notification means for issuing an alert when an abnormality is detected by the AI ​​analysis means, SOS button means operable by the user in an emergency, transmission means configured to transmit part of the data to the server at specified intervals, a smartphone application for which the notification means issues push notifications, and means for notifying in real time when an abnormality is detected via the smartphone application. This makes it possible to monitor the health status and location information of elderly people and children in real time and to respond quickly and accurately when an abnormality occurs.

[0150] The "sensor means" is a device for measuring heart rate, blood pressure, body temperature, location information, and activity information.

[0151] The "transmitting means" is a device for transmitting data measured by the sensor means to the server.

[0152] "AI analysis means" refers to a device or system that uses artificial intelligence technology to receive and analyze data transmitted by the transmission means.

[0153] The "notification means" is a device or system that issues an alert to the user when an abnormality is detected by the AI ​​analysis means.

[0154] An "SOS button means" is a device having a button that can be operated by a user in an emergency, and operating this button sends an emergency notification.

[0155] A "smartphone application" is application software that runs on a smartphone and receives and displays push notifications from a notification means.

[0156] The "transmitting means configured to transmit data to a server at intervals" is a device having a function of transmitting a portion of data to a server at a set time interval.

[0157] "Means of real-time notification" refers to a function that immediately sends a notification via a smartphone application if an abnormality is detected.

[0158] This invention is a system that monitors the health status and location information of elderly people and children in real time and promptly notifies users when an abnormality is detected. This system consists of sensor devices, a server that analyzes the data, and users who receive notifications.

[0159] 1. Sensor device (terminal)

[0160] The terminal provides a wristband or necklace-type sensor means that can be worn daily by the elderly and children. This sensor device is equipped with various sensors to measure heart rate, blood pressure, body temperature, location information, and activity information, and temporarily stores these measured values ​​in a buffer at regular intervals. The sensor device also has a transmission means for sending the measured data to a server. It also has an SOS button means that the user can operate in the event of an emergency.

[0161] 2. Server (Central Management System)

[0162] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by the AI ​​analysis means. The AI ​​analysis means runs an algorithm that compares the data with normal health data to detect abnormal values ​​and behavior. This analysis is performed using software such as Python and Flask. If the notification means detects an abnormality, a push notification smartphone application will alert the user in real time. Notifications are sent using Google Firebase Cloud Messaging (FCM).

[0163] 3. User Notification and Emergency Response

[0164] The intended recipients of notifications are close relatives and caregivers. The smartphone application displays a push notification in real time when an abnormality occurs. The alert includes the time of the abnormality, detailed data, and the current location. After receiving the notification, the user can check the detailed data and take emergency action if necessary. For example, if an elderly person's heart rate shows an abnormal value, close relatives will receive a push notification and can check the detailed data in the application. They can then contact the user directly or arrange for medical services if necessary.

[0165] Specific examples

[0166] Consider the case where a 75-year-old person experiences an abnormally high heart rate while going about their daily life. At this time, the heart rate sensor detects the abnormal value and sends the data to the server. The server's AI analysis means analyzes the abnormal value and immediately detects the abnormality. The server then sends a push notification, which is sent in real time to the smartphones of close relatives.

[0167] Example prompt sentence:

[0168] Develop an application that monitors the heart rate and location of elderly people in real time and sends push notifications to their next of kin if an abnormality is detected. Use Python and Flask to receive data from sensor devices and include a function to send notifications via Firebase Cloud Messaging if an abnormal value is detected.

[0169] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0170] Step 1:

[0171] Data collection using sensor devices

[0172] The device's built-in sensors measure various data in real time, including heart rate, blood pressure, body temperature, location information, and activity information. This measurement data is temporarily stored in a buffer within the device.

[0173] Input: Heart rate, blood pressure, temperature, location, activity information

[0174] Output: Buffered sensor data

[0175] Step 2:

[0176] Data transmission

[0177] The terminal transmits data measured by the sensor means to the server at regular intervals (for example, every 5 minutes). In an emergency, the data is transmitted immediately when the SOS button means of the terminal is pressed.

[0178] Input: Buffered sensor data

[0179] Output: Sensor data sent to the server

[0180] Step 3:

[0181] Data reception and storage

[0182] The server receives the sensor data sent from the terminal and stores it in a database.

[0183] Input: Sensor data sent to the server

[0184] Output: Sensor data stored in a database

[0185] Step 4:

[0186] AI analysis

[0187] The server's AI analysis tools analyze the stored data in real time, compare it with normal data ranges, and run algorithms to detect outliers and abnormal behavior.

[0188] Input: Sensor data stored in a database

[0189] Output: Anomaly detection result (normal / abnormal)

[0190] Step 5:

[0191] Anomaly detection notification

[0192] If the AI ​​analysis method detects an abnormality, the server's notification method will send a push notification to the user. The push notification will include the time the abnormality occurred, detailed data, and the user's current location. Firebase Cloud Messaging (FCM) is used.

[0193] Input: Anomaly detection results

[0194] Output: A push notification that appears on the user's phone.

[0195] Step 6:

[0196] User Support

[0197] Users receive a notification on their smartphone app, view detailed data, assess the situation, and, if necessary, contact the user directly or arrange for medical assistance.

[0198] Input: Push notification displayed on smartphone

[0199] Output: User's response (contact, medical service arrangements, etc.)

[0200] 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.

[0201] This invention is a system that combines a system that monitors the health status and location information of elderly people and children in real time and quickly notifies users when an abnormality is detected with an emotion engine that recognizes the user's emotions. This system consists of a wristband or necklace-type sensor device, a server that analyzes the data, a user who receives notifications, and an emotion engine that recognizes the user's emotions.

[0202] 1. Sensor device (terminal)

[0203] The sensor device is equipped with various sensors necessary to measure heart rate, blood pressure, body temperature, location information, and activity information. This sensor device is provided in simple formats such as a wristband or necklace, so that elderly people and children can wear it on a daily basis without difficulty. The sensor device also has a communication module that transmits the measured data to a server.

[0204] 2. Server (Central Management System)

[0205] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by an AI analysis means. The AI ​​analysis means compares the data with normal ranges and executes an algorithm to detect abnormal values ​​and abnormal behavior.

[0206] The server also incorporates an emotion engine that analyzes the user's emotional state. The emotion engine recognizes the user's emotions by analyzing the user's voice data and facial expression data. This emotional information is also stored on the server and evaluated together with the analysis of the user's health status.

[0207] 3. Notification and Emergency Response (User)

[0208] Users (close relatives and caregivers) who receive alerts via notification methods can check the notifications in real time through a smartphone or tablet application. The alerts include the time of the abnormality, detailed data, current location information, and information about the user's emotional state. Based on this information, users can take prompt action.

[0209] For example, if an elderly person's heart rate shows abnormal values, the user will receive a push notification and can view the details and emotional state in the app, after which the user can be contacted directly or medical assistance can be arranged if necessary.

[0210] Specific examples

[0211] Example 1: Detecting abnormal heart rate with emotional fluctuations

[0212] 1. Device: The heart rate sensor measures the heart rate and sends the data to the server. The device also acquires the user's emotional data through voice recognition.

[0213] 2. Server: The server analyzes the received heart rate data and emotion data. If an abnormal value is detected, it evaluates the importance of the abnormality taking into account the emotion data.

[0214] 3. Server: If an abnormal heart rate is detected and the emotion engine detects emotional data indicating stress or anxiety, it generates alert information and sends an alert to close relatives or caregivers via notification means.

[0215] 4. User: Next of kin will receive a push notification to view detailed data and emotional state, assess the situation, contact the user if necessary, and arrange medical services.

[0216] Example 2: Fall and panic detection and notification

[0217] 1. Device: The accelerometer monitors the user's movements and detects abnormal acceleration. The voice recognition function also captures the user's emotional data (such as out-of-range tone of voice).

[0218] 2. Server: The server receives and analyzes the abnormal behavior data and emotion data. If it determines that there is a high possibility of a fall and the emotion engine detects emotion data indicating panic or fear, it generates an alert.

[0219] 3. Server: Notifies next of kin and caregivers of fall and panic alerts.

[0220] 4. User: Next of kin receives push notification to check abnormal behavior and emotional state, and responds quickly, arranging for help if necessary.

[0221] Specific program processing

[0222] The program processing is carried out in the following steps:

[0223] The sensor device measures heart rate, blood pressure, body temperature, location information, and activity information, and analyzes voice and facial expression data using an emotion engine. This data is sent to a server at regular intervals, and the server analyzes the received data using AI analysis means. In the event of an abnormality, an alert is generated taking into account the emotional information. Ultimately, a notification is sent to close relatives or caregivers, allowing for prompt action.

[0224] The system of the present invention can improve the safety and quality of life (QOL) of users by comprehensively monitoring the health status and emotions of elderly people and children.

[0225] The processing flow will be explained below.

[0226] Abnormal heart rate detection process combined with emotion engine

[0227] Step 1:

[0228] The device measures the heart rate using the heart rate sensor and temporarily stores the measurement data in a buffer.

[0229] Step 2:

[0230] The device uses its voice recognition function to acquire the user's voice data, analyzes it with its emotion engine, and temporarily stores the emotion data in a buffer.

[0231] Step 3:

[0232] The device sends the buffered heart rate data and emotion data to the server at regular intervals (e.g., every 5 minutes).

[0233] Step 4:

[0234] The server receives the heart rate data and emotion data sent from the device and stores the received data in a database.

[0235] Step 5:

[0236] The heart rate data received by the server is analyzed using AI analysis tools, and abnormal values ​​are detected by comparing them with the normal range.

[0237] Step 6:

[0238] The server analyzes the received emotional data to determine the user's emotional state, for example, detecting data indicating stress or anxiety.

[0239] Step 7:

[0240] The server comprehensively evaluates abnormal heart rate values ​​and emotional data to determine the importance of the abnormality.

[0241] Step 8:

[0242] If the server detects abnormal heart rate and emotions associated with stress or anxiety, it generates an alert with detailed data (heart rate, emotional state, time, and location).

[0243] Step 9:

[0244] The server issues an alert to the next of kin or caregiver via the notification means.

[0245] Step 10:

[0246] Users receive alerts via a smartphone or tablet application, where they can view detailed data on abnormal heart rates and emotional states.

[0247] Step 11:

[0248] The user assesses the situation and contacts the user or arranges for medical services if necessary.

[0249] Fall detection and notification process combined with emotion engine

[0250] Step 1:

[0251] The device uses an acceleration sensor to monitor the user's movements in real time and detect abnormal acceleration.

[0252] Step 2:

[0253] The device uses its voice recognition function to acquire the user's voice data, analyzes it with its emotion engine, and temporarily stores the emotion data in a buffer.

[0254] Step 3:

[0255] If the device detects abnormal acceleration, it immediately sends that data to the server, along with emotion data.

[0256] Step 4:

[0257] The server receives abnormal behavior data and emotion data sent from the device and stores them in a database.

[0258] Step 5:

[0259] The server analyzes the abnormal movement data using AI analysis methods and determines that there is a high possibility of a fall.

[0260] Step 6:

[0261] The server analyzes the emotional data to determine if the user is exhibiting panic or fear.

[0262] Step 7:

[0263] The server comprehensively assesses the likelihood of falling and the emotional state and determines the importance.

[0264] Step 8:

[0265] If the server detects a fall and emotions associated with panic or fear, it generates an alert containing detailed data (abnormal behavior, emotional state, time, and location information).

[0266] Step 9:

[0267] The server notifies the alert information to the next of kin or caregiver via the notification means.

[0268] Step 10:

[0269] Users receive alerts via a smartphone or tablet application, and can view detailed data on fall detection and emotional state.

[0270] Step 11:

[0271] If the user determines that an emergency response is required, we will promptly arrange for rescue and contact the user directly to confirm the situation.

[0272] In this way, the system of the present invention is designed to monitor not only the health status of elderly people and children but also their emotional state in real time, and to respond quickly to abnormalities or emergencies.

[0273] Example 2

[0274] 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."

[0275] In modern society, there is a growing demand for real-time monitoring of the safety and health of the elderly and children. However, current systems do not adequately detect abnormalities that take into account the user's emotional state, which can lead to delayed responses when an abnormality occurs. Furthermore, systems that simply measure biometric data have the challenge of making it difficult to respond appropriately to psychological states such as stress and anxiety in users.

[0276] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0277] In this invention, the server includes an AI analysis unit, an emotion engine unit, and a notification unit, which enables real-time detection of abnormalities and rapid response while taking into account both biometric data and emotion data.

[0278] The "sensor means" is a device for measuring biological data such as heart rate, blood pressure, body temperature, location information, and activity information.

[0279] The "transmitting means" is a communication device for transmitting data measured by the sensor means to the server.

[0280] "AI analysis means" refers to an artificial intelligence algorithm that analyzes received data in real time, compares it with normal ranges, and detects abnormal values ​​and behavior.

[0281] The "notification means" is a device that issues an alert to the user when an abnormality is detected by the AI ​​analysis means.

[0282] The "SOS button means" is a device that can be operated by a user to send an SOS signal in an emergency.

[0283] The "emotion engine means" is an algorithm for analyzing the user's voice and facial expression data and recognizing the user's emotional state.

[0284] An "alert" is a warning message that is sent to the user or a close relative when an abnormality is detected.

[0285] An "interval" is a specified time interval for sending data to the server.

[0286] This system monitors the health status and location information of elderly people and children in real time and promptly notifies users when abnormalities are detected. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to comprehensively evaluate both biometric data and emotion data. This system consists of a wristband or necklace-style sensor device, a server that analyzes the data, a user who receives notifications, and an emotion engine that recognizes the user's emotions.

[0287] 1. Sensor device (terminal)

[0288] The sensor device is equipped with sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information. This sensor device is available in the form of a wristband or necklace, making it easy for elderly people and children to wear on a daily basis. It also has a voice recognition function and a camera function for capturing voice and facial expression data. The sensor device also includes a communication module for transmitting the measured data to a server.

[0289] 2. Server (Central Management System)

[0290] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by AI analysis means. The AI ​​analysis means compares biometric data such as heart rate, blood pressure, body temperature, location information, and activity information with normal range data and executes algorithms to detect abnormal values ​​and behavior. The server also incorporates an emotion engine, which has the function of analyzing the user's emotional state. The emotion engine recognizes the user's emotions by analyzing the user's voice data and facial expression data. This emotional information is also stored on the server and is comprehensively evaluated along with an analysis of the user's health status.

[0291] 3. Notification and Emergency Response (User)

[0292] Users (close relatives and caregivers) who receive alerts via notification methods can check the notifications in real time through a smartphone or tablet application. The alerts include the time of the abnormality, detailed data, current location information, and information about the user's emotional state. Based on this information, users can take prompt action.

[0293] For example, if an elderly person's heart rate shows abnormal values, the user will receive a push notification and can view the details and emotional state in the app, after which the user can be contacted directly or medical assistance can be arranged if necessary.

[0294] Specific examples

[0295] Example 1: Detecting abnormal heart rate with emotional fluctuations

[0296] 1. Device: The heart rate sensor measures the heart rate and sends the data to the server. The device also acquires the user's emotional data through voice recognition.

[0297] 2. Server: The server analyzes the received heart rate data and emotion data. If an abnormal value is detected, it evaluates the importance of the abnormality taking into account the emotion data.

[0298] 3. Server: If an abnormal heart rate is detected and the emotion engine detects emotional data indicating stress or anxiety, it generates alert information and sends an alert to close relatives or caregivers via notification means.

[0299] 4. User: Next of kin will receive a push notification to view detailed data and emotional state, assess the situation, contact the user if necessary, and arrange medical services.

[0300] Example 2: Fall and panic detection and notification

[0301] 1. Device: The accelerometer monitors the user's movements and detects abnormal acceleration. The voice recognition function also captures the user's emotional data (such as out-of-range tone of voice).

[0302] 2. Server: The server receives and analyzes the abnormal behavior data and emotion data. If it determines that there is a high possibility of a fall and the emotion engine detects emotion data indicating panic or fear, it generates an alert.

[0303] 3. Server: Notifies next of kin and caregivers of fall and panic alerts.

[0304] 4. User: Next of kin receives push notification to check abnormal behavior and emotional state, and responds quickly, arranging for help if necessary.

[0305] Example prompt

[0306] "Describe a scenario in which you want to detect abnormal heart rates and emotional fluctuations in an elderly person."

[0307] "How do you alert me when my child falls and panics?"

[0308] This system comprehensively monitors the health and emotions of elderly people and children, improving the safety and quality of life of users.

[0309] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0310] Step 1:

[0311] Device: Measures heart rate, blood pressure, body temperature, location, and activity information.

[0312] How it works: Various sensors installed on the device continuously monitor the user's biometric data and collect data at regular intervals.

[0313] Input: User's biological status (heart rate, blood pressure, body temperature, location information, activity information)

[0314] Output: Biometric data set (heart rate, blood pressure, temperature, location, activity)

[0315] Step 2:

[0316] Terminal: Analyzes voice and facial expression data using an emotion engine to generate emotion data.

[0317] How it works: Using voice recognition and camera functions, the user's tone of voice and facial expressions are collected and analyzed by the emotion engine.

[0318] Input: User's voice data and image data (facial expressions)

[0319] Output: Emotion data (stress, anxiety, joy, etc.)

[0320] Step 3:

[0321] Terminal: Sends collected sensor data and emotion data to the server via the communication module.

[0322] Operation: Data is collected within the sensor device and transferred to the server via wireless communication (Wi-Fi, Bluetooth, etc.).

[0323] Input: Biometric dataset and emotion data

[0324] Output: Data packets (biometric dataset, emotion data) to the server

[0325] Step 4:

[0326] Server: The server receives the data sent from the device.

[0327] Operation: The server receives data via the communication protocol and stores it in a receive buffer.

[0328] Input: Data packets sent from the device

[0329] Output: Raw data in the receive buffer

[0330] Step 5:

[0331] Server: Stores the received data in a database.

[0332] How it works: Connects to a database and stores data by time.

[0333] Input: Raw data in the receive buffer

[0334] Output: Structured data stored in a database

[0335] Step 6:

[0336] Server: Analyzes the stored data in real time using AI analysis methods.

[0337] How it works: It uses AI models to analyze biometric data and compare it to normal ranges. If an abnormality is detected, it highlights it.

[0338] Input: Structured data in a database

[0339] Output: Abnormality detection result and its detailed data

[0340] Step 7:

[0341] Server: The emotion engine analyzes voice and facial expression data to recognize the user's emotional state.

[0342] How it works: The emotion engine analyzes subtle changes in vocal tone and facial expressions to determine emotional states (e.g., stress, joy, anxiety).

[0343] Input: Voice and facial expression data in the database

[0344] Output: Emotion analysis results

[0345] Step 8:

[0346] Server: Generates notifications when anomalies are detected based on data analysis results and emotion data.

[0347] Behavior: If an abnormal value is detected and the sentiment is unstable, a notification message is generated and linked to the notification system.

[0348] Input: Anomaly detection results and emotion analysis results

[0349] Output: Information message

[0350] Step 9:

[0351] Server: Sends alerts to the smartphones or tablets of relatives or caregivers through a notification system.

[0352] What it does: Sends real-time alerts using notification protocols (e.g., push notifications, SMS).

[0353] Input: Notification message

[0354] Output: Push notification to user device

[0355] Step 10:

[0356] Users: Receive notifications and view detailed data in an application on their smartphone or tablet.

[0357] What it does: Tap the push notification to open the app and check the abnormal data and emotional state.

[0358] Input: Push notification to user device

[0359] Output: Detailed data and emotional state displayed on the application

[0360] Step 11:

[0361] User: Contacting users or providing emergency response as needed.

[0362] How it works: Based on the notification, the system will contact the user via phone or messaging app and arrange for medical services or rescue operations depending on the situation.

[0363] Input: Detailed data and emotional state displayed on the application

[0364] Output: User's response actions (contact, medical assistance, rescue operation)

[0365] (Application example 2)

[0366] 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."

[0367] Monitoring the health and location information of elderly people and children in real time and responding promptly when abnormalities are detected is an important issue in today's society. However, existing monitoring systems are limited to simply monitoring data such as heart rate and body temperature, making it difficult to provide a comprehensive response that takes into account the user's emotional state. As a result, true emergencies can be overlooked or unnecessary alerts can be generated. Furthermore, there is a risk of delayed response in emergencies due to a lack of systems in place to enable relatives and caregivers to respond promptly.

[0368] 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 an AI analysis means for analyzing data measured by the sensor means, an emotion engine for analyzing the emotional state of the user, and a notification means for issuing an alert when an abnormality is detected. This makes it possible to comprehensively monitor the health and emotional states of elderly people and children, and to respond quickly when an abnormality occurs.

[0369] The "health monitoring system" is a system that monitors the health status and location information of elderly people and children in real time, and responds quickly when an abnormality is detected.

[0370] The "sensor means" is a device including various sensors for measuring heart rate, blood pressure, body temperature, location information, activity information, voice data, and facial expression data.

[0371] The "transmitting means" is a device that includes a communication module for transmitting data measured by the sensor device to the server.

[0372] The "AI analysis means" has the function of analyzing the data received by the server, comparing it with data within the normal range, and executing an algorithm to detect abnormal values ​​or abnormal behavior.

[0373] An "emotion engine" is a software engine that has the function of analyzing a user's voice data and facial expression data and recognizing the user's emotional state.

[0374] "Notification means" refers to a means for sending an alert to next of kin or caregivers when an abnormality is detected by the AI ​​analysis means and emotion engine.

[0375] "Communication means" refers to a means for informing relatives or caregivers of the health and emotional state of the elderly or child in real time via notification means.

[0376] "SOS Button Means" means a device that includes a button that allows a user or their next of kin to manually initiate an emergency alert in the event of an emergency.

[0377] The "wristband or necklace type sensor means" is a sensor device that can be easily worn in daily life and can measure heart rate, blood pressure, body temperature, location information, and activity information.

[0378] This is a health monitoring system that comprehensively monitors the health and emotional states of the elderly and children, enabling rapid response in the event of an abnormality. The basic components of this system are a wristband or necklace-type sensor device, a server, a notification means, and an SOS button means for emergency response.

[0379] 1. Sensor Devices

[0380] The sensor device includes various sensors for measuring heart rate, blood pressure, body temperature, location information, activity information, as well as voice and facial expression data. This allows it to acquire a wide range of data while being easy for elderly people and children to wear on a daily basis. The sensor device is equipped with a communication module for transmitting the measured data to a server.

[0381] 2. Server

[0382] The server receives and analyzes the data sent by the sensor device. This involves the use of an AI analysis means and emotion engine. The AI ​​analysis means analyzes the received health data in real time, comparing it with normal range data to detect outliers and abnormal behavior. The emotion engine analyzes voice data and facial expression data to identify the user's emotional state. If the server detects an abnormality based on this data, it immediately generates an alert.

[0383] 3. Means of notification

[0384] The notification mechanism is responsible for sending alerts generated by the server to next of kin or caregivers. Notifications are provided in real time via a smartphone or tablet application, allowing for immediate sharing of information about the time of the anomaly, detailed data, current location, and emotional state.

[0385] 4. Emergency Response Measures

[0386] The emergency response measures include an SOS button that can be manually operated by the user in an emergency, which immediately initiates an emergency call to request help.

[0387] The processing of the program for realizing this system will be explained below.

[0388] Program processing

[0389] The server receives data sent from the sensor device at regular intervals. The server first analyzes the health data using AI analysis tools to check for any abnormal values. Next, the emotion engine analyzes the voice and facial expression data to identify the user's emotional state. If an abnormality is detected, an alert is generated based on this information and sent promptly to next of kin or caregivers via notification tools. The notification includes the time the abnormality occurred, detailed health data, location information, and emotional state.

[0390] Hardware and software used

[0391] Sensor devices: Includes sensors for measuring heart rate, blood pressure, body temperature, location information, activity information, voice data, and facial expression data.

[0392] Server: Contains AI analysis tools and emotion engine.

[0393] Communication modules: Modules for sending data (e.g., the requests library).

[0394] Notification System: The system for sending alerts (e.g. NotificationSystem).

[0395] Specific examples

[0396] If an elderly person's heart rate is abnormally high and the emotion engine's stress emotion analysis results show a high value:

[0397] "User A's heart rate is abnormally high, and the stress emotion analysis results from the emotion engine indicate a high value. Their current location is ____. Please take appropriate action immediately."

[0398] If a child falls and the emotion engine detects emotion data that indicates fear or panic:

[0399] "A child has fallen and the emotion engine has detected emotion data indicating fear or panic. Current location: ____. Immediate response required."

[0400] This system will enable comprehensive monitoring of the health and emotional state of the elderly and children, and will enable prompt response if any abnormalities occur.

[0401] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0402] Step 1:

[0403] The sensor device measures the heart rate, blood pressure, body temperature, location information, activity information, voice data, and facial expression data of elderly people and children.

[0404] Input: Heart rate, blood pressure, body temperature, location information, activity information, voice data, facial expression data

[0405] Output: Measurement data

[0406] How it works: The sensor device is worn on the body of an elderly person or child, and the built-in sensors collect health and emotional data in real time.

[0407] Step 2:

[0408] The measurement data acquired by the sensor device is sent to the server.

[0409] Input: Measurement data

[0410] Output: Data sent to the server

[0411] Specific operation: Data is sent to the server at regular intervals using the communication module of the sensor device.

[0412] Step 3:

[0413] The data received by the server is analyzed using AI analysis methods.

[0414] Input: Measurement data

[0415] Output: Analysis results (health status)

[0416] Specific operation: An AI analysis tool running on the server analyzes the received data in real time and compares it with data within the normal range to detect any abnormalities.

[0417] Step 4:

[0418] The server uses an emotion engine to analyze voice data and facial expression data to identify the emotional state.

[0419] Input: Voice data, facial expression data

[0420] Output: Emotional state

[0421] How it works: The emotion engine on the server uses voice and image recognition technology to identify the user's emotional state (e.g., stress, anxiety, panic, etc.).

[0422] Step 5:

[0423] The server detects abnormalities based on the analysis results and emotional state.

[0424] Input: Analysis results, emotional state

[0425] Output: Abnormality detection

[0426] Specific behavior: Match the output of the AI ​​analysis method with the emotion engine to determine whether an abnormal health condition and a dangerous emotional state are detected simultaneously.

[0427] Step 6:

[0428] If the server detects an abnormality, it generates an alert.

[0429] Input: Anomaly detection results (health status and emotional state)

[0430] Output: Alert information

[0431] Specific behavior: When an anomaly is detected, the server generates alert information including the specific anomaly content, time, location information, and emotional state.

[0432] Step 7:

[0433] The server generates alert information and sends it to a close relative or caregiver via a notification means.

[0434] Input: Alert information

[0435] Output: Notification message (e.g. push notification)

[0436] Specific operation: Alert information is sent in real time via a smartphone application or email, and details of the abnormality are notified to next of kin or caregivers.

[0437] Step 8:

[0438] Relatives and caregivers will receive a notification message and take appropriate action.

[0439] Input: Notification message

[0440] Output: Carrying out care and emergency response

[0441] What it does: A push notification allows a relative or caregiver to use the app to view detailed health information and emotional state, and then respond or provide help if necessary.

[0442] This will enable real-time monitoring of the health and emotional state of the elderly and children, and rapid response if any abnormalities are detected.

[0443] 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.

[0444] 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.

[0445] 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.

[0446] [Second embodiment]

[0447] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0448] 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.

[0449] 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).

[0450] 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.

[0451] 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.

[0452] 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).

[0453] 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.

[0454] 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.

[0455] 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.

[0456] 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.

[0457] 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.

[0458] 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."

[0459] This invention is a system that monitors the health status and location information of elderly people and children in real time and promptly notifies users when an abnormality is detected. This system consists of three main components: a wristband or necklace-type sensor device, a server that analyzes the data, and the user who receives the notification.

[0460] 1. Sensor device (terminal)

[0461] The sensor device is equipped with various sensors necessary to measure heart rate, blood pressure, body temperature, location information, and activity information. This sensor device is provided in simple formats such as a wristband or necklace, so that elderly people and children can wear it on a daily basis without difficulty. The sensor device also has a communication module that transmits the measured data to a server.

[0462] The sensor device measures heart rate, blood pressure, and body temperature, for example, every 60 seconds, and temporarily stores the data in a buffer. This data is then sent to a server at regular intervals (for example, every 5 minutes). In the event of an emergency, the user can press the SOS button, and the data will be sent to the server immediately.

[0463] 2. Server (Central Management System)

[0464] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by an AI analysis means. The AI ​​analysis means compares the data with normal ranges and executes an algorithm to detect abnormal values ​​and abnormal behavior.

[0465] For example, if the heart rate is abnormal, the server will analyze the received heart rate data in detail and if it detects consecutive values ​​outside the normal range, it will determine that there is an abnormality. If such an abnormality is detected, the server will promptly send an alert to close relatives or caregivers via a notification means.

[0466] 3. Notification and Emergency Response (User)

[0467] Users (close relatives or caregivers) who receive alerts via notification methods can check the notifications in real time through a smartphone or tablet application. The alerts include the time when the abnormality occurred, detailed data, and current location information. Based on this information, users can take prompt action.

[0468] For example, if an elderly person's heart rate shows an abnormal value, the user will receive a push notification and can view the details in the app, after which they can contact the person directly or arrange for medical assistance if necessary.

[0469] Specific examples

[0470] Example 1: Detecting abnormal heart rates

[0471] 1. Device: The heart rate sensor measures the heart rate and sends the data to the server.

[0472] 2. Server: The server analyzes the received heart rate data and determines that an abnormality has occurred if a value outside the normal range is detected consecutively. If an abnormality is detected, an alert is issued.

[0473] 3. User: Next of kin receives an alert in the application, checks the details, assesses the situation, and if necessary, contacts the person directly to arrange medical services.

[0474] Example 2: Fall detection and notification

[0475] 1. Device: The accelerometer monitors the user's movements and detects abnormal acceleration (e.g., sudden acceleration or deceleration). If abnormal movement is detected, the data is sent to the server.

[0476] 2. Server: The server analyzes the received data and determines the possibility of a fall. It generates alert information for the fall detection and issues the alert via the notification means.

[0477] 3. User: Next of kin receive an alert in the application, check the detailed data, and if they determine that emergency response is required, they will contact them directly and respond promptly.

[0478] In this way, the system of the present invention can protect the health and safety of users by combining sensor devices that can be easily used by the elderly and children, a server that analyzes data in real time, and a notification means for rapid response.

[0479] The processing flow will be explained below.

[0480] Abnormal Heart Rate Detection Process

[0481] Step 1:

[0482] The device measures the heart rate using the heart rate sensor and temporarily stores the measurement data in a buffer.

[0483] Step 2:

[0484] The device sends the buffered heart rate data to the server at regular intervals (for example, every 5 minutes).

[0485] Step 3:

[0486] The server receives the heart rate data sent from the device and stores it in a database.

[0487] Step 4:

[0488] The heart rate data received by the server is analyzed using AI analysis tools, and abnormal values ​​are detected by comparing them with the normal range.

[0489] Step 5:

[0490] If the server detects an abnormal value, it generates alert information and issues an alert to close relatives or caregivers via a notification means.

[0491] Step 6:

[0492] Users receive alerts via an application on their smartphone or tablet, where they can view detailed data on abnormal heart rates.

[0493] Step 7:

[0494] The user assesses the situation and contacts the user or arranges for medical services if necessary.

[0495] Fall detection and notification process

[0496] Step 1:

[0497] The device uses an acceleration sensor to monitor the user's movements in real time and detect abnormal acceleration.

[0498] Step 2:

[0499] If the device detects abnormal acceleration, it immediately sends the data to the server.

[0500] Step 3:

[0501] The server receives the abnormal operation data sent from the device and stores the received data in a database.

[0502] Step 4:

[0503] The server analyzes the received data using AI analysis methods and determines that there is a high possibility of a fall.

[0504] Step 5:

[0505] The server generates alert information for the fall detection and notifies the next of kin or caregiver via the notification means.

[0506] Step 6:

[0507] Users can receive alerts via smartphone or tablet applications and check detailed data on fall detection.

[0508] Step 7:

[0509] If the user determines that an emergency response is required, the user will be contacted directly and help will be called for and responded to promptly.

[0510] Emergency Call Process

[0511] Step 1:

[0512] The device detects when the SOS button is pressed by the user and immediately sends emergency data to the server.

[0513] Step 2:

[0514] The server receives the emergency data sent from the device and stores the received data in a database.

[0515] Step 3:

[0516] The server generates emergency call alert information and immediately notifies the next of kin or caregiver via the notification means.

[0517] Step 4:

[0518] Users receive emergency alerts via smartphone or tablet applications and can view detailed emergency data.

[0519] Step 5:

[0520] The user assesses the situation and takes immediate action, arranging for medical services or emergency response if necessary.

[0521] Through the above processing steps, the system of the present invention can monitor the health and safety of the elderly and children in real time and respond quickly to abnormalities or emergencies.

[0522] Example 1

[0523] 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."

[0524] The goal is to monitor the health status and location information of vulnerable individuals, such as the elderly and children, in real time, and to take prompt and appropriate action when an abnormality occurs. However, existing systems make it difficult to respond quickly because the processes of data collection, communication, anomaly detection, and notification are not efficiently coordinated. In addition, many systems lack the ability to respond immediately in an emergency.

[0525] 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.

[0526] In this invention, the server includes sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information, transmission means for transmitting data measured by the sensor means to the server at regular intervals (for example, every 5 minutes), communication means for immediately transmitting data to the server when a user presses an SOS button operable by the user in an emergency, AI analysis means for receiving and analyzing the data transmitted by the transmission means and the emergency communication means, and notification means for promptly notifying close relatives or caregivers if an abnormality is detected by the AI ​​analysis means. This enables real-time health status monitoring, prompt notification in the event of an abnormality, and immediate response.

[0527] The "sensor means" refers to a device for measuring heart rate, blood pressure, body temperature, location information, activity information, and the like.

[0528] The "transmitting means" refers to a communication device for transmitting the data measured by the sensor means to a server at regular intervals.

[0529] "Communication means" refers to a device that allows a user to press an SOS button in an emergency to instantly send data to a server.

[0530] "AI analysis means" refers to an analytical device that uses artificial intelligence to analyze received data, compare it with the normal range, and detect abnormal values.

[0531] The "notification means" refers to a device that promptly notifies next of kin or caregivers when an abnormality is detected by the AI ​​analysis means.

[0532] This invention is a system that monitors the health status and location information of elderly people and children in real time and promptly notifies them when an abnormality is detected. This system consists of three main components: a wristband or necklace-type sensor device, a server that analyzes the data, and the user who receives the notification.

[0533] Sensor device (terminal)

[0534] The sensor device is equipped with various sensors to measure heart rate, blood pressure, body temperature, location information, and activity information. This sensor device is provided in simple formats such as wristbands and necklaces, and can be worn comfortably by the elderly and children on a daily basis. The sensor device also has a communication module that transmits the measured data to a server.

[0535] The device measures heart rate, blood pressure, and body temperature, for example, every 60 seconds, and temporarily stores the data in a buffer.The data is then sent to the server at regular intervals (for example, every 5 minutes).In the event of an emergency, the user can press the SOS button, and the data will be sent to the server immediately.

[0536] Server (central management system)

[0537] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by an AI analysis means. The AI ​​analysis means compares the data with normal ranges and executes an algorithm to detect abnormal values ​​and abnormal behavior.

[0538] For example, if the heart rate is abnormal, the server will analyze the received heart rate data in detail and if it detects consecutive values ​​outside the normal range, it will determine that there is an abnormality. If such an abnormality is detected, the server will promptly send an alert to close relatives or caregivers via a notification means.

[0539] Notification and Emergency Response (User)

[0540] Users (close relatives or caregivers) who receive alerts via notification methods can check the notifications in real time through a smartphone or tablet application. The alerts include the time when the abnormality occurred, detailed data, and current location information. Based on this information, users can take prompt action.

[0541] For example, if an elderly person's heart rate shows an abnormal value, the user will receive a push notification and can view the details in the app, after which they can contact the person directly or arrange for medical assistance if necessary.

[0542] Specific examples

[0543] Example 1: Detecting abnormal heart rates

[0544] 1. Device: The heart rate sensor measures the heart rate and sends the data to the server.

[0545] 2. Server: The server analyzes the received heart rate data and determines that an abnormality has occurred if a value outside the normal range is detected consecutively. If an abnormality is detected, an alert is issued.

[0546] 3. User: Next of kin receives an alert in the application, checks the details, assesses the situation, and if necessary, contacts the person directly to arrange medical services.

[0547] Example 2: Fall detection and notification

[0548] 1. Device: The accelerometer monitors the user's movements and detects abnormal acceleration (e.g., sudden acceleration or deceleration). If abnormal movement is detected, the data is sent to the server.

[0549] 2. Server: The server analyzes the received data and determines the possibility of a fall. It generates alert information for the fall detection and issues the alert via the notification means.

[0550] 3. User: Next of kin receive an alert in the application, check the detailed data, and if they determine that emergency response is required, they will contact them directly and respond promptly.

[0551] Prompt Sentence Examples

[0552] "If the user's heart rate is outside the normal range, activate an alert and notify next of kin."

[0553] "If the device's location information changes suddenly, send that data immediately and issue an alert if it determines there is a possibility of a fall."

[0554] In this way, the system of the present invention can protect the health and safety of the elderly and children in real time by combining sensor devices, a server that performs AI analysis, and notification means.

[0555] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0556] Step 1: Data collection (device)

[0557] The device operates various sensors to measure heart rate, blood pressure, body temperature, location information, and activity information. Specifically, the heart rate sensor measures heart rate every 60 seconds, and the blood pressure sensor measures blood pressure. These data are temporarily stored in a buffer within the device. Location information is also periodically updated using GPS and other location sensors. The input is vital information of the human body, and the output is sensor data stored in the buffer.

[0558] Step 2: Send data (terminal)

[0559] The communication module in the device sends the data stored in the buffer to the server at regular intervals (for example, every 5 minutes). In addition, in the event of an emergency, the user can press the SOS button, which immediately sends the data to the server. The input is the sensor data stored in the buffer, and the output is the transmitted data. Specifically, the communication module retrieves the data from the buffer and sends it to the server's receiving port.

[0560] Step 3: Receiving data (server)

[0561] The server receives data sent from the terminal. Specifically, the server constantly monitors the receiving port and waits for data to arrive. The input is the sensor data sent from the terminal, and the output is the received data. The received data is immediately saved in the database.

[0562] Step 4: Data analysis (server)

[0563] The AI ​​analysis algorithm in the server analyzes the received data by comparing it with normal ranges. For example, if consecutive abnormal heart rate values ​​are detected, it will flag them as an abnormality. The input is the sensor data stored in the database, and the output is the analysis result. Specifically, the AI ​​algorithm retrieves the data from the database and performs analysis.

[0564] Step 5: Alert generation (server)

[0565] If the server detects an abnormality, it will use the notification system to send an alert to relatives or caregivers. Specific operations include email, SMS, and app push notifications. The input is the result of the AI ​​analysis, and the output is the sent alert.

[0566] Step 6: Receiving and Confirming Notifications (User)

[0567] The user receives an alert notification on their smartphone or tablet. They can then check detailed data (such as the time the abnormality occurred and details of the heart rate) through the app. The input is the alert sent from the server, and the output is the detailed data displayed on the user's device. Specifically, the user opens the app and checks the alert content.

[0568] Step 7: Emergency Response (User)

[0569] After receiving an alert, the user checks the situation and takes necessary action, such as contacting the user directly or arranging for medical services. The input is the alert content and detailed data, and the output is the response action taken. Specific actions taken by the user include contacting the user by phone or messaging app.

[0570] (Application example 1)

[0571] 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."

[0572] Conventional health monitoring systems have difficulty monitoring the health status and location information of elderly people and children in real time, making it difficult to respond quickly when an abnormality occurs. Furthermore, there are cases where analysis of data sent from sensor devices and notifications are delayed, hindering emergency response. Furthermore, the system's operation is complicated, making it difficult for elderly people and children to use it on a daily basis.

[0573] 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.

[0574] In this invention, the server includes sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information, transmission means for transmitting data measured by the sensor means to the server, AI analysis means for receiving and analyzing the data transmitted by the transmission means, notification means for issuing an alert when an abnormality is detected by the AI ​​analysis means, SOS button means operable by the user in an emergency, transmission means configured to transmit part of the data to the server at specified intervals, a smartphone application for which the notification means issues push notifications, and means for notifying in real time when an abnormality is detected via the smartphone application. This makes it possible to monitor the health status and location information of elderly people and children in real time and to respond quickly and accurately when an abnormality occurs.

[0575] The "sensor means" is a device for measuring heart rate, blood pressure, body temperature, location information, and activity information.

[0576] The "transmitting means" is a device for transmitting data measured by the sensor means to the server.

[0577] "AI analysis means" refers to a device or system that uses artificial intelligence technology to receive and analyze data transmitted by the transmission means.

[0578] The "notification means" is a device or system that issues an alert to the user when an abnormality is detected by the AI ​​analysis means.

[0579] An "SOS button means" is a device having a button that can be operated by a user in an emergency, and operating this button sends an emergency notification.

[0580] A "smartphone application" is application software that runs on a smartphone and receives and displays push notifications from a notification means.

[0581] The "transmitting means configured to transmit data to a server at intervals" is a device having a function of transmitting a portion of data to a server at a set time interval.

[0582] "Means of real-time notification" refers to a function that immediately sends a notification via a smartphone application if an abnormality is detected.

[0583] This invention is a system that monitors the health status and location information of elderly people and children in real time and promptly notifies users when an abnormality is detected. This system consists of sensor devices, a server that analyzes the data, and users who receive notifications.

[0584] 1. Sensor device (terminal)

[0585] The terminal provides a wristband or necklace-type sensor means that can be worn daily by the elderly and children. This sensor device is equipped with various sensors to measure heart rate, blood pressure, body temperature, location information, and activity information, and temporarily stores these measured values ​​in a buffer at regular intervals. The sensor device also has a transmission means for sending the measured data to a server. It also has an SOS button means that the user can operate in the event of an emergency.

[0586] 2. Server (Central Management System)

[0587] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by the AI ​​analysis means. The AI ​​analysis means runs an algorithm that compares the data with normal health data to detect abnormal values ​​and behavior. This analysis is performed using software such as Python and Flask. If the notification means detects an abnormality, a push notification smartphone application will alert the user in real time. Notifications are sent using Google Firebase Cloud Messaging (FCM).

[0588] 3. User Notification and Emergency Response

[0589] The intended recipients of notifications are close relatives and caregivers. The smartphone application displays a push notification in real time when an abnormality occurs. The alert includes the time of the abnormality, detailed data, and the current location. After receiving the notification, the user can check the detailed data and take emergency action if necessary. For example, if an elderly person's heart rate shows an abnormal value, close relatives will receive a push notification and can check the detailed data in the application. They can then contact the user directly or arrange for medical services if necessary.

[0590] Specific examples

[0591] Consider the case where a 75-year-old person experiences an abnormally high heart rate while going about their daily life. At this time, the heart rate sensor detects the abnormal value and sends the data to the server. The server's AI analysis means analyzes the abnormal value and immediately detects the abnormality. The server then sends a push notification, which is sent in real time to the smartphones of close relatives.

[0592] Example prompt sentence:

[0593] Develop an application that monitors the heart rate and location of elderly people in real time and sends push notifications to their next of kin if an abnormality is detected. Use Python and Flask to receive data from sensor devices and include a function to send notifications via Firebase Cloud Messaging if an abnormal value is detected.

[0594] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0595] Step 1:

[0596] Data collection using sensor devices

[0597] The device's built-in sensors measure various data in real time, including heart rate, blood pressure, body temperature, location information, and activity information. This measurement data is temporarily stored in a buffer within the device.

[0598] Input: Heart rate, blood pressure, temperature, location, activity information

[0599] Output: Buffered sensor data

[0600] Step 2:

[0601] Data transmission

[0602] The terminal transmits data measured by the sensor means to the server at regular intervals (for example, every 5 minutes). In an emergency, the data is transmitted immediately when the SOS button means of the terminal is pressed.

[0603] Input: Buffered sensor data

[0604] Output: Sensor data sent to the server

[0605] Step 3:

[0606] Data reception and storage

[0607] The server receives the sensor data sent from the terminal and stores it in a database.

[0608] Input: Sensor data sent to the server

[0609] Output: Sensor data stored in a database

[0610] Step 4:

[0611] AI analysis

[0612] The server's AI analysis tools analyze the stored data in real time, compare it with normal data ranges, and run algorithms to detect outliers and abnormal behavior.

[0613] Input: Sensor data stored in a database

[0614] Output: Anomaly detection result (normal / abnormal)

[0615] Step 5:

[0616] Anomaly detection notification

[0617] If the AI ​​analysis method detects an abnormality, the server's notification method will send a push notification to the user. The push notification will include the time the abnormality occurred, detailed data, and the user's current location. Firebase Cloud Messaging (FCM) is used.

[0618] Input: Anomaly detection results

[0619] Output: A push notification that appears on the user's phone.

[0620] Step 6:

[0621] User Support

[0622] Users receive a notification on their smartphone app, view detailed data, assess the situation, and, if necessary, contact the user directly or arrange for medical assistance.

[0623] Input: Push notification displayed on smartphone

[0624] Output: User's response (contact, medical service arrangements, etc.)

[0625] 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.

[0626] This invention is a system that combines a system that monitors the health status and location information of elderly people and children in real time and quickly notifies users when an abnormality is detected with an emotion engine that recognizes the user's emotions. This system consists of a wristband or necklace-type sensor device, a server that analyzes the data, a user who receives notifications, and an emotion engine that recognizes the user's emotions.

[0627] 1. Sensor device (terminal)

[0628] The sensor device is equipped with various sensors necessary to measure heart rate, blood pressure, body temperature, location information, and activity information. This sensor device is provided in simple formats such as a wristband or necklace, so that elderly people and children can wear it on a daily basis without difficulty. The sensor device also has a communication module that transmits the measured data to a server.

[0629] 2. Server (Central Management System)

[0630] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by an AI analysis means. The AI ​​analysis means compares the data with normal ranges and executes an algorithm to detect abnormal values ​​and abnormal behavior.

[0631] The server also incorporates an emotion engine that analyzes the user's emotional state. The emotion engine recognizes the user's emotions by analyzing the user's voice data and facial expression data. This emotional information is also stored on the server and evaluated together with the analysis of the user's health status.

[0632] 3. Notification and Emergency Response (User)

[0633] Users (close relatives and caregivers) who receive alerts via notification methods can check the notifications in real time through a smartphone or tablet application. The alerts include the time of the abnormality, detailed data, current location information, and information about the user's emotional state. Based on this information, users can take prompt action.

[0634] For example, if an elderly person's heart rate shows abnormal values, the user will receive a push notification and can view the details and emotional state in the app, after which the user can be contacted directly or medical assistance can be arranged if necessary.

[0635] Specific examples

[0636] Example 1: Detecting abnormal heart rate with emotional fluctuations

[0637] 1. Device: The heart rate sensor measures the heart rate and sends the data to the server. The device also acquires the user's emotional data through voice recognition.

[0638] 2. Server: The server analyzes the received heart rate data and emotion data. If an abnormal value is detected, it evaluates the importance of the abnormality taking into account the emotion data.

[0639] 3. Server: If an abnormal heart rate is detected and the emotion engine detects emotional data indicating stress or anxiety, it generates alert information and sends an alert to close relatives or caregivers via notification means.

[0640] 4. User: Next of kin will receive a push notification to view detailed data and emotional state, assess the situation, contact the user if necessary, and arrange medical services.

[0641] Example 2: Fall and panic detection and notification

[0642] 1. Device: The accelerometer monitors the user's movements and detects abnormal acceleration. The voice recognition function also captures the user's emotional data (such as out-of-range tone of voice).

[0643] 2. Server: The server receives and analyzes the abnormal behavior data and emotion data. If it determines that there is a high possibility of a fall and the emotion engine detects emotion data indicating panic or fear, it generates an alert.

[0644] 3. Server: Notifies next of kin and caregivers of fall and panic alerts.

[0645] 4. User: Next of kin receives push notification to check abnormal behavior and emotional state, and responds quickly, arranging for help if necessary.

[0646] Specific program processing

[0647] The program processing is carried out in the following steps:

[0648] The sensor device measures heart rate, blood pressure, body temperature, location information, and activity information, and analyzes voice and facial expression data using an emotion engine. This data is sent to a server at regular intervals, and the server analyzes the received data using AI analysis means. In the event of an abnormality, an alert is generated taking into account the emotional information. Ultimately, a notification is sent to close relatives or caregivers, allowing for prompt action.

[0649] The system of the present invention can improve the safety and quality of life (QOL) of users by comprehensively monitoring the health status and emotions of elderly people and children.

[0650] The processing flow will be explained below.

[0651] Abnormal heart rate detection process combined with emotion engine

[0652] Step 1:

[0653] The device measures the heart rate using the heart rate sensor and temporarily stores the measurement data in a buffer.

[0654] Step 2:

[0655] The device uses its voice recognition function to acquire the user's voice data, analyzes it with its emotion engine, and temporarily stores the emotion data in a buffer.

[0656] Step 3:

[0657] The device sends the buffered heart rate data and emotion data to the server at regular intervals (e.g., every 5 minutes).

[0658] Step 4:

[0659] The server receives the heart rate data and emotion data sent from the device and stores the received data in a database.

[0660] Step 5:

[0661] The heart rate data received by the server is analyzed using AI analysis tools, and abnormal values ​​are detected by comparing them with the normal range.

[0662] Step 6:

[0663] The server analyzes the received emotional data to determine the user's emotional state, for example, detecting data indicating stress or anxiety.

[0664] Step 7:

[0665] The server comprehensively evaluates abnormal heart rate values ​​and emotional data to determine the importance of the abnormality.

[0666] Step 8:

[0667] If the server detects abnormal heart rate and emotions associated with stress or anxiety, it generates an alert with detailed data (heart rate, emotional state, time, and location).

[0668] Step 9:

[0669] The server issues an alert to the next of kin or caregiver via the notification means.

[0670] Step 10:

[0671] Users receive alerts via a smartphone or tablet application, where they can view detailed data on abnormal heart rates and emotional states.

[0672] Step 11:

[0673] The user assesses the situation and contacts the user or arranges for medical services if necessary.

[0674] Fall detection and notification process combined with emotion engine

[0675] Step 1:

[0676] The device uses an acceleration sensor to monitor the user's movements in real time and detect abnormal acceleration.

[0677] Step 2:

[0678] The device uses its voice recognition function to acquire the user's voice data, analyzes it with its emotion engine, and temporarily stores the emotion data in a buffer.

[0679] Step 3:

[0680] If the device detects abnormal acceleration, it immediately sends that data to the server, along with emotion data.

[0681] Step 4:

[0682] The server receives abnormal behavior data and emotion data sent from the device and stores them in a database.

[0683] Step 5:

[0684] The server analyzes the abnormal movement data using AI analysis methods and determines that there is a high possibility of a fall.

[0685] Step 6:

[0686] The server analyzes the emotional data to determine if the user is exhibiting panic or fear.

[0687] Step 7:

[0688] The server comprehensively assesses the likelihood of falling and the emotional state and determines the importance.

[0689] Step 8:

[0690] If the server detects a fall and emotions associated with panic or fear, it generates an alert containing detailed data (abnormal behavior, emotional state, time, and location information).

[0691] Step 9:

[0692] The server notifies the alert information to the next of kin or caregiver via the notification means.

[0693] Step 10:

[0694] Users receive alerts via a smartphone or tablet application, and can view detailed data on fall detection and emotional state.

[0695] Step 11:

[0696] If the user determines that an emergency response is required, we will promptly arrange for rescue and contact the user directly to confirm the situation.

[0697] In this way, the system of the present invention is designed to monitor not only the health status of elderly people and children but also their emotional state in real time, and to respond quickly to abnormalities or emergencies.

[0698] Example 2

[0699] 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."

[0700] In modern society, there is a growing demand for real-time monitoring of the safety and health of the elderly and children. However, current systems do not adequately detect abnormalities that take into account the user's emotional state, which can lead to delayed responses when an abnormality occurs. Furthermore, systems that simply measure biometric data have the challenge of making it difficult to respond appropriately to psychological states such as stress and anxiety in users.

[0701] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0702] In this invention, the server includes an AI analysis unit, an emotion engine unit, and a notification unit, which enables real-time detection of abnormalities and rapid response while taking into account both biometric data and emotion data.

[0703] The "sensor means" is a device for measuring biological data such as heart rate, blood pressure, body temperature, location information, and activity information.

[0704] The "transmitting means" is a communication device for transmitting data measured by the sensor means to the server.

[0705] "AI analysis means" refers to an artificial intelligence algorithm that analyzes received data in real time, compares it with normal ranges, and detects abnormal values ​​and behavior.

[0706] The "notification means" is a device that issues an alert to the user when an abnormality is detected by the AI ​​analysis means.

[0707] The "SOS button means" is a device that can be operated by a user to send an SOS signal in an emergency.

[0708] The "emotion engine means" is an algorithm for analyzing the user's voice and facial expression data and recognizing the user's emotional state.

[0709] An "alert" is a warning message that is sent to the user or a close relative when an abnormality is detected.

[0710] An "interval" is a specified time interval for sending data to the server.

[0711] This system monitors the health status and location information of elderly people and children in real time and promptly notifies users when abnormalities are detected. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to comprehensively evaluate both biometric data and emotion data. This system consists of a wristband or necklace-style sensor device, a server that analyzes the data, a user who receives notifications, and an emotion engine that recognizes the user's emotions.

[0712] 1. Sensor device (terminal)

[0713] The sensor device is equipped with sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information. This sensor device is available in the form of a wristband or necklace, making it easy for elderly people and children to wear on a daily basis. It also has a voice recognition function and a camera function for capturing voice and facial expression data. The sensor device also includes a communication module for transmitting the measured data to a server.

[0714] 2. Server (Central Management System)

[0715] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by AI analysis means. The AI ​​analysis means compares biometric data such as heart rate, blood pressure, body temperature, location information, and activity information with normal range data and executes algorithms to detect abnormal values ​​and behavior. The server also incorporates an emotion engine, which has the function of analyzing the user's emotional state. The emotion engine recognizes the user's emotions by analyzing the user's voice data and facial expression data. This emotional information is also stored on the server and is comprehensively evaluated along with an analysis of the user's health status.

[0716] 3. Notification and Emergency Response (User)

[0717] Users (close relatives and caregivers) who receive alerts via notification methods can check the notifications in real time through a smartphone or tablet application. The alerts include the time of the abnormality, detailed data, current location information, and information about the user's emotional state. Based on this information, users can take prompt action.

[0718] For example, if an elderly person's heart rate shows abnormal values, the user will receive a push notification and can view the details and emotional state in the app, after which the user can be contacted directly or medical assistance can be arranged if necessary.

[0719] Specific examples

[0720] Example 1: Detecting abnormal heart rate with emotional fluctuations

[0721] 1. Device: The heart rate sensor measures the heart rate and sends the data to the server. The device also acquires the user's emotional data through voice recognition.

[0722] 2. Server: The server analyzes the received heart rate data and emotion data. If an abnormal value is detected, it evaluates the importance of the abnormality taking into account the emotion data.

[0723] 3. Server: If an abnormal heart rate is detected and the emotion engine detects emotional data indicating stress or anxiety, it generates alert information and sends an alert to close relatives or caregivers via notification means.

[0724] 4. User: Next of kin will receive a push notification to view detailed data and emotional state, assess the situation, contact the user if necessary, and arrange medical services.

[0725] Example 2: Fall and panic detection and notification

[0726] 1. Device: The accelerometer monitors the user's movements and detects abnormal acceleration. The voice recognition function also captures the user's emotional data (such as out-of-range tone of voice).

[0727] 2. Server: The server receives and analyzes the abnormal behavior data and emotion data. If it determines that there is a high possibility of a fall and the emotion engine detects emotion data indicating panic or fear, it generates an alert.

[0728] 3. Server: Notifies next of kin and caregivers of fall and panic alerts.

[0729] 4. User: Next of kin receives push notification to check abnormal behavior and emotional state, and responds quickly, arranging for help if necessary.

[0730] Example prompt

[0731] "Describe a scenario in which you want to detect abnormal heart rates and emotional fluctuations in an elderly person."

[0732] "How do you alert me when my child falls and panics?"

[0733] This system comprehensively monitors the health and emotions of elderly people and children, improving the safety and quality of life of users.

[0734] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0735] Step 1:

[0736] Device: Measures heart rate, blood pressure, body temperature, location, and activity information.

[0737] How it works: Various sensors installed on the device continuously monitor the user's biometric data and collect data at regular intervals.

[0738] Input: User's biological status (heart rate, blood pressure, body temperature, location information, activity information)

[0739] Output: Biometric data set (heart rate, blood pressure, temperature, location, activity)

[0740] Step 2:

[0741] Terminal: Analyzes voice and facial expression data using an emotion engine to generate emotion data.

[0742] How it works: Using voice recognition and camera functions, the user's tone of voice and facial expressions are collected and analyzed by the emotion engine.

[0743] Input: User's voice data and image data (facial expressions)

[0744] Output: Emotion data (stress, anxiety, joy, etc.)

[0745] Step 3:

[0746] Terminal: Sends collected sensor data and emotion data to the server via the communication module.

[0747] Operation: Data is collected within the sensor device and transferred to the server via wireless communication (Wi-Fi, Bluetooth, etc.).

[0748] Input: Biometric dataset and emotion data

[0749] Output: Data packets (biometric dataset, emotion data) to the server

[0750] Step 4:

[0751] Server: The server receives the data sent from the device.

[0752] Operation: The server receives data via the communication protocol and stores it in a receive buffer.

[0753] Input: Data packets sent from the device

[0754] Output: Raw data in the receive buffer

[0755] Step 5:

[0756] Server: Stores the received data in a database.

[0757] How it works: Connects to a database and stores data by time.

[0758] Input: Raw data in the receive buffer

[0759] Output: Structured data stored in a database

[0760] Step 6:

[0761] Server: Analyzes the stored data in real time using AI analysis methods.

[0762] How it works: It uses AI models to analyze biometric data and compare it to normal ranges. If an abnormality is detected, it highlights it.

[0763] Input: Structured data in a database

[0764] Output: Abnormality detection result and its detailed data

[0765] Step 7:

[0766] Server: The emotion engine analyzes voice and facial expression data to recognize the user's emotional state.

[0767] How it works: The emotion engine analyzes subtle changes in vocal tone and facial expressions to determine emotional states (e.g., stress, joy, anxiety).

[0768] Input: Voice and facial expression data in the database

[0769] Output: Emotion analysis results

[0770] Step 8:

[0771] Server: Generates notifications when anomalies are detected based on data analysis results and emotion data.

[0772] Behavior: If an abnormal value is detected and the sentiment is unstable, a notification message is generated and linked to the notification system.

[0773] Input: Anomaly detection results and emotion analysis results

[0774] Output: Information message

[0775] Step 9:

[0776] Server: Sends alerts to the smartphones or tablets of relatives or caregivers through a notification system.

[0777] What it does: Sends real-time alerts using notification protocols (e.g., push notifications, SMS).

[0778] Input: Notification message

[0779] Output: Push notification to user device

[0780] Step 10:

[0781] Users: Receive notifications and view detailed data in an application on their smartphone or tablet.

[0782] What it does: Tap the push notification to open the app and check the abnormal data and emotional state.

[0783] Input: Push notification to user device

[0784] Output: Detailed data and emotional state displayed on the application

[0785] Step 11:

[0786] User: Contacting users or providing emergency response as needed.

[0787] How it works: Based on the notification, the system will contact the user via phone or messaging app and arrange for medical services or rescue operations depending on the situation.

[0788] Input: Detailed data and emotional state displayed on the application

[0789] Output: User's response actions (contact, medical assistance, rescue operation)

[0790] (Application example 2)

[0791] 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."

[0792] Monitoring the health and location information of elderly people and children in real time and responding promptly when abnormalities are detected is an important issue in today's society. However, existing monitoring systems are limited to simply monitoring data such as heart rate and body temperature, making it difficult to provide a comprehensive response that takes into account the user's emotional state. As a result, true emergencies can be overlooked or unnecessary alerts can be generated. Furthermore, there is a risk of delayed response in emergencies due to a lack of systems in place to enable relatives and caregivers to respond promptly.

[0793] 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 an AI analysis means for analyzing data measured by the sensor means, an emotion engine for analyzing the emotional state of the user, and a notification means for issuing an alert when an abnormality is detected. This makes it possible to comprehensively monitor the health and emotional states of elderly people and children, and to respond quickly when an abnormality occurs.

[0794] The "health monitoring system" is a system that monitors the health status and location information of elderly people and children in real time, and responds quickly when an abnormality is detected.

[0795] The "sensor means" is a device including various sensors for measuring heart rate, blood pressure, body temperature, location information, activity information, voice data, and facial expression data.

[0796] The "transmitting means" is a device that includes a communication module for transmitting data measured by the sensor device to the server.

[0797] The "AI analysis means" has the function of analyzing the data received by the server, comparing it with data within the normal range, and executing an algorithm to detect abnormal values ​​or abnormal behavior.

[0798] An "emotion engine" is a software engine that has the function of analyzing a user's voice data and facial expression data and recognizing the user's emotional state.

[0799] "Notification means" refers to a means for sending an alert to next of kin or caregivers when an abnormality is detected by the AI ​​analysis means and emotion engine.

[0800] "Communication means" refers to a means for informing relatives or caregivers of the health and emotional state of the elderly or child in real time via notification means.

[0801] "SOS Button Means" means a device that includes a button that allows a user or their next of kin to manually initiate an emergency alert in the event of an emergency.

[0802] The "wristband or necklace type sensor means" is a sensor device that can be easily worn in daily life and can measure heart rate, blood pressure, body temperature, location information, and activity information.

[0803] This is a health monitoring system that comprehensively monitors the health and emotional states of the elderly and children, enabling rapid response in the event of an abnormality. The basic components of this system are a wristband or necklace-type sensor device, a server, a notification means, and an SOS button means for emergency response.

[0804] 1. Sensor Devices

[0805] The sensor device includes various sensors for measuring heart rate, blood pressure, body temperature, location information, activity information, as well as voice and facial expression data. This allows it to acquire a wide range of data while being easy for elderly people and children to wear on a daily basis. The sensor device is equipped with a communication module for transmitting the measured data to a server.

[0806] 2. Server

[0807] The server receives and analyzes the data sent by the sensor device. This involves the use of an AI analysis means and emotion engine. The AI ​​analysis means analyzes the received health data in real time, comparing it with normal range data to detect outliers and abnormal behavior. The emotion engine analyzes voice data and facial expression data to identify the user's emotional state. If the server detects an abnormality based on this data, it immediately generates an alert.

[0808] 3. Means of notification

[0809] The notification mechanism is responsible for sending alerts generated by the server to next of kin or caregivers. Notifications are provided in real time via a smartphone or tablet application, allowing for immediate sharing of information about the time of the anomaly, detailed data, current location, and emotional state.

[0810] 4. Emergency Response Measures

[0811] The emergency response measures include an SOS button that can be manually operated by the user in an emergency, which immediately initiates an emergency call to request help.

[0812] The processing of the program for realizing this system will be explained below.

[0813] Program processing

[0814] The server receives data sent from the sensor device at regular intervals. The server first analyzes the health data using AI analysis tools to check for any abnormal values. Next, the emotion engine analyzes the voice and facial expression data to identify the user's emotional state. If an abnormality is detected, an alert is generated based on this information and sent promptly to next of kin or caregivers via notification tools. The notification includes the time the abnormality occurred, detailed health data, location information, and emotional state.

[0815] Hardware and software used

[0816] Sensor devices: Includes sensors for measuring heart rate, blood pressure, body temperature, location information, activity information, voice data, and facial expression data.

[0817] Server: Contains AI analysis tools and emotion engine.

[0818] Communication modules: Modules for sending data (e.g., the requests library).

[0819] Notification System: The system for sending alerts (e.g. NotificationSystem).

[0820] Specific examples

[0821] If an elderly person's heart rate is abnormally high and the emotion engine's stress emotion analysis results show a high value:

[0822] "User A's heart rate is abnormally high, and the stress emotion analysis results from the emotion engine indicate a high value. Their current location is ____. Please take appropriate action immediately."

[0823] If a child falls and the emotion engine detects emotion data that indicates fear or panic:

[0824] "A child has fallen and the emotion engine has detected emotion data indicating fear or panic. Current location: ____. Immediate response required."

[0825] This system will enable comprehensive monitoring of the health and emotional state of the elderly and children, and will enable prompt response if any abnormalities occur.

[0826] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0827] Step 1:

[0828] The sensor device measures the heart rate, blood pressure, body temperature, location information, activity information, voice data, and facial expression data of elderly people and children.

[0829] Input: Heart rate, blood pressure, body temperature, location information, activity information, voice data, facial expression data

[0830] Output: Measurement data

[0831] How it works: The sensor device is worn on the body of an elderly person or child, and the built-in sensors collect health and emotional data in real time.

[0832] Step 2:

[0833] The measurement data acquired by the sensor device is sent to the server.

[0834] Input: Measurement data

[0835] Output: Data sent to the server

[0836] Specific operation: Data is sent to the server at regular intervals using the communication module of the sensor device.

[0837] Step 3:

[0838] The data received by the server is analyzed using AI analysis methods.

[0839] Input: Measurement data

[0840] Output: Analysis results (health status)

[0841] Specific operation: An AI analysis tool running on the server analyzes the received data in real time and compares it with data within the normal range to detect any abnormalities.

[0842] Step 4:

[0843] The server uses an emotion engine to analyze voice data and facial expression data to identify the emotional state.

[0844] Input: Voice data, facial expression data

[0845] Output: Emotional state

[0846] How it works: The emotion engine on the server uses voice and image recognition technology to identify the user's emotional state (e.g., stress, anxiety, panic, etc.).

[0847] Step 5:

[0848] The server detects abnormalities based on the analysis results and emotional state.

[0849] Input: Analysis results, emotional state

[0850] Output: Abnormality detection

[0851] Specific behavior: Match the output of the AI ​​analysis method with the emotion engine to determine whether an abnormal health condition and a dangerous emotional state are detected simultaneously.

[0852] Step 6:

[0853] If the server detects an abnormality, it generates an alert.

[0854] Input: Anomaly detection results (health status and emotional state)

[0855] Output: Alert information

[0856] Specific behavior: When an anomaly is detected, the server generates alert information including the specific anomaly content, time, location information, and emotional state.

[0857] Step 7:

[0858] The server generates alert information and sends it to a close relative or caregiver via a notification means.

[0859] Input: Alert information

[0860] Output: Notification message (e.g. push notification)

[0861] Specific operation: Alert information is sent in real time via a smartphone application or email, and details of the abnormality are notified to next of kin or caregivers.

[0862] Step 8:

[0863] Relatives and caregivers will receive a notification message and take appropriate action.

[0864] Input: Notification message

[0865] Output: Carrying out care and emergency response

[0866] What it does: A push notification allows a relative or caregiver to use the app to view detailed health information and emotional state, and then respond or provide help if necessary.

[0867] This will enable real-time monitoring of the health and emotional state of the elderly and children, and rapid response if any abnormalities are detected.

[0868] 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.

[0869] 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.

[0870] 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.

[0871] [Third embodiment]

[0872] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0873] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0874] 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).

[0875] 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.

[0876] 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.

[0877] 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).

[0878] 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.

[0879] 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.

[0880] 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.

[0881] 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.

[0882] 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.

[0883] 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."

[0884] This invention is a system that monitors the health status and location information of elderly people and children in real time and promptly notifies users when an abnormality is detected. This system consists of three main components: a wristband or necklace-type sensor device, a server that analyzes the data, and the user who receives the notification.

[0885] 1. Sensor device (terminal)

[0886] The sensor device is equipped with various sensors necessary to measure heart rate, blood pressure, body temperature, location information, and activity information. This sensor device is provided in simple formats such as a wristband or necklace, so that elderly people and children can wear it on a daily basis without difficulty. The sensor device also has a communication module that transmits the measured data to a server.

[0887] The sensor device measures heart rate, blood pressure, and body temperature, for example, every 60 seconds, and temporarily stores the data in a buffer. This data is then sent to a server at regular intervals (for example, every 5 minutes). In the event of an emergency, the user can press the SOS button, and the data will be sent to the server immediately.

[0888] 2. Server (Central Management System)

[0889] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by an AI analysis means. The AI ​​analysis means compares the data with normal ranges and executes an algorithm to detect abnormal values ​​and abnormal behavior.

[0890] For example, if the heart rate is abnormal, the server will analyze the received heart rate data in detail and if it detects consecutive values ​​outside the normal range, it will determine that there is an abnormality. If such an abnormality is detected, the server will promptly send an alert to close relatives or caregivers via a notification means.

[0891] 3. Notification and Emergency Response (User)

[0892] Users (close relatives or caregivers) who receive alerts via notification methods can check the notifications in real time through a smartphone or tablet application. The alerts include the time when the abnormality occurred, detailed data, and current location information. Based on this information, users can take prompt action.

[0893] For example, if an elderly person's heart rate shows an abnormal value, the user will receive a push notification and can view the details in the app, after which they can contact the person directly or arrange for medical assistance if necessary.

[0894] Specific examples

[0895] Example 1: Detecting abnormal heart rates

[0896] 1. Device: The heart rate sensor measures the heart rate and sends the data to the server.

[0897] 2. Server: The server analyzes the received heart rate data and determines that an abnormality has occurred if a value outside the normal range is detected consecutively. If an abnormality is detected, an alert is issued.

[0898] 3. User: Next of kin receives an alert in the application, checks the details, assesses the situation, and if necessary, contacts the person directly to arrange medical services.

[0899] Example 2: Fall detection and notification

[0900] 1. Device: The accelerometer monitors the user's movements and detects abnormal acceleration (e.g., sudden acceleration or deceleration). If abnormal movement is detected, the data is sent to the server.

[0901] 2. Server: The server analyzes the received data and determines the possibility of a fall. It generates alert information for the fall detection and issues the alert via the notification means.

[0902] 3. User: Next of kin receive an alert in the application, check the detailed data, and if they determine that emergency response is required, they will contact them directly and respond promptly.

[0903] In this way, the system of the present invention can protect the health and safety of users by combining sensor devices that can be easily used by the elderly and children, a server that analyzes data in real time, and a notification means for rapid response.

[0904] The processing flow will be explained below.

[0905] Abnormal Heart Rate Detection Process

[0906] Step 1:

[0907] The device measures the heart rate using the heart rate sensor and temporarily stores the measurement data in a buffer.

[0908] Step 2:

[0909] The device sends the buffered heart rate data to the server at regular intervals (for example, every 5 minutes).

[0910] Step 3:

[0911] The server receives the heart rate data sent from the device and stores it in a database.

[0912] Step 4:

[0913] The heart rate data received by the server is analyzed using AI analysis tools, and abnormal values ​​are detected by comparing them with the normal range.

[0914] Step 5:

[0915] If the server detects an abnormal value, it generates alert information and issues an alert to close relatives or caregivers via a notification means.

[0916] Step 6:

[0917] Users receive alerts via an application on their smartphone or tablet, where they can view detailed data on abnormal heart rates.

[0918] Step 7:

[0919] The user assesses the situation and contacts the user or arranges for medical services if necessary.

[0920] Fall detection and notification process

[0921] Step 1:

[0922] The device uses an acceleration sensor to monitor the user's movements in real time and detect abnormal acceleration.

[0923] Step 2:

[0924] If the device detects abnormal acceleration, it immediately sends the data to the server.

[0925] Step 3:

[0926] The server receives the abnormal operation data sent from the device and stores the received data in a database.

[0927] Step 4:

[0928] The server analyzes the received data using AI analysis methods and determines that there is a high possibility of a fall.

[0929] Step 5:

[0930] The server generates alert information for the fall detection and notifies the next of kin or caregiver via the notification means.

[0931] Step 6:

[0932] Users can receive alerts via smartphone or tablet applications and check detailed data on fall detection.

[0933] Step 7:

[0934] If the user determines that an emergency response is required, the user will be contacted directly and help will be called for and responded to promptly.

[0935] Emergency Call Process

[0936] Step 1:

[0937] The device detects when the SOS button is pressed by the user and immediately sends emergency data to the server.

[0938] Step 2:

[0939] The server receives the emergency data sent from the device and stores the received data in a database.

[0940] Step 3:

[0941] The server generates emergency call alert information and immediately notifies the next of kin or caregiver via the notification means.

[0942] Step 4:

[0943] Users receive emergency alerts via smartphone or tablet applications and can view detailed emergency data.

[0944] Step 5:

[0945] The user assesses the situation and takes immediate action, arranging for medical services or emergency response if necessary.

[0946] Through the above processing steps, the system of the present invention can monitor the health and safety of the elderly and children in real time and respond quickly to abnormalities or emergencies.

[0947] Example 1

[0948] 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."

[0949] The goal is to monitor the health status and location information of vulnerable individuals, such as the elderly and children, in real time, and to take prompt and appropriate action when an abnormality occurs. However, existing systems make it difficult to respond quickly because the processes of data collection, communication, anomaly detection, and notification are not efficiently coordinated. In addition, many systems lack the ability to respond immediately in an emergency.

[0950] 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.

[0951] In this invention, the server includes sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information, transmission means for transmitting data measured by the sensor means to the server at regular intervals (for example, every 5 minutes), communication means for immediately transmitting data to the server when a user presses an SOS button operable by the user in an emergency, AI analysis means for receiving and analyzing the data transmitted by the transmission means and the emergency communication means, and notification means for promptly notifying close relatives or caregivers if an abnormality is detected by the AI ​​analysis means. This enables real-time health status monitoring, prompt notification in the event of an abnormality, and immediate response.

[0952] The "sensor means" refers to a device for measuring heart rate, blood pressure, body temperature, location information, activity information, and the like.

[0953] The "transmitting means" refers to a communication device for transmitting the data measured by the sensor means to a server at regular intervals.

[0954] "Communication means" refers to a device that allows a user to press an SOS button in an emergency to instantly send data to a server.

[0955] "AI analysis means" refers to an analytical device that uses artificial intelligence to analyze received data, compare it with the normal range, and detect abnormal values.

[0956] The "notification means" refers to a device that promptly notifies next of kin or caregivers when an abnormality is detected by the AI ​​analysis means.

[0957] This invention is a system that monitors the health status and location information of elderly people and children in real time and promptly notifies them when an abnormality is detected. This system consists of three main components: a wristband or necklace-type sensor device, a server that analyzes the data, and the user who receives the notification.

[0958] Sensor device (terminal)

[0959] The sensor device is equipped with various sensors to measure heart rate, blood pressure, body temperature, location information, and activity information. This sensor device is provided in simple formats such as wristbands and necklaces, and can be worn comfortably by the elderly and children on a daily basis. The sensor device also has a communication module that transmits the measured data to a server.

[0960] The device measures heart rate, blood pressure, and body temperature, for example, every 60 seconds, and temporarily stores the data in a buffer.The data is then sent to the server at regular intervals (for example, every 5 minutes).In the event of an emergency, the user can press the SOS button, and the data will be sent to the server immediately.

[0961] Server (central management system)

[0962] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by an AI analysis means. The AI ​​analysis means compares the data with normal ranges and executes an algorithm to detect abnormal values ​​and abnormal behavior.

[0963] For example, if the heart rate is abnormal, the server will analyze the received heart rate data in detail and if it detects consecutive values ​​outside the normal range, it will determine that there is an abnormality. If such an abnormality is detected, the server will promptly send an alert to close relatives or caregivers via a notification means.

[0964] Notification and Emergency Response (User)

[0965] Users (close relatives or caregivers) who receive alerts via notification methods can check the notifications in real time through a smartphone or tablet application. The alerts include the time when the abnormality occurred, detailed data, and current location information. Based on this information, users can take prompt action.

[0966] For example, if an elderly person's heart rate shows an abnormal value, the user will receive a push notification and can view the details in the app, after which they can contact the person directly or arrange for medical assistance if necessary.

[0967] Specific examples

[0968] Example 1: Detecting abnormal heart rates

[0969] 1. Device: The heart rate sensor measures the heart rate and sends the data to the server.

[0970] 2. Server: The server analyzes the received heart rate data and determines that an abnormality has occurred if a value outside the normal range is detected consecutively. If an abnormality is detected, an alert is issued.

[0971] 3. User: Next of kin receives an alert in the application, checks the details, assesses the situation, and if necessary, contacts the person directly to arrange medical services.

[0972] Example 2: Fall detection and notification

[0973] 1. Device: The accelerometer monitors the user's movements and detects abnormal acceleration (e.g., sudden acceleration or deceleration). If abnormal movement is detected, the data is sent to the server.

[0974] 2. Server: The server analyzes the received data and determines the possibility of a fall. It generates alert information for the fall detection and issues the alert via the notification means.

[0975] 3. User: Next of kin receive an alert in the application, check the detailed data, and if they determine that emergency response is required, they will contact them directly and respond promptly.

[0976] Prompt Sentence Examples

[0977] "If the user's heart rate is outside the normal range, activate an alert and notify next of kin."

[0978] "If the device's location information changes suddenly, send that data immediately and issue an alert if it determines there is a possibility of a fall."

[0979] In this way, the system of the present invention can protect the health and safety of the elderly and children in real time by combining sensor devices, a server that performs AI analysis, and notification means.

[0980] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0981] Step 1: Data collection (device)

[0982] The device operates various sensors to measure heart rate, blood pressure, body temperature, location information, and activity information. Specifically, the heart rate sensor measures heart rate every 60 seconds, and the blood pressure sensor measures blood pressure. These data are temporarily stored in a buffer within the device. Location information is also periodically updated using GPS and other location sensors. The input is vital information of the human body, and the output is sensor data stored in the buffer.

[0983] Step 2: Send data (terminal)

[0984] The communication module in the device sends the data stored in the buffer to the server at regular intervals (for example, every 5 minutes). In addition, in the event of an emergency, the user can press the SOS button, which immediately sends the data to the server. The input is the sensor data stored in the buffer, and the output is the transmitted data. Specifically, the communication module retrieves the data from the buffer and sends it to the server's receiving port.

[0985] Step 3: Receiving data (server)

[0986] The server receives data sent from the terminal. Specifically, the server constantly monitors the receiving port and waits for data to arrive. The input is the sensor data sent from the terminal, and the output is the received data. The received data is immediately saved in the database.

[0987] Step 4: Data analysis (server)

[0988] The AI ​​analysis algorithm in the server analyzes the received data by comparing it with normal ranges. For example, if consecutive abnormal heart rate values ​​are detected, it will flag them as an abnormality. The input is the sensor data stored in the database, and the output is the analysis result. Specifically, the AI ​​algorithm retrieves the data from the database and performs analysis.

[0989] Step 5: Alert generation (server)

[0990] If the server detects an abnormality, it will use the notification system to send an alert to relatives or caregivers. Specific operations include email, SMS, and app push notifications. The input is the result of the AI ​​analysis, and the output is the sent alert.

[0991] Step 6: Receiving and Confirming Notifications (User)

[0992] The user receives an alert notification on their smartphone or tablet. They can then check detailed data (such as the time the abnormality occurred and details of the heart rate) through the app. The input is the alert sent from the server, and the output is the detailed data displayed on the user's device. Specifically, the user opens the app and checks the alert content.

[0993] Step 7: Emergency Response (User)

[0994] After receiving an alert, the user checks the situation and takes necessary action, such as contacting the user directly or arranging for medical services. The input is the alert content and detailed data, and the output is the response action taken. Specific actions taken by the user include contacting the user by phone or messaging app.

[0995] (Application example 1)

[0996] 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."

[0997] Conventional health monitoring systems have difficulty monitoring the health status and location information of elderly people and children in real time, making it difficult to respond quickly when an abnormality occurs. Furthermore, there are cases where analysis of data sent from sensor devices and notifications are delayed, hindering emergency response. Furthermore, the system's operation is complicated, making it difficult for elderly people and children to use it on a daily basis.

[0998] 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.

[0999] In this invention, the server includes sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information, transmission means for transmitting data measured by the sensor means to the server, AI analysis means for receiving and analyzing the data transmitted by the transmission means, notification means for issuing an alert when an abnormality is detected by the AI ​​analysis means, SOS button means operable by the user in an emergency, transmission means configured to transmit part of the data to the server at specified intervals, a smartphone application for which the notification means issues push notifications, and means for notifying in real time when an abnormality is detected via the smartphone application. This makes it possible to monitor the health status and location information of elderly people and children in real time and to respond quickly and accurately when an abnormality occurs.

[1000] The "sensor means" is a device for measuring heart rate, blood pressure, body temperature, location information, and activity information.

[1001] The "transmitting means" is a device for transmitting data measured by the sensor means to the server.

[1002] "AI analysis means" refers to a device or system that uses artificial intelligence technology to receive and analyze data transmitted by the transmission means.

[1003] The "notification means" is a device or system that issues an alert to the user when an abnormality is detected by the AI ​​analysis means.

[1004] An "SOS button means" is a device having a button that can be operated by a user in an emergency, and operating this button sends an emergency notification.

[1005] A "smartphone application" is application software that runs on a smartphone and receives and displays push notifications from a notification means.

[1006] The "transmitting means configured to transmit data to a server at intervals" is a device having a function of transmitting a portion of data to a server at a set time interval.

[1007] "Means of real-time notification" refers to a function that immediately sends a notification via a smartphone application if an abnormality is detected.

[1008] This invention is a system that monitors the health status and location information of elderly people and children in real time and promptly notifies users when an abnormality is detected. This system consists of sensor devices, a server that analyzes the data, and users who receive notifications.

[1009] 1. Sensor device (terminal)

[1010] The terminal provides a wristband or necklace-type sensor means that can be worn daily by the elderly and children. This sensor device is equipped with various sensors to measure heart rate, blood pressure, body temperature, location information, and activity information, and temporarily stores these measured values ​​in a buffer at regular intervals. The sensor device also has a transmission means for sending the measured data to a server. It also has an SOS button means that the user can operate in the event of an emergency.

[1011] 2. Server (Central Management System)

[1012] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by the AI ​​analysis means. The AI ​​analysis means runs an algorithm that compares the data with normal health data to detect abnormal values ​​and behavior. This analysis is performed using software such as Python and Flask. If the notification means detects an abnormality, a push notification smartphone application will alert the user in real time. Notifications are sent using Google Firebase Cloud Messaging (FCM).

[1013] 3. User Notification and Emergency Response

[1014] The intended recipients of notifications are close relatives and caregivers. The smartphone application displays a push notification in real time when an abnormality occurs. The alert includes the time of the abnormality, detailed data, and the current location. After receiving the notification, the user can check the detailed data and take emergency action if necessary. For example, if an elderly person's heart rate shows an abnormal value, close relatives will receive a push notification and can check the detailed data in the application. They can then contact the user directly or arrange for medical services if necessary.

[1015] Specific examples

[1016] Consider the case where a 75-year-old person experiences an abnormally high heart rate while going about their daily life. At this time, the heart rate sensor detects the abnormal value and sends the data to the server. The server's AI analysis means analyzes the abnormal value and immediately detects the abnormality. The server then sends a push notification, which is sent in real time to the smartphones of close relatives.

[1017] Example prompt sentence:

[1018] Develop an application that monitors the heart rate and location of elderly people in real time and sends push notifications to their next of kin if an abnormality is detected. Use Python and Flask to receive data from sensor devices and include a function to send notifications via Firebase Cloud Messaging if an abnormal value is detected.

[1019] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1020] Step 1:

[1021] Data collection using sensor devices

[1022] The device's built-in sensors measure various data in real time, including heart rate, blood pressure, body temperature, location information, and activity information. This measurement data is temporarily stored in a buffer within the device.

[1023] Input: Heart rate, blood pressure, temperature, location, activity information

[1024] Output: Buffered sensor data

[1025] Step 2:

[1026] Data transmission

[1027] The terminal transmits data measured by the sensor means to the server at regular intervals (for example, every 5 minutes). In an emergency, the data is transmitted immediately when the SOS button means of the terminal is pressed.

[1028] Input: Buffered sensor data

[1029] Output: Sensor data sent to the server

[1030] Step 3:

[1031] Data reception and storage

[1032] The server receives the sensor data sent from the terminal and stores it in a database.

[1033] Input: Sensor data sent to the server

[1034] Output: Sensor data stored in a database

[1035] Step 4:

[1036] AI analysis

[1037] The server's AI analysis tools analyze the stored data in real time, compare it with normal data ranges, and run algorithms to detect outliers and abnormal behavior.

[1038] Input: Sensor data stored in a database

[1039] Output: Anomaly detection result (normal / abnormal)

[1040] Step 5:

[1041] Anomaly detection notification

[1042] If the AI ​​analysis method detects an abnormality, the server's notification method will send a push notification to the user. The push notification will include the time the abnormality occurred, detailed data, and the user's current location. Firebase Cloud Messaging (FCM) is used.

[1043] Input: Anomaly detection results

[1044] Output: A push notification that appears on the user's phone.

[1045] Step 6:

[1046] User Support

[1047] Users receive a notification on their smartphone app, view detailed data, assess the situation, and, if necessary, contact the user directly or arrange for medical assistance.

[1048] Input: Push notification displayed on smartphone

[1049] Output: User's response (contact, medical service arrangements, etc.)

[1050] 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.

[1051] This invention is a system that combines a system that monitors the health status and location information of elderly people and children in real time and quickly notifies users when an abnormality is detected with an emotion engine that recognizes the user's emotions. This system consists of a wristband or necklace-type sensor device, a server that analyzes the data, a user who receives notifications, and an emotion engine that recognizes the user's emotions.

[1052] 1. Sensor device (terminal)

[1053] The sensor device is equipped with various sensors necessary to measure heart rate, blood pressure, body temperature, location information, and activity information. This sensor device is provided in simple formats such as a wristband or necklace, so that elderly people and children can wear it on a daily basis without difficulty. The sensor device also has a communication module that transmits the measured data to a server.

[1054] 2. Server (Central Management System)

[1055] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by an AI analysis means. The AI ​​analysis means compares the data with normal ranges and executes an algorithm to detect abnormal values ​​and abnormal behavior.

[1056] The server also incorporates an emotion engine that analyzes the user's emotional state. The emotion engine recognizes the user's emotions by analyzing the user's voice data and facial expression data. This emotional information is also stored on the server and evaluated together with the analysis of the user's health status.

[1057] 3. Notification and Emergency Response (User)

[1058] Users (close relatives and caregivers) who receive alerts via notification methods can check the notifications in real time through a smartphone or tablet application. The alerts include the time of the abnormality, detailed data, current location information, and information about the user's emotional state. Based on this information, users can take prompt action.

[1059] For example, if an elderly person's heart rate shows abnormal values, the user will receive a push notification and can view the details and emotional state in the app, after which the user can be contacted directly or medical assistance can be arranged if necessary.

[1060] Specific examples

[1061] Example 1: Detecting abnormal heart rate with emotional fluctuations

[1062] 1. Device: The heart rate sensor measures the heart rate and sends the data to the server. The device also acquires the user's emotional data through voice recognition.

[1063] 2. Server: The server analyzes the received heart rate data and emotion data. If an abnormal value is detected, it evaluates the importance of the abnormality taking into account the emotion data.

[1064] 3. Server: If an abnormal heart rate is detected and the emotion engine detects emotional data indicating stress or anxiety, it generates alert information and sends an alert to close relatives or caregivers via notification means.

[1065] 4. User: Next of kin will receive a push notification to view detailed data and emotional state, assess the situation, contact the user if necessary, and arrange medical services.

[1066] Example 2: Fall and panic detection and notification

[1067] 1. Device: The accelerometer monitors the user's movements and detects abnormal acceleration. The voice recognition function also captures the user's emotional data (such as out-of-range tone of voice).

[1068] 2. Server: The server receives and analyzes the abnormal behavior data and emotion data. If it determines that there is a high possibility of a fall and the emotion engine detects emotion data indicating panic or fear, it generates an alert.

[1069] 3. Server: Notifies next of kin and caregivers of fall and panic alerts.

[1070] 4. User: Next of kin receives push notification to check abnormal behavior and emotional state, and responds quickly, arranging for help if necessary.

[1071] Specific program processing

[1072] The program processing is carried out in the following steps:

[1073] The sensor device measures heart rate, blood pressure, body temperature, location information, and activity information, and analyzes voice and facial expression data using an emotion engine. This data is sent to a server at regular intervals, and the server analyzes the received data using AI analysis means. In the event of an abnormality, an alert is generated taking into account the emotional information. Ultimately, a notification is sent to close relatives or caregivers, allowing for prompt action.

[1074] The system of the present invention can improve the safety and quality of life (QOL) of users by comprehensively monitoring the health status and emotions of elderly people and children.

[1075] The processing flow will be explained below.

[1076] Abnormal heart rate detection process combined with emotion engine

[1077] Step 1:

[1078] The device measures the heart rate using the heart rate sensor and temporarily stores the measurement data in a buffer.

[1079] Step 2:

[1080] The device uses its voice recognition function to acquire the user's voice data, analyzes it with its emotion engine, and temporarily stores the emotion data in a buffer.

[1081] Step 3:

[1082] The device sends the buffered heart rate data and emotion data to the server at regular intervals (e.g., every 5 minutes).

[1083] Step 4:

[1084] The server receives the heart rate data and emotion data sent from the device and stores the received data in a database.

[1085] Step 5:

[1086] The heart rate data received by the server is analyzed using AI analysis tools, and abnormal values ​​are detected by comparing them with the normal range.

[1087] Step 6:

[1088] The server analyzes the received emotional data to determine the user's emotional state, for example, detecting data indicating stress or anxiety.

[1089] Step 7:

[1090] The server comprehensively evaluates abnormal heart rate values ​​and emotional data to determine the importance of the abnormality.

[1091] Step 8:

[1092] If the server detects abnormal heart rate and emotions associated with stress or anxiety, it generates an alert with detailed data (heart rate, emotional state, time, and location).

[1093] Step 9:

[1094] The server issues an alert to the next of kin or caregiver via the notification means.

[1095] Step 10:

[1096] Users receive alerts via a smartphone or tablet application, where they can view detailed data on abnormal heart rates and emotional states.

[1097] Step 11:

[1098] The user assesses the situation and contacts the user or arranges for medical services if necessary.

[1099] Fall detection and notification process combined with emotion engine

[1100] Step 1:

[1101] The device uses an acceleration sensor to monitor the user's movements in real time and detect abnormal acceleration.

[1102] Step 2:

[1103] The device uses its voice recognition function to acquire the user's voice data, analyzes it with its emotion engine, and temporarily stores the emotion data in a buffer.

[1104] Step 3:

[1105] If the device detects abnormal acceleration, it immediately sends that data to the server, along with emotion data.

[1106] Step 4:

[1107] The server receives abnormal behavior data and emotion data sent from the device and stores them in a database.

[1108] Step 5:

[1109] The server analyzes the abnormal movement data using AI analysis methods and determines that there is a high possibility of a fall.

[1110] Step 6:

[1111] The server analyzes the emotional data to determine if the user is exhibiting panic or fear.

[1112] Step 7:

[1113] The server comprehensively assesses the likelihood of falling and the emotional state and determines the importance.

[1114] Step 8:

[1115] If the server detects a fall and emotions associated with panic or fear, it generates an alert containing detailed data (abnormal behavior, emotional state, time, and location information).

[1116] Step 9:

[1117] The server notifies the alert information to the next of kin or caregiver via the notification means.

[1118] Step 10:

[1119] Users receive alerts via a smartphone or tablet application, and can view detailed data on fall detection and emotional state.

[1120] Step 11:

[1121] If the user determines that an emergency response is required, we will promptly arrange for rescue and contact the user directly to confirm the situation.

[1122] In this way, the system of the present invention is designed to monitor not only the health status of elderly people and children but also their emotional state in real time, and to respond quickly to abnormalities or emergencies.

[1123] Example 2

[1124] 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."

[1125] In modern society, there is a growing demand for real-time monitoring of the safety and health of the elderly and children. However, current systems do not adequately detect abnormalities that take into account the user's emotional state, which can lead to delayed responses when an abnormality occurs. Furthermore, systems that simply measure biometric data have the challenge of making it difficult to respond appropriately to psychological states such as stress and anxiety in users.

[1126] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1127] In this invention, the server includes an AI analysis unit, an emotion engine unit, and a notification unit, which enables real-time detection of abnormalities and rapid response while taking into account both biometric data and emotion data.

[1128] The "sensor means" is a device for measuring biological data such as heart rate, blood pressure, body temperature, location information, and activity information.

[1129] The "transmitting means" is a communication device for transmitting data measured by the sensor means to the server.

[1130] "AI analysis means" refers to an artificial intelligence algorithm that analyzes received data in real time, compares it with normal ranges, and detects abnormal values ​​and behavior.

[1131] The "notification means" is a device that issues an alert to the user when an abnormality is detected by the AI ​​analysis means.

[1132] The "SOS button means" is a device that can be operated by a user to send an SOS signal in an emergency.

[1133] The "emotion engine means" is an algorithm for analyzing the user's voice and facial expression data and recognizing the user's emotional state.

[1134] An "alert" is a warning message that is sent to the user or a close relative when an abnormality is detected.

[1135] An "interval" is a specified time interval for sending data to the server.

[1136] This system monitors the health status and location information of elderly people and children in real time and promptly notifies users when abnormalities are detected. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to comprehensively evaluate both biometric data and emotion data. This system consists of a wristband or necklace-style sensor device, a server that analyzes the data, a user who receives notifications, and an emotion engine that recognizes the user's emotions.

[1137] 1. Sensor device (terminal)

[1138] The sensor device is equipped with sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information. This sensor device is available in the form of a wristband or necklace, making it easy for elderly people and children to wear on a daily basis. It also has a voice recognition function and a camera function for capturing voice and facial expression data. The sensor device also includes a communication module for transmitting the measured data to a server.

[1139] 2. Server (Central Management System)

[1140] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by AI analysis means. The AI ​​analysis means compares biometric data such as heart rate, blood pressure, body temperature, location information, and activity information with normal range data and executes algorithms to detect abnormal values ​​and behavior. The server also incorporates an emotion engine, which has the function of analyzing the user's emotional state. The emotion engine recognizes the user's emotions by analyzing the user's voice data and facial expression data. This emotional information is also stored on the server and is comprehensively evaluated along with an analysis of the user's health status.

[1141] 3. Notification and Emergency Response (User)

[1142] Users (close relatives and caregivers) who receive alerts via notification methods can check the notifications in real time through a smartphone or tablet application. The alerts include the time of the abnormality, detailed data, current location information, and information about the user's emotional state. Based on this information, users can take prompt action.

[1143] For example, if an elderly person's heart rate shows abnormal values, the user will receive a push notification and can view the details and emotional state in the app, after which the user can be contacted directly or medical assistance can be arranged if necessary.

[1144] Specific examples

[1145] Example 1: Detecting abnormal heart rate with emotional fluctuations

[1146] 1. Device: The heart rate sensor measures the heart rate and sends the data to the server. The device also acquires the user's emotional data through voice recognition.

[1147] 2. Server: The server analyzes the received heart rate data and emotion data. If an abnormal value is detected, it evaluates the importance of the abnormality taking into account the emotion data.

[1148] 3. Server: If an abnormal heart rate is detected and the emotion engine detects emotional data indicating stress or anxiety, it generates alert information and sends an alert to close relatives or caregivers via notification means.

[1149] 4. User: Next of kin will receive a push notification to view detailed data and emotional state, assess the situation, contact the user if necessary, and arrange medical services.

[1150] Example 2: Fall and panic detection and notification

[1151] 1. Device: The accelerometer monitors the user's movements and detects abnormal acceleration. The voice recognition function also captures the user's emotional data (such as out-of-range tone of voice).

[1152] 2. Server: The server receives and analyzes the abnormal behavior data and emotion data. If it determines that there is a high possibility of a fall and the emotion engine detects emotion data indicating panic or fear, it generates an alert.

[1153] 3. Server: Notifies next of kin and caregivers of fall and panic alerts.

[1154] 4. User: Next of kin receives push notification to check abnormal behavior and emotional state, and responds quickly, arranging for help if necessary.

[1155] Example prompt

[1156] "Describe a scenario in which you want to detect abnormal heart rates and emotional fluctuations in an elderly person."

[1157] "How do you alert me when my child falls and panics?"

[1158] This system comprehensively monitors the health and emotions of elderly people and children, improving the safety and quality of life of users.

[1159] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1160] Step 1:

[1161] Device: Measures heart rate, blood pressure, body temperature, location, and activity information.

[1162] How it works: Various sensors installed on the device continuously monitor the user's biometric data and collect data at regular intervals.

[1163] Input: User's biological status (heart rate, blood pressure, body temperature, location information, activity information)

[1164] Output: Biometric data set (heart rate, blood pressure, temperature, location, activity)

[1165] Step 2:

[1166] Terminal: Analyzes voice and facial expression data using an emotion engine to generate emotion data.

[1167] How it works: Using voice recognition and camera functions, the user's tone of voice and facial expressions are collected and analyzed by the emotion engine.

[1168] Input: User's voice data and image data (facial expressions)

[1169] Output: Emotion data (stress, anxiety, joy, etc.)

[1170] Step 3:

[1171] Terminal: Sends collected sensor data and emotion data to the server via the communication module.

[1172] Operation: Data is collected within the sensor device and transferred to the server via wireless communication (Wi-Fi, Bluetooth, etc.).

[1173] Input: Biometric dataset and emotion data

[1174] Output: Data packets (biometric dataset, emotion data) to the server

[1175] Step 4:

[1176] Server: The server receives the data sent from the device.

[1177] Operation: The server receives data via the communication protocol and stores it in a receive buffer.

[1178] Input: Data packets sent from the device

[1179] Output: Raw data in the receive buffer

[1180] Step 5:

[1181] Server: Stores the received data in a database.

[1182] How it works: Connects to a database and stores data by time.

[1183] Input: Raw data in the receive buffer

[1184] Output: Structured data stored in a database

[1185] Step 6:

[1186] Server: Analyzes the stored data in real time using AI analysis methods.

[1187] How it works: It uses AI models to analyze biometric data and compare it to normal ranges. If an abnormality is detected, it highlights it.

[1188] Input: Structured data in a database

[1189] Output: Abnormality detection result and its detailed data

[1190] Step 7:

[1191] Server: The emotion engine analyzes voice and facial expression data to recognize the user's emotional state.

[1192] How it works: The emotion engine analyzes subtle changes in vocal tone and facial expressions to determine emotional states (e.g., stress, joy, anxiety).

[1193] Input: Voice and facial expression data in the database

[1194] Output: Emotion analysis results

[1195] Step 8:

[1196] Server: Generates notifications when anomalies are detected based on data analysis results and emotion data.

[1197] Behavior: If an abnormal value is detected and the sentiment is unstable, a notification message is generated and linked to the notification system.

[1198] Input: Anomaly detection results and emotion analysis results

[1199] Output: Information message

[1200] Step 9:

[1201] Server: Sends alerts to the smartphones or tablets of relatives or caregivers through a notification system.

[1202] What it does: Sends real-time alerts using notification protocols (e.g., push notifications, SMS).

[1203] Input: Notification message

[1204] Output: Push notification to user device

[1205] Step 10:

[1206] Users: Receive notifications and view detailed data in an application on their smartphone or tablet.

[1207] What it does: Tap the push notification to open the app and check the abnormal data and emotional state.

[1208] Input: Push notification to user device

[1209] Output: Detailed data and emotional state displayed on the application

[1210] Step 11:

[1211] User: Contacting users or providing emergency response as needed.

[1212] How it works: Based on the notification, the system will contact the user via phone or messaging app and arrange for medical services or rescue operations depending on the situation.

[1213] Input: Detailed data and emotional state displayed on the application

[1214] Output: User's response actions (contact, medical assistance, rescue operation)

[1215] (Application example 2)

[1216] 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."

[1217] Monitoring the health and location information of elderly people and children in real time and responding promptly when abnormalities are detected is an important issue in today's society. However, existing monitoring systems are limited to simply monitoring data such as heart rate and body temperature, making it difficult to provide a comprehensive response that takes into account the user's emotional state. As a result, true emergencies can be overlooked or unnecessary alerts can be generated. Furthermore, there is a risk of delayed response in emergencies due to a lack of systems in place to enable relatives and caregivers to respond promptly.

[1218] 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 an AI analysis means for analyzing data measured by the sensor means, an emotion engine for analyzing the emotional state of the user, and a notification means for issuing an alert when an abnormality is detected. This makes it possible to comprehensively monitor the health and emotional states of elderly people and children, and to respond quickly when an abnormality occurs.

[1219] The "health monitoring system" is a system that monitors the health status and location information of elderly people and children in real time, and responds quickly when an abnormality is detected.

[1220] The "sensor means" is a device including various sensors for measuring heart rate, blood pressure, body temperature, location information, activity information, voice data, and facial expression data.

[1221] The "transmitting means" is a device that includes a communication module for transmitting data measured by the sensor device to the server.

[1222] The "AI analysis means" has the function of analyzing the data received by the server, comparing it with data within the normal range, and executing an algorithm to detect abnormal values ​​or abnormal behavior.

[1223] An "emotion engine" is a software engine that has the function of analyzing a user's voice data and facial expression data and recognizing the user's emotional state.

[1224] "Notification means" refers to a means for sending an alert to next of kin or caregivers when an abnormality is detected by the AI ​​analysis means and emotion engine.

[1225] "Communication means" refers to a means for informing relatives or caregivers of the health and emotional state of the elderly or child in real time via notification means.

[1226] "SOS Button Means" means a device that includes a button that allows a user or their next of kin to manually initiate an emergency alert in the event of an emergency.

[1227] The "wristband or necklace type sensor means" is a sensor device that can be easily worn in daily life and can measure heart rate, blood pressure, body temperature, location information, and activity information.

[1228] This is a health monitoring system that comprehensively monitors the health and emotional states of the elderly and children, enabling rapid response in the event of an abnormality. The basic components of this system are a wristband or necklace-type sensor device, a server, a notification means, and an SOS button means for emergency response.

[1229] 1. Sensor Devices

[1230] The sensor device includes various sensors for measuring heart rate, blood pressure, body temperature, location information, activity information, as well as voice and facial expression data. This allows it to acquire a wide range of data while being easy for elderly people and children to wear on a daily basis. The sensor device is equipped with a communication module for transmitting the measured data to a server.

[1231] 2. Server

[1232] The server receives and analyzes the data sent by the sensor device. This involves the use of an AI analysis means and emotion engine. The AI ​​analysis means analyzes the received health data in real time, comparing it with normal range data to detect outliers and abnormal behavior. The emotion engine analyzes voice data and facial expression data to identify the user's emotional state. If the server detects an abnormality based on this data, it immediately generates an alert.

[1233] 3. Means of notification

[1234] The notification mechanism is responsible for sending alerts generated by the server to next of kin or caregivers. Notifications are provided in real time via a smartphone or tablet application, allowing for immediate sharing of information about the time of the anomaly, detailed data, current location, and emotional state.

[1235] 4. Emergency Response Measures

[1236] The emergency response measures include an SOS button that can be manually operated by the user in an emergency, which immediately initiates an emergency call to request help.

[1237] The processing of the program for realizing this system will be explained below.

[1238] Program processing

[1239] The server receives data sent from the sensor device at regular intervals. The server first analyzes the health data using AI analysis tools to check for any abnormal values. Next, the emotion engine analyzes the voice and facial expression data to identify the user's emotional state. If an abnormality is detected, an alert is generated based on this information and sent promptly to next of kin or caregivers via notification tools. The notification includes the time the abnormality occurred, detailed health data, location information, and emotional state.

[1240] Hardware and software used

[1241] Sensor devices: Includes sensors for measuring heart rate, blood pressure, body temperature, location information, activity information, voice data, and facial expression data.

[1242] Server: Contains AI analysis tools and emotion engine.

[1243] Communication modules: Modules for sending data (e.g., the requests library).

[1244] Notification System: The system for sending alerts (e.g. NotificationSystem).

[1245] Specific examples

[1246] If an elderly person's heart rate is abnormally high and the emotion engine's stress emotion analysis results show a high value:

[1247] "User A's heart rate is abnormally high, and the stress emotion analysis results from the emotion engine indicate a high value. Their current location is ____. Please take appropriate action immediately."

[1248] If a child falls and the emotion engine detects emotion data that indicates fear or panic:

[1249] "A child has fallen and the emotion engine has detected emotion data indicating fear or panic. Current location: ____. Immediate response required."

[1250] This system will enable comprehensive monitoring of the health and emotional state of the elderly and children, and will enable prompt response if any abnormalities occur.

[1251] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1252] Step 1:

[1253] The sensor device measures the heart rate, blood pressure, body temperature, location information, activity information, voice data, and facial expression data of elderly people and children.

[1254] Input: Heart rate, blood pressure, body temperature, location information, activity information, voice data, facial expression data

[1255] Output: Measurement data

[1256] How it works: The sensor device is worn on the body of an elderly person or child, and the built-in sensors collect health and emotional data in real time.

[1257] Step 2:

[1258] The measurement data acquired by the sensor device is sent to the server.

[1259] Input: Measurement data

[1260] Output: Data sent to the server

[1261] Specific operation: Data is sent to the server at regular intervals using the communication module of the sensor device.

[1262] Step 3:

[1263] The data received by the server is analyzed using AI analysis methods.

[1264] Input: Measurement data

[1265] Output: Analysis results (health status)

[1266] Specific operation: An AI analysis tool running on the server analyzes the received data in real time and compares it with data within the normal range to detect any abnormalities.

[1267] Step 4:

[1268] The server uses an emotion engine to analyze voice data and facial expression data to identify the emotional state.

[1269] Input: Voice data, facial expression data

[1270] Output: Emotional state

[1271] How it works: The emotion engine on the server uses voice and image recognition technology to identify the user's emotional state (e.g., stress, anxiety, panic, etc.).

[1272] Step 5:

[1273] The server detects abnormalities based on the analysis results and emotional state.

[1274] Input: Analysis results, emotional state

[1275] Output: Abnormality detection

[1276] Specific behavior: Match the output of the AI ​​analysis method with the emotion engine to determine whether an abnormal health condition and a dangerous emotional state are detected simultaneously.

[1277] Step 6:

[1278] If the server detects an abnormality, it generates an alert.

[1279] Input: Anomaly detection results (health status and emotional state)

[1280] Output: Alert information

[1281] Specific behavior: When an anomaly is detected, the server generates alert information including the specific anomaly content, time, location information, and emotional state.

[1282] Step 7:

[1283] The server generates alert information and sends it to a close relative or caregiver via a notification means.

[1284] Input: Alert information

[1285] Output: Notification message (e.g. push notification)

[1286] Specific operation: Alert information is sent in real time via a smartphone application or email, and details of the abnormality are notified to next of kin or caregivers.

[1287] Step 8:

[1288] Relatives and caregivers will receive a notification message and take appropriate action.

[1289] Input: Notification message

[1290] Output: Carrying out care and emergency response

[1291] What it does: A push notification allows a relative or caregiver to use the app to view detailed health information and emotional state, and then respond or provide help if necessary.

[1292] This will enable real-time monitoring of the health and emotional state of the elderly and children, and rapid response if any abnormalities are detected.

[1293] 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.

[1294] 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.

[1295] 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.

[1296] [Fourth embodiment]

[1297] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1298] 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.

[1299] 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).

[1300] 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.

[1301] 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.

[1302] 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).

[1303] 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.

[1304] 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.

[1305] 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.

[1306] 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.

[1307] 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.

[1308] 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.

[1309] 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."

[1310] This invention is a system that monitors the health status and location information of elderly people and children in real time and promptly notifies users when an abnormality is detected. This system consists of three main components: a wristband or necklace-type sensor device, a server that analyzes the data, and the user who receives the notification.

[1311] 1. Sensor device (terminal)

[1312] The sensor device is equipped with various sensors necessary to measure heart rate, blood pressure, body temperature, location information, and activity information. This sensor device is provided in simple formats such as a wristband or necklace, so that elderly people and children can wear it on a daily basis without difficulty. The sensor device also has a communication module that transmits the measured data to a server.

[1313] The sensor device measures heart rate, blood pressure, and body temperature, for example, every 60 seconds, and temporarily stores the data in a buffer. This data is then sent to a server at regular intervals (for example, every 5 minutes). In the event of an emergency, the user can press the SOS button, and the data will be sent to the server immediately.

[1314] 2. Server (Central Management System)

[1315] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by an AI analysis means. The AI ​​analysis means compares the data with normal ranges and executes an algorithm to detect abnormal values ​​and abnormal behavior.

[1316] For example, if the heart rate is abnormal, the server will analyze the received heart rate data in detail and if it detects consecutive values ​​outside the normal range, it will determine that there is an abnormality. If such an abnormality is detected, the server will promptly send an alert to close relatives or caregivers via a notification means.

[1317] 3. Notification and Emergency Response (User)

[1318] Users (close relatives or caregivers) who receive alerts via notification methods can check the notifications in real time through a smartphone or tablet application. The alerts include the time when the abnormality occurred, detailed data, and current location information. Based on this information, users can take prompt action.

[1319] For example, if an elderly person's heart rate shows an abnormal value, the user will receive a push notification and can view the details in the app, after which they can contact the person directly or arrange for medical assistance if necessary.

[1320] Specific examples

[1321] Example 1: Detecting abnormal heart rates

[1322] 1. Device: The heart rate sensor measures the heart rate and sends the data to the server.

[1323] 2. Server: The server analyzes the received heart rate data and determines that an abnormality has occurred if a value outside the normal range is detected consecutively. If an abnormality is detected, an alert is issued.

[1324] 3. User: Next of kin receives an alert in the application, checks the details, assesses the situation, and if necessary, contacts the person directly to arrange medical services.

[1325] Example 2: Fall detection and notification

[1326] 1. Device: The accelerometer monitors the user's movements and detects abnormal acceleration (e.g., sudden acceleration or deceleration). If abnormal movement is detected, the data is sent to the server.

[1327] 2. Server: The server analyzes the received data and determines the possibility of a fall. It generates alert information for the fall detection and issues the alert via the notification means.

[1328] 3. User: Next of kin receive an alert in the application, check the detailed data, and if they determine that emergency response is required, they will contact them directly and respond promptly.

[1329] In this way, the system of the present invention can protect the health and safety of users by combining sensor devices that can be easily used by the elderly and children, a server that analyzes data in real time, and a notification means for rapid response.

[1330] The processing flow will be explained below.

[1331] Abnormal Heart Rate Detection Process

[1332] Step 1:

[1333] The device measures the heart rate using the heart rate sensor and temporarily stores the measurement data in a buffer.

[1334] Step 2:

[1335] The device sends the buffered heart rate data to the server at regular intervals (for example, every 5 minutes).

[1336] Step 3:

[1337] The server receives the heart rate data sent from the device and stores it in a database.

[1338] Step 4:

[1339] The heart rate data received by the server is analyzed using AI analysis tools, and abnormal values ​​are detected by comparing them with the normal range.

[1340] Step 5:

[1341] If the server detects an abnormal value, it generates alert information and issues an alert to close relatives or caregivers via a notification means.

[1342] Step 6:

[1343] Users receive alerts via an application on their smartphone or tablet, where they can view detailed data on abnormal heart rates.

[1344] Step 7:

[1345] The user assesses the situation and contacts the user or arranges for medical services if necessary.

[1346] Fall detection and notification process

[1347] Step 1:

[1348] The device uses an acceleration sensor to monitor the user's movements in real time and detect abnormal acceleration.

[1349] Step 2:

[1350] If the device detects abnormal acceleration, it immediately sends the data to the server.

[1351] Step 3:

[1352] The server receives the abnormal operation data sent from the device and stores the received data in a database.

[1353] Step 4:

[1354] The server analyzes the received data using AI analysis methods and determines that there is a high possibility of a fall.

[1355] Step 5:

[1356] The server generates alert information for the fall detection and notifies the next of kin or caregiver via the notification means.

[1357] Step 6:

[1358] Users can receive alerts via smartphone or tablet applications and check detailed data on fall detection.

[1359] Step 7:

[1360] If the user determines that an emergency response is required, the user will be contacted directly and help will be called for and responded to promptly.

[1361] Emergency Call Process

[1362] Step 1:

[1363] The device detects when the SOS button is pressed by the user and immediately sends emergency data to the server.

[1364] Step 2:

[1365] The server receives the emergency data sent from the device and stores the received data in a database.

[1366] Step 3:

[1367] The server generates emergency call alert information and immediately notifies the next of kin or caregiver via the notification means.

[1368] Step 4:

[1369] Users receive emergency alerts via smartphone or tablet applications and can view detailed emergency data.

[1370] Step 5:

[1371] The user assesses the situation and takes immediate action, arranging for medical services or emergency response if necessary.

[1372] Through the above processing steps, the system of the present invention can monitor the health and safety of the elderly and children in real time and respond quickly to abnormalities or emergencies.

[1373] Example 1

[1374] 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."

[1375] The goal is to monitor the health status and location information of vulnerable individuals, such as the elderly and children, in real time, and to take prompt and appropriate action when an abnormality occurs. However, existing systems make it difficult to respond quickly because the processes of data collection, communication, anomaly detection, and notification are not efficiently coordinated. In addition, many systems lack the ability to respond immediately in an emergency.

[1376] 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.

[1377] In this invention, the server includes sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information, transmission means for transmitting data measured by the sensor means to the server at regular intervals (for example, every 5 minutes), communication means for immediately transmitting data to the server when a user presses an SOS button operable by the user in an emergency, AI analysis means for receiving and analyzing the data transmitted by the transmission means and the emergency communication means, and notification means for promptly notifying close relatives or caregivers if an abnormality is detected by the AI ​​analysis means. This enables real-time health status monitoring, prompt notification in the event of an abnormality, and immediate response.

[1378] The "sensor means" refers to a device for measuring heart rate, blood pressure, body temperature, location information, activity information, and the like.

[1379] The "transmitting means" refers to a communication device for transmitting the data measured by the sensor means to a server at regular intervals.

[1380] "Communication means" refers to a device that allows a user to press an SOS button in an emergency to instantly send data to a server.

[1381] "AI analysis means" refers to an analytical device that uses artificial intelligence to analyze received data, compare it with the normal range, and detect abnormal values.

[1382] The "notification means" refers to a device that promptly notifies next of kin or caregivers when an abnormality is detected by the AI ​​analysis means.

[1383] This invention is a system that monitors the health status and location information of elderly people and children in real time and promptly notifies them when an abnormality is detected. This system consists of three main components: a wristband or necklace-type sensor device, a server that analyzes the data, and the user who receives the notification.

[1384] Sensor device (terminal)

[1385] The sensor device is equipped with various sensors to measure heart rate, blood pressure, body temperature, location information, and activity information. This sensor device is provided in simple formats such as wristbands and necklaces, and can be worn comfortably by the elderly and children on a daily basis. The sensor device also has a communication module that transmits the measured data to a server.

[1386] The device measures heart rate, blood pressure, and body temperature, for example, every 60 seconds, and temporarily stores the data in a buffer.The data is then sent to the server at regular intervals (for example, every 5 minutes).In the event of an emergency, the user can press the SOS button, and the data will be sent to the server immediately.

[1387] Server (central management system)

[1388] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by an AI analysis means. The AI ​​analysis means compares the data with normal ranges and executes an algorithm to detect abnormal values ​​and abnormal behavior.

[1389] For example, if the heart rate is abnormal, the server will analyze the received heart rate data in detail and if it detects consecutive values ​​outside the normal range, it will determine that there is an abnormality. If such an abnormality is detected, the server will promptly send an alert to close relatives or caregivers via a notification means.

[1390] Notification and Emergency Response (User)

[1391] Users (close relatives or caregivers) who receive alerts via notification methods can check the notifications in real time through a smartphone or tablet application. The alerts include the time when the abnormality occurred, detailed data, and current location information. Based on this information, users can take prompt action.

[1392] For example, if an elderly person's heart rate shows an abnormal value, the user will receive a push notification and can view the details in the app, after which they can contact the person directly or arrange for medical assistance if necessary.

[1393] Specific examples

[1394] Example 1: Detecting abnormal heart rates

[1395] 1. Device: The heart rate sensor measures the heart rate and sends the data to the server.

[1396] 2. Server: The server analyzes the received heart rate data and determines that an abnormality has occurred if a value outside the normal range is detected consecutively. If an abnormality is detected, an alert is issued.

[1397] 3. User: Next of kin receives an alert in the application, checks the details, assesses the situation, and if necessary, contacts the person directly to arrange medical services.

[1398] Example 2: Fall detection and notification

[1399] 1. Device: The accelerometer monitors the user's movements and detects abnormal acceleration (e.g., sudden acceleration or deceleration). If abnormal movement is detected, the data is sent to the server.

[1400] 2. Server: The server analyzes the received data and determines the possibility of a fall. It generates alert information for the fall detection and issues the alert via the notification means.

[1401] 3. User: Next of kin receive an alert in the application, check the detailed data, and if they determine that emergency response is required, they will contact them directly and respond promptly.

[1402] Prompt Sentence Examples

[1403] "If the user's heart rate is outside the normal range, activate an alert and notify next of kin."

[1404] "If the device's location information changes suddenly, send that data immediately and issue an alert if it determines there is a possibility of a fall."

[1405] In this way, the system of the present invention can protect the health and safety of the elderly and children in real time by combining sensor devices, a server that performs AI analysis, and notification means.

[1406] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1407] Step 1: Data collection (device)

[1408] The device operates various sensors to measure heart rate, blood pressure, body temperature, location information, and activity information. Specifically, the heart rate sensor measures heart rate every 60 seconds, and the blood pressure sensor measures blood pressure. These data are temporarily stored in a buffer within the device. Location information is also periodically updated using GPS and other location sensors. The input is vital information of the human body, and the output is sensor data stored in the buffer.

[1409] Step 2: Send data (terminal)

[1410] The communication module in the device sends the data stored in the buffer to the server at regular intervals (for example, every 5 minutes). In addition, in the event of an emergency, the user can press the SOS button, which immediately sends the data to the server. The input is the sensor data stored in the buffer, and the output is the transmitted data. Specifically, the communication module retrieves the data from the buffer and sends it to the server's receiving port.

[1411] Step 3: Receiving data (server)

[1412] The server receives data sent from the terminal. Specifically, the server constantly monitors the receiving port and waits for data to arrive. The input is the sensor data sent from the terminal, and the output is the received data. The received data is immediately saved in the database.

[1413] Step 4: Data analysis (server)

[1414] The AI ​​analysis algorithm in the server analyzes the received data by comparing it with normal ranges. For example, if consecutive abnormal heart rate values ​​are detected, it will flag them as an abnormality. The input is the sensor data stored in the database, and the output is the analysis result. Specifically, the AI ​​algorithm retrieves the data from the database and performs analysis.

[1415] Step 5: Alert generation (server)

[1416] If the server detects an abnormality, it will use the notification system to send an alert to relatives or caregivers. Specific operations include email, SMS, and app push notifications. The input is the result of the AI ​​analysis, and the output is the sent alert.

[1417] Step 6: Receiving and Confirming Notifications (User)

[1418] The user receives an alert notification on their smartphone or tablet. They can then check detailed data (such as the time the abnormality occurred and details of the heart rate) through the app. The input is the alert sent from the server, and the output is the detailed data displayed on the user's device. Specifically, the user opens the app and checks the alert content.

[1419] Step 7: Emergency Response (User)

[1420] After receiving an alert, the user checks the situation and takes necessary action, such as contacting the user directly or arranging for medical services. The input is the alert content and detailed data, and the output is the response action taken. Specific actions taken by the user include contacting the user by phone or messaging app.

[1421] (Application example 1)

[1422] 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."

[1423] Conventional health monitoring systems have difficulty monitoring the health status and location information of elderly people and children in real time, making it difficult to respond quickly when an abnormality occurs. Furthermore, there are cases where analysis of data sent from sensor devices and notifications are delayed, hindering emergency response. Furthermore, the system's operation is complicated, making it difficult for elderly people and children to use it on a daily basis.

[1424] 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.

[1425] In this invention, the server includes sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information, transmission means for transmitting data measured by the sensor means to the server, AI analysis means for receiving and analyzing the data transmitted by the transmission means, notification means for issuing an alert when an abnormality is detected by the AI ​​analysis means, SOS button means operable by the user in an emergency, transmission means configured to transmit part of the data to the server at specified intervals, a smartphone application for which the notification means issues push notifications, and means for notifying in real time when an abnormality is detected via the smartphone application. This makes it possible to monitor the health status and location information of elderly people and children in real time and to respond quickly and accurately when an abnormality occurs.

[1426] The "sensor means" is a device for measuring heart rate, blood pressure, body temperature, location information, and activity information.

[1427] The "transmitting means" is a device for transmitting data measured by the sensor means to the server.

[1428] "AI analysis means" refers to a device or system that uses artificial intelligence technology to receive and analyze data transmitted by the transmission means.

[1429] The "notification means" is a device or system that issues an alert to the user when an abnormality is detected by the AI ​​analysis means.

[1430] An "SOS button means" is a device having a button that can be operated by a user in an emergency, and operating this button sends an emergency notification.

[1431] A "smartphone application" is application software that runs on a smartphone and receives and displays push notifications from a notification means.

[1432] The "transmitting means configured to transmit data to a server at intervals" is a device having a function of transmitting a portion of data to a server at a set time interval.

[1433] "Means of real-time notification" refers to a function that immediately sends a notification via a smartphone application if an abnormality is detected.

[1434] This invention is a system that monitors the health status and location information of elderly people and children in real time and promptly notifies users when an abnormality is detected. This system consists of sensor devices, a server that analyzes the data, and users who receive notifications.

[1435] 1. Sensor device (terminal)

[1436] The terminal provides a wristband or necklace-type sensor means that can be worn daily by the elderly and children. This sensor device is equipped with various sensors to measure heart rate, blood pressure, body temperature, location information, and activity information, and temporarily stores these measured values ​​in a buffer at regular intervals. The sensor device also has a transmission means for sending the measured data to a server. It also has an SOS button means that the user can operate in the event of an emergency.

[1437] 2. Server (Central Management System)

[1438] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by the AI ​​analysis means. The AI ​​analysis means runs an algorithm that compares the data with normal health data to detect abnormal values ​​and behavior. This analysis is performed using software such as Python and Flask. If the notification means detects an abnormality, a push notification smartphone application will alert the user in real time. Notifications are sent using Google Firebase Cloud Messaging (FCM).

[1439] 3. User Notification and Emergency Response

[1440] The intended recipients of notifications are close relatives and caregivers. The smartphone application displays a push notification in real time when an abnormality occurs. The alert includes the time of the abnormality, detailed data, and the current location. After receiving the notification, the user can check the detailed data and take emergency action if necessary. For example, if an elderly person's heart rate shows an abnormal value, close relatives will receive a push notification and can check the detailed data in the application. They can then contact the user directly or arrange for medical services if necessary.

[1441] Specific examples

[1442] Consider the case where a 75-year-old person experiences an abnormally high heart rate while going about their daily life. At this time, the heart rate sensor detects the abnormal value and sends the data to the server. The server's AI analysis means analyzes the abnormal value and immediately detects the abnormality. The server then sends a push notification, which is sent in real time to the smartphones of close relatives.

[1443] Example prompt sentence:

[1444] Develop an application that monitors the heart rate and location of elderly people in real time and sends push notifications to their next of kin if an abnormality is detected. Use Python and Flask to receive data from sensor devices and include a function to send notifications via Firebase Cloud Messaging if an abnormal value is detected.

[1445] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1446] Step 1:

[1447] Data collection using sensor devices

[1448] The device's built-in sensors measure various data in real time, including heart rate, blood pressure, body temperature, location information, and activity information. This measurement data is temporarily stored in a buffer within the device.

[1449] Input: Heart rate, blood pressure, temperature, location, activity information

[1450] Output: Buffered sensor data

[1451] Step 2:

[1452] Data transmission

[1453] The terminal transmits data measured by the sensor means to the server at regular intervals (for example, every 5 minutes). In an emergency, the data is transmitted immediately when the SOS button means of the terminal is pressed.

[1454] Input: Buffered sensor data

[1455] Output: Sensor data sent to the server

[1456] Step 3:

[1457] Data reception and storage

[1458] The server receives the sensor data sent from the terminal and stores it in a database.

[1459] Input: Sensor data sent to the server

[1460] Output: Sensor data stored in a database

[1461] Step 4:

[1462] AI analysis

[1463] The server's AI analysis tools analyze the stored data in real time, compare it with normal data ranges, and run algorithms to detect outliers and abnormal behavior.

[1464] Input: Sensor data stored in a database

[1465] Output: Anomaly detection result (normal / abnormal)

[1466] Step 5:

[1467] Anomaly detection notification

[1468] If the AI ​​analysis method detects an abnormality, the server's notification method will send a push notification to the user. The push notification will include the time the abnormality occurred, detailed data, and the user's current location. Firebase Cloud Messaging (FCM) is used.

[1469] Input: Anomaly detection results

[1470] Output: A push notification that appears on the user's phone.

[1471] Step 6:

[1472] User Support

[1473] Users receive a notification on their smartphone app, view detailed data, assess the situation, and, if necessary, contact the user directly or arrange for medical assistance.

[1474] Input: Push notification displayed on smartphone

[1475] Output: User's response (contact, medical service arrangements, etc.)

[1476] 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.

[1477] This invention is a system that combines a system that monitors the health status and location information of elderly people and children in real time and quickly notifies users when an abnormality is detected with an emotion engine that recognizes the user's emotions. This system consists of a wristband or necklace-type sensor device, a server that analyzes the data, a user who receives notifications, and an emotion engine that recognizes the user's emotions.

[1478] 1. Sensor device (terminal)

[1479] The sensor device is equipped with various sensors necessary to measure heart rate, blood pressure, body temperature, location information, and activity information. This sensor device is provided in simple formats such as a wristband or necklace, so that elderly people and children can wear it on a daily basis without difficulty. The sensor device also has a communication module that transmits the measured data to a server.

[1480] 2. Server (Central Management System)

[1481] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by an AI analysis means. The AI ​​analysis means compares the data with normal ranges and executes an algorithm to detect abnormal values ​​and abnormal behavior.

[1482] The server also incorporates an emotion engine that analyzes the user's emotional state. The emotion engine recognizes the user's emotions by analyzing the user's voice data and facial expression data. This emotional information is also stored on the server and evaluated together with the analysis of the user's health status.

[1483] 3. Notification and Emergency Response (User)

[1484] Users (close relatives and caregivers) who receive alerts via notification methods can check the notifications in real time through a smartphone or tablet application. The alerts include the time of the abnormality, detailed data, current location information, and information about the user's emotional state. Based on this information, users can take prompt action.

[1485] For example, if an elderly person's heart rate shows abnormal values, the user will receive a push notification and can view the details and emotional state in the app, after which the user can be contacted directly or medical assistance can be arranged if necessary.

[1486] Specific examples

[1487] Example 1: Detecting abnormal heart rate with emotional fluctuations

[1488] 1. Device: The heart rate sensor measures the heart rate and sends the data to the server. The device also acquires the user's emotional data through voice recognition.

[1489] 2. Server: The server analyzes the received heart rate data and emotion data. If an abnormal value is detected, it evaluates the importance of the abnormality taking into account the emotion data.

[1490] 3. Server: If an abnormal heart rate is detected and the emotion engine detects emotional data indicating stress or anxiety, it generates alert information and sends an alert to close relatives or caregivers via notification means.

[1491] 4. User: Next of kin will receive a push notification to view detailed data and emotional state, assess the situation, contact the user if necessary, and arrange medical services.

[1492] Example 2: Fall and panic detection and notification

[1493] 1. Device: The accelerometer monitors the user's movements and detects abnormal acceleration. The voice recognition function also captures the user's emotional data (such as out-of-range tone of voice).

[1494] 2. Server: The server receives and analyzes the abnormal behavior data and emotion data. If it determines that there is a high possibility of a fall and the emotion engine detects emotion data indicating panic or fear, it generates an alert.

[1495] 3. Server: Notifies next of kin and caregivers of fall and panic alerts.

[1496] 4. User: Next of kin receives push notification to check abnormal behavior and emotional state, and responds quickly, arranging for help if necessary.

[1497] Specific program processing

[1498] The program processing is carried out in the following steps:

[1499] The sensor device measures heart rate, blood pressure, body temperature, location information, and activity information, and analyzes voice and facial expression data using an emotion engine. This data is sent to a server at regular intervals, and the server analyzes the received data using AI analysis means. In the event of an abnormality, an alert is generated taking into account the emotional information. Ultimately, a notification is sent to close relatives or caregivers, allowing for prompt action.

[1500] The system of the present invention can improve the safety and quality of life (QOL) of users by comprehensively monitoring the health status and emotions of elderly people and children.

[1501] The processing flow will be explained below.

[1502] Abnormal heart rate detection process combined with emotion engine

[1503] Step 1:

[1504] The device measures the heart rate using the heart rate sensor and temporarily stores the measurement data in a buffer.

[1505] Step 2:

[1506] The device uses its voice recognition function to acquire the user's voice data, analyzes it with its emotion engine, and temporarily stores the emotion data in a buffer.

[1507] Step 3:

[1508] The device sends the buffered heart rate data and emotion data to the server at regular intervals (e.g., every 5 minutes).

[1509] Step 4:

[1510] The server receives the heart rate data and emotion data sent from the device and stores the received data in a database.

[1511] Step 5:

[1512] The heart rate data received by the server is analyzed using AI analysis tools, and abnormal values ​​are detected by comparing them with the normal range.

[1513] Step 6:

[1514] The server analyzes the received emotional data to determine the user's emotional state, for example, detecting data indicating stress or anxiety.

[1515] Step 7:

[1516] The server comprehensively evaluates abnormal heart rate values ​​and emotional data to determine the importance of the abnormality.

[1517] Step 8:

[1518] If the server detects abnormal heart rate and emotions associated with stress or anxiety, it generates an alert with detailed data (heart rate, emotional state, time, and location).

[1519] Step 9:

[1520] The server issues an alert to the next of kin or caregiver via the notification means.

[1521] Step 10:

[1522] Users receive alerts via a smartphone or tablet application, where they can view detailed data on abnormal heart rates and emotional states.

[1523] Step 11:

[1524] The user assesses the situation and contacts the user or arranges for medical services if necessary.

[1525] Fall detection and notification process combined with emotion engine

[1526] Step 1:

[1527] The device uses an acceleration sensor to monitor the user's movements in real time and detect abnormal acceleration.

[1528] Step 2:

[1529] The device uses its voice recognition function to acquire the user's voice data, analyzes it with its emotion engine, and temporarily stores the emotion data in a buffer.

[1530] Step 3:

[1531] If the device detects abnormal acceleration, it immediately sends that data to the server, along with emotion data.

[1532] Step 4:

[1533] The server receives abnormal behavior data and emotion data sent from the device and stores them in a database.

[1534] Step 5:

[1535] The server analyzes the abnormal movement data using AI analysis methods and determines that there is a high possibility of a fall.

[1536] Step 6:

[1537] The server analyzes the emotional data to determine if the user is exhibiting panic or fear.

[1538] Step 7:

[1539] The server comprehensively assesses the likelihood of falling and the emotional state and determines the importance.

[1540] Step 8:

[1541] If the server detects a fall and emotions associated with panic or fear, it generates an alert containing detailed data (abnormal behavior, emotional state, time, and location information).

[1542] Step 9:

[1543] The server notifies the alert information to the next of kin or caregiver via the notification means.

[1544] Step 10:

[1545] Users receive alerts via a smartphone or tablet application, and can view detailed data on fall detection and emotional state.

[1546] Step 11:

[1547] If the user determines that an emergency response is required, we will promptly arrange for rescue and contact the user directly to confirm the situation.

[1548] In this way, the system of the present invention is designed to monitor not only the health status of elderly people and children but also their emotional state in real time, and to respond quickly to abnormalities or emergencies.

[1549] Example 2

[1550] 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."

[1551] In modern society, there is a growing demand for real-time monitoring of the safety and health of the elderly and children. However, current systems do not adequately detect abnormalities that take into account the user's emotional state, which can lead to delayed responses when an abnormality occurs. Furthermore, systems that simply measure biometric data have the challenge of making it difficult to respond appropriately to psychological states such as stress and anxiety in users.

[1552] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1553] In this invention, the server includes an AI analysis unit, an emotion engine unit, and a notification unit, which enables real-time detection of abnormalities and rapid response while taking into account both biometric data and emotion data.

[1554] The "sensor means" is a device for measuring biological data such as heart rate, blood pressure, body temperature, location information, and activity information.

[1555] The "transmitting means" is a communication device for transmitting data measured by the sensor means to the server.

[1556] "AI analysis means" refers to an artificial intelligence algorithm that analyzes received data in real time, compares it with normal ranges, and detects abnormal values ​​and behavior.

[1557] The "notification means" is a device that issues an alert to the user when an abnormality is detected by the AI ​​analysis means.

[1558] The "SOS button means" is a device that can be operated by a user to send an SOS signal in an emergency.

[1559] The "emotion engine means" is an algorithm for analyzing the user's voice and facial expression data and recognizing the user's emotional state.

[1560] An "alert" is a warning message that is sent to the user or a close relative when an abnormality is detected.

[1561] An "interval" is a specified time interval for sending data to the server.

[1562] This system monitors the health status and location information of elderly people and children in real time and promptly notifies users when abnormalities are detected. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to comprehensively evaluate both biometric data and emotion data. This system consists of a wristband or necklace-style sensor device, a server that analyzes the data, a user who receives notifications, and an emotion engine that recognizes the user's emotions.

[1563] 1. Sensor device (terminal)

[1564] The sensor device is equipped with sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information. This sensor device is available in the form of a wristband or necklace, making it easy for elderly people and children to wear on a daily basis. It also has a voice recognition function and a camera function for capturing voice and facial expression data. The sensor device also includes a communication module for transmitting the measured data to a server.

[1565] 2. Server (Central Management System)

[1566] The server receives data sent from the sensor devices and stores it in a database. The received data is analyzed in real time by AI analysis means. The AI ​​analysis means compares biometric data such as heart rate, blood pressure, body temperature, location information, and activity information with normal range data and executes algorithms to detect abnormal values ​​and behavior. The server also incorporates an emotion engine, which has the function of analyzing the user's emotional state. The emotion engine recognizes the user's emotions by analyzing the user's voice data and facial expression data. This emotional information is also stored on the server and is comprehensively evaluated along with an analysis of the user's health status.

[1567] 3. Notification and Emergency Response (User)

[1568] Users (close relatives and caregivers) who receive alerts via notification methods can check the notifications in real time through a smartphone or tablet application. The alerts include the time of the abnormality, detailed data, current location information, and information about the user's emotional state. Based on this information, users can take prompt action.

[1569] For example, if an elderly person's heart rate shows abnormal values, the user will receive a push notification and can view the details and emotional state in the app, after which the user can be contacted directly or medical assistance can be arranged if necessary.

[1570] Specific examples

[1571] Example 1: Detecting abnormal heart rate with emotional fluctuations

[1572] 1. Device: The heart rate sensor measures the heart rate and sends the data to the server. The device also acquires the user's emotional data through voice recognition.

[1573] 2. Server: The server analyzes the received heart rate data and emotion data. If an abnormal value is detected, it evaluates the importance of the abnormality taking into account the emotion data.

[1574] 3. Server: If an abnormal heart rate is detected and the emotion engine detects emotional data indicating stress or anxiety, it generates alert information and sends an alert to close relatives or caregivers via notification means.

[1575] 4. User: Next of kin will receive a push notification to view detailed data and emotional state, assess the situation, contact the user if necessary, and arrange medical services.

[1576] Example 2: Fall and panic detection and notification

[1577] 1. Device: The accelerometer monitors the user's movements and detects abnormal acceleration. The voice recognition function also captures the user's emotional data (such as out-of-range tone of voice).

[1578] 2. Server: The server receives and analyzes the abnormal behavior data and emotion data. If it determines that there is a high possibility of a fall and the emotion engine detects emotion data indicating panic or fear, it generates an alert.

[1579] 3. Server: Notifies next of kin and caregivers of fall and panic alerts.

[1580] 4. User: Next of kin receives push notification to check abnormal behavior and emotional state, and responds quickly, arranging for help if necessary.

[1581] Example prompt

[1582] "Describe a scenario in which you want to detect abnormal heart rates and emotional fluctuations in an elderly person."

[1583] "How do you alert me when my child falls and panics?"

[1584] This system comprehensively monitors the health and emotions of elderly people and children, improving the safety and quality of life of users.

[1585] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1586] Step 1:

[1587] Device: Measures heart rate, blood pressure, body temperature, location, and activity information.

[1588] How it works: Various sensors installed on the device continuously monitor the user's biometric data and collect data at regular intervals.

[1589] Input: User's biological status (heart rate, blood pressure, body temperature, location information, activity information)

[1590] Output: Biometric data set (heart rate, blood pressure, temperature, location, activity)

[1591] Step 2:

[1592] Terminal: Analyzes voice and facial expression data using an emotion engine to generate emotion data.

[1593] How it works: Using voice recognition and camera functions, the user's tone of voice and facial expressions are collected and analyzed by the emotion engine.

[1594] Input: User's voice data and image data (facial expressions)

[1595] Output: Emotion data (stress, anxiety, joy, etc.)

[1596] Step 3:

[1597] Terminal: Sends collected sensor data and emotion data to the server via the communication module.

[1598] Operation: Data is collected within the sensor device and transferred to the server via wireless communication (Wi-Fi, Bluetooth, etc.).

[1599] Input: Biometric dataset and emotion data

[1600] Output: Data packets (biometric dataset, emotion data) to the server

[1601] Step 4:

[1602] Server: The server receives the data sent from the device.

[1603] Operation: The server receives data via the communication protocol and stores it in a receive buffer.

[1604] Input: Data packets sent from the device

[1605] Output: Raw data in the receive buffer

[1606] Step 5:

[1607] Server: Stores the received data in a database.

[1608] How it works: Connects to a database and stores data by time.

[1609] Input: Raw data in the receive buffer

[1610] Output: Structured data stored in a database

[1611] Step 6:

[1612] Server: Analyzes the stored data in real time using AI analysis methods.

[1613] How it works: It uses AI models to analyze biometric data and compare it to normal ranges. If an abnormality is detected, it highlights it.

[1614] Input: Structured data in a database

[1615] Output: Abnormality detection result and its detailed data

[1616] Step 7:

[1617] Server: The emotion engine analyzes voice and facial expression data to recognize the user's emotional state.

[1618] How it works: The emotion engine analyzes subtle changes in vocal tone and facial expressions to determine emotional states (e.g., stress, joy, anxiety).

[1619] Input: Voice and facial expression data in the database

[1620] Output: Emotion analysis results

[1621] Step 8:

[1622] Server: Generates notifications when anomalies are detected based on data analysis results and emotion data.

[1623] Behavior: If an abnormal value is detected and the sentiment is unstable, a notification message is generated and linked to the notification system.

[1624] Input: Anomaly detection results and emotion analysis results

[1625] Output: Information message

[1626] Step 9:

[1627] Server: Sends alerts to the smartphones or tablets of relatives or caregivers through a notification system.

[1628] What it does: Sends real-time alerts using notification protocols (e.g., push notifications, SMS).

[1629] Input: Notification message

[1630] Output: Push notification to user device

[1631] Step 10:

[1632] Users: Receive notifications and view detailed data in an application on their smartphone or tablet.

[1633] What it does: Tap the push notification to open the app and check the abnormal data and emotional state.

[1634] Input: Push notification to user device

[1635] Output: Detailed data and emotional state displayed on the application

[1636] Step 11:

[1637] User: Contacting users or providing emergency response as needed.

[1638] How it works: Based on the notification, the system will contact the user via phone or messaging app and arrange for medical services or rescue operations depending on the situation.

[1639] Input: Detailed data and emotional state displayed on the application

[1640] Output: User's response actions (contact, medical assistance, rescue operation)

[1641] (Application example 2)

[1642] 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."

[1643] Monitoring the health and location information of elderly people and children in real time and responding promptly when abnormalities are detected is an important issue in today's society. However, existing monitoring systems are limited to simply monitoring data such as heart rate and body temperature, making it difficult to provide a comprehensive response that takes into account the user's emotional state. As a result, true emergencies can be overlooked or unnecessary alerts can be generated. Furthermore, there is a risk of delayed response in emergencies due to a lack of systems in place to enable relatives and caregivers to respond promptly.

[1644] 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 an AI analysis means for analyzing data measured by the sensor means, an emotion engine for analyzing the emotional state of the user, and a notification means for issuing an alert when an abnormality is detected. This makes it possible to comprehensively monitor the health and emotional states of elderly people and children, and to respond quickly when an abnormality occurs.

[1645] The "health monitoring system" is a system that monitors the health status and location information of elderly people and children in real time, and responds quickly when an abnormality is detected.

[1646] The "sensor means" is a device including various sensors for measuring heart rate, blood pressure, body temperature, location information, activity information, voice data, and facial expression data.

[1647] The "transmitting means" is a device that includes a communication module for transmitting data measured by the sensor device to the server.

[1648] The "AI analysis means" has the function of analyzing the data received by the server, comparing it with data within the normal range, and executing an algorithm to detect abnormal values ​​or abnormal behavior.

[1649] An "emotion engine" is a software engine that has the function of analyzing a user's voice data and facial expression data and recognizing the user's emotional state.

[1650] "Notification means" refers to a means for sending an alert to next of kin or caregivers when an abnormality is detected by the AI ​​analysis means and emotion engine.

[1651] "Communication means" refers to a means for informing relatives or caregivers of the health and emotional state of the elderly or child in real time via notification means.

[1652] "SOS Button Means" means a device that includes a button that allows a user or their next of kin to manually initiate an emergency alert in the event of an emergency.

[1653] The "wristband or necklace type sensor means" is a sensor device that can be easily worn in daily life and can measure heart rate, blood pressure, body temperature, location information, and activity information.

[1654] This is a health monitoring system that comprehensively monitors the health and emotional states of the elderly and children, enabling rapid response in the event of an abnormality. The basic components of this system are a wristband or necklace-type sensor device, a server, a notification means, and an SOS button means for emergency response.

[1655] 1. Sensor Devices

[1656] The sensor device includes various sensors for measuring heart rate, blood pressure, body temperature, location information, activity information, as well as voice and facial expression data. This allows it to acquire a wide range of data while being easy for elderly people and children to wear on a daily basis. The sensor device is equipped with a communication module for transmitting the measured data to a server.

[1657] 2. Server

[1658] The server receives and analyzes the data sent by the sensor device. This involves the use of an AI analysis means and emotion engine. The AI ​​analysis means analyzes the received health data in real time, comparing it with normal range data to detect outliers and abnormal behavior. The emotion engine analyzes voice data and facial expression data to identify the user's emotional state. If the server detects an abnormality based on this data, it immediately generates an alert.

[1659] 3. Means of notification

[1660] The notification mechanism is responsible for sending alerts generated by the server to next of kin or caregivers. Notifications are provided in real time via a smartphone or tablet application, allowing for immediate sharing of information about the time of the anomaly, detailed data, current location, and emotional state.

[1661] 4. Emergency Response Measures

[1662] The emergency response measures include an SOS button that can be manually operated by the user in an emergency, which immediately initiates an emergency call to request help.

[1663] The processing of the program for realizing this system will be explained below.

[1664] Program processing

[1665] The server receives data sent from the sensor device at regular intervals. The server first analyzes the health data using AI analysis tools to check for any abnormal values. Next, the emotion engine analyzes the voice and facial expression data to identify the user's emotional state. If an abnormality is detected, an alert is generated based on this information and sent promptly to next of kin or caregivers via notification tools. The notification includes the time the abnormality occurred, detailed health data, location information, and emotional state.

[1666] Hardware and software used

[1667] Sensor devices: Includes sensors for measuring heart rate, blood pressure, body temperature, location information, activity information, voice data, and facial expression data.

[1668] Server: Contains AI analysis tools and emotion engine.

[1669] Communication modules: Modules for sending data (e.g., the requests library).

[1670] Notification System: The system for sending alerts (e.g. NotificationSystem).

[1671] Specific examples

[1672] If an elderly person's heart rate is abnormally high and the emotion engine's stress emotion analysis results show a high value:

[1673] "User A's heart rate is abnormally high, and the stress emotion analysis results from the emotion engine indicate a high value. Their current location is ____. Please take appropriate action immediately."

[1674] If a child falls and the emotion engine detects emotion data that indicates fear or panic:

[1675] "A child has fallen and the emotion engine has detected emotion data indicating fear or panic. Current location: ____. Immediate response required."

[1676] This system will enable comprehensive monitoring of the health and emotional state of the elderly and children, and will enable prompt response if any abnormalities occur.

[1677] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1678] Step 1:

[1679] The sensor device measures the heart rate, blood pressure, body temperature, location information, activity information, voice data, and facial expression data of elderly people and children.

[1680] Input: Heart rate, blood pressure, body temperature, location information, activity information, voice data, facial expression data

[1681] Output: Measurement data

[1682] How it works: The sensor device is worn on the body of an elderly person or child, and the built-in sensors collect health and emotional data in real time.

[1683] Step 2:

[1684] The measurement data acquired by the sensor device is sent to the server.

[1685] Input: Measurement data

[1686] Output: Data sent to the server

[1687] Specific operation: Data is sent to the server at regular intervals using the communication module of the sensor device.

[1688] Step 3:

[1689] The data received by the server is analyzed using AI analysis methods.

[1690] Input: Measurement data

[1691] Output: Analysis results (health status)

[1692] Specific operation: An AI analysis tool running on the server analyzes the received data in real time and compares it with data within the normal range to detect any abnormalities.

[1693] Step 4:

[1694] The server uses an emotion engine to analyze voice data and facial expression data to identify the emotional state.

[1695] Input: Voice data, facial expression data

[1696] Output: Emotional state

[1697] How it works: The emotion engine on the server uses voice and image recognition technology to identify the user's emotional state (e.g., stress, anxiety, panic, etc.).

[1698] Step 5:

[1699] The server detects abnormalities based on the analysis results and emotional state.

[1700] Input: Analysis results, emotional state

[1701] Output: Abnormality detection

[1702] Specific behavior: Match the output of the AI ​​analysis method with the emotion engine to determine whether an abnormal health condition and a dangerous emotional state are detected simultaneously.

[1703] Step 6:

[1704] If the server detects an abnormality, it generates an alert.

[1705] Input: Anomaly detection results (health status and emotional state)

[1706] Output: Alert information

[1707] Specific behavior: When an anomaly is detected, the server generates alert information including the specific anomaly content, time, location information, and emotional state.

[1708] Step 7:

[1709] The server generates alert information and sends it to a close relative or caregiver via a notification means.

[1710] Input: Alert information

[1711] Output: Notification message (e.g. push notification)

[1712] Specific operation: Alert information is sent in real time via a smartphone application or email, and details of the abnormality are notified to next of kin or caregivers.

[1713] Step 8:

[1714] Relatives and caregivers will receive a notification message and take appropriate action.

[1715] Input: Notification message

[1716] Output: Carrying out care and emergency response

[1717] What it does: A push notification allows a relative or caregiver to use the app to view detailed health information and emotional state, and then respond or provide help if necessary.

[1718] This will enable real-time monitoring of the health and emotional state of the elderly and children, and rapid response if any abnormalities are detected.

[1719] 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.

[1720] 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.

[1721] 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.

[1722] 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.

[1723] FIG. 9 is a diagram illustrating 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 actions 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.

[1724] 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.

[1725] 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).

[1726] 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.

[1727] 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."

[1728] 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.

[1729] 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).

[1730] 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.

[1731] 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.

[1732] 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.

[1733] 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.

[1734] 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.

[1735] 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.

[1736] 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.

[1737] 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.

[1738] 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.

[1739] 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.

[1740] The following is further disclosed regarding the above embodiment.

[1741] (Claim 1)

[1742] A health monitoring system for watching over elderly people and children,

[1743] Sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information;

[1744] a transmitting means for transmitting data measured by the sensor means to a server;

[1745] AI analysis means for receiving and analyzing the data transmitted by the transmission means;

[1746] a notification means for issuing an alert when an abnormality is detected by the AI ​​analysis means;

[1747] an SOS button means operable by a user in an emergency;

[1748] A system including:

[1749] (Claim 2)

[1750] 10. The system of claim 1, including sensor means in the form of a wristband or necklace.

[1751] (Claim 3)

[1752] 10. The system of claim 1, further comprising: transmitting means configured to transmit a portion of the data to the server at specified intervals.

[1753] "Example 1"

[1754] (Claim 1)

[1755] Sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information;

[1756] a transmitting means for transmitting the data measured by the sensor means to a server at regular intervals (for example, every 5 minutes);

[1757] A communication method that allows users to immediately send data to a server by pressing an SOS button in an emergency.

[1758] AI analysis means for receiving and analyzing data transmitted by the transmission means and emergency communication means;

[1759] a notification means for promptly notifying a close relative or a caregiver when an abnormality is detected by the AI ​​analysis means;

[1760] A system including:

[1761] (Claim 2)

[1762] 10. The system of claim 1, including sensor means in the form of a wristband or necklace.

[1763] (Claim 3)

[1764] 10. The system of claim 1, further comprising: transmitting means configured to transmit a portion of the data to the server at specified intervals.

[1765] "Application Example 1"

[1766] (Claim 1)

[1767] A health monitoring system for watching over elderly people and children,

[1768] Sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information;

[1769] a transmitting means for transmitting data measured by the sensor means to a server;

[1770] AI analysis means for receiving and analyzing the data transmitted by the transmission means;

[1771] a notification means for issuing an alert when an abnormality is detected by the AI ​​analysis means;

[1772] an SOS button means operable by a user in an emergency;

[1773] transmitting means configured to transmit a portion of the data to a server at specified intervals;

[1774] the notification means is a smartphone application that performs push notifications;

[1775] A means for notifying in real time when an abnormality is detected by the smartphone application;

[1776] A system including:

[1777] (Claim 2)

[1778] 10. The system of claim 1, including sensor means in the form of a wristband or necklace.

[1779] (Claim 3)

[1780] 10. The system of claim 1, further comprising means for determining abnormalities in real time by combining location information and abnormal heart rate values.

[1781] "Example 2: Combining Emotion Engines"

[1782] (Claim 1)

[1783] A health monitoring system for watching over elderly people and children,

[1784] Sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information;

[1785] a transmitting means for transmitting data measured by the sensor means to a server;

[1786] AI analysis means for receiving and analyzing the data transmitted by the transmission means;

[1787] a notification means for issuing an alert in consideration of the emotional state when an abnormality is detected by the AI ​​analysis means;

[1788] an SOS button means operable by a user in an emergency;

[1789] emotion engine means for analyzing voice and facial expression data of a user to recognize the user's emotional state;

[1790] A system including:

[1791] (Claim 2)

[1792] 10. The system of claim 1, including sensor means in the form of a wristband or necklace.

[1793] (Claim 3)

[1794] 10. The system of claim 1, further comprising: transmitting means configured to transmit a portion of the data to the server at specified intervals.

[1795] "Application example 2 when combining emotion engines"

[1796] (Claim 1)

[1797] A health monitoring system for watching over elderly people and children,

[1798] Sensor means for measuring heart rate, blood pressure, body temperature, location information, activity information, voice data, and facial expression data;

[1799] a transmitting means for transmitting data measured by the sensor means to a server;

[1800] AI analysis means for receiving and analyzing the data transmitted by the transmission means;

[1801] an emotion engine for analyzing the user's emotional state;

[1802] a notification means for issuing an alert when an abnormality is detected by the AI ​​analysis means and the emotion engine;

[1803] a communication means for notifying the elderly person or a child of their health condition or emotional state in real time through a notification means;

[1804] an SOS button means operable by a user in an emergency;

[1805] A system including:

[1806] (Claim 2)

[1807] 10. The system of claim 1, including sensor means in the form of a wristband or necklace.

[1808] (Claim 3)

[1809] 10. The system of claim 1, further comprising: transmitting means configured to transmit a portion of the data to the server at specified intervals. [Explanation of symbols]

[1810] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A health monitoring system for watching over elderly people and children, Sensor means for measuring heart rate, blood pressure, body temperature, location information, and activity information; a transmitting means for transmitting data measured by the sensor means to a server; AI analysis means for receiving and analyzing the data transmitted by the transmission means; a notification means for issuing an alert when an abnormality is detected by the AI ​​analysis means; an SOS button means operable by a user in an emergency; A system including:

2. 10. The system of claim 1, including sensor means in the form of a wristband or necklace.

3. 2. The system of claim 1, further comprising: transmitting means configured to transmit a portion of the data to the server at specified intervals.

Images